sha
null | last_modified
null | library_name
stringclasses 154
values | text
stringlengths 1
900k
| metadata
stringlengths 2
348k
| pipeline_tag
stringclasses 45
values | id
stringlengths 5
122
| tags
sequencelengths 1
1.84k
| created_at
stringlengths 25
25
| arxiv
sequencelengths 0
201
| languages
sequencelengths 0
1.83k
| tags_str
stringlengths 17
9.34k
| text_str
stringlengths 0
389k
| text_lists
sequencelengths 0
722
| processed_texts
sequencelengths 1
723
| tokens_length
sequencelengths 1
723
| input_texts
sequencelengths 1
61
| embeddings
sequencelengths 768
768
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null | null | timm | # Model card for nextvit_small.bd_in1k_384
A Next-ViT image classification model. Trained on ImageNet-1k by paper authors.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model Stats:**
- Params (M): 31.8
- GMACs: 17.0
- Activations (M): 51.7
- Image size: 384 x 384
- **Dataset:** ImageNet-1k
- **Papers:**
- Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios: https://arxiv.org/abs/2207.05501
- **Original:** https://github.com/bytedance/Next-ViT
## Model Usage
### Image Classification
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model('nextvit_small.bd_in1k_384', pretrained=True)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
top5_probabilities, top5_class_indices = torch.topk(output.softmax(dim=1) * 100, k=5)
```
### Feature Map Extraction
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model(
'nextvit_small.bd_in1k_384',
pretrained=True,
features_only=True,
)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
for o in output:
# print shape of each feature map in output
# e.g.:
# torch.Size([1, 96, 96, 96])
# torch.Size([1, 256, 48, 48])
# torch.Size([1, 512, 24, 24])
# torch.Size([1, 1024, 12, 12])
print(o.shape)
```
### Image Embeddings
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model(
'nextvit_small.bd_in1k_384',
pretrained=True,
num_classes=0, # remove classifier nn.Linear
)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor
# or equivalently (without needing to set num_classes=0)
output = model.forward_features(transforms(img).unsqueeze(0))
# output is unpooled, a (1, 1024, 12, 12) shaped tensor
output = model.forward_head(output, pre_logits=True)
# output is a (1, num_features) shaped tensor
```
## Model Comparison
### By Top-1
|model |top1 |top1_err|top5 |top5_err|param_count|
|---------------------------------|------|--------|------|--------|-----------|
|nextvit_large.bd_ssld_6m_in1k_384|86.542|13.458 |98.142|1.858 |57.87 |
|nextvit_base.bd_ssld_6m_in1k_384 |86.352|13.648 |98.04 |1.96 |44.82 |
|nextvit_small.bd_ssld_6m_in1k_384|85.964|14.036 |97.908|2.092 |31.76 |
|nextvit_large.bd_ssld_6m_in1k |85.48 |14.52 |97.696|2.304 |57.87 |
|nextvit_base.bd_ssld_6m_in1k |85.186|14.814 |97.59 |2.41 |44.82 |
|nextvit_large.bd_in1k_384 |84.924|15.076 |97.294|2.706 |57.87 |
|nextvit_small.bd_ssld_6m_in1k |84.862|15.138 |97.382|2.618 |31.76 |
|nextvit_base.bd_in1k_384 |84.706|15.294 |97.224|2.776 |44.82 |
|nextvit_small.bd_in1k_384 |84.022|15.978 |96.99 |3.01 |31.76 |
|nextvit_large.bd_in1k |83.626|16.374 |96.694|3.306 |57.87 |
|nextvit_base.bd_in1k |83.472|16.528 |96.656|3.344 |44.82 |
|nextvit_small.bd_in1k |82.61 |17.39 |96.226|3.774 |31.76 |
## Citation
```bibtex
@article{li2022next,
title={Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios},
author={Li, Jiashi and Xia, Xin and Li, Wei and Li, Huixia and Wang, Xing and Xiao, Xuefeng and Wang, Rui and Zheng, Min and Pan, Xin},
journal={arXiv preprint arXiv:2207.05501},
year={2022}
}
```
| {"license": "apache-2.0", "library_name": "timm", "tags": ["image-classification", "timm"], "datasets": ["imagenet-1k"]} | image-classification | timm/nextvit_small.bd_in1k_384 | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2207.05501",
"license:apache-2.0",
"region:us"
] | 2024-02-11T00:32:56+00:00 | [
"2207.05501"
] | [] | TAGS
#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #arxiv-2207.05501 #license-apache-2.0 #region-us
| Model card for nextvit\_small.bd\_in1k\_384
===========================================
A Next-ViT image classification model. Trained on ImageNet-1k by paper authors.
Model Details
-------------
* Model Type: Image classification / feature backbone
* Model Stats:
+ Params (M): 31.8
+ GMACs: 17.0
+ Activations (M): 51.7
+ Image size: 384 x 384
* Dataset: ImageNet-1k
* Papers:
+ Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios: URL
* Original: URL
Model Usage
-----------
### Image Classification
### Feature Map Extraction
### Image Embeddings
Model Comparison
----------------
### By Top-1
| [
"### Image Classification",
"### Feature Map Extraction",
"### Image Embeddings\n\n\nModel Comparison\n----------------",
"### By Top-1"
] | [
"TAGS\n#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #arxiv-2207.05501 #license-apache-2.0 #region-us \n",
"### Image Classification",
"### Feature Map Extraction",
"### Image Embeddings\n\n\nModel Comparison\n----------------",
"### By Top-1"
] | [
47,
5,
6,
12,
5
] | [
"passage: TAGS\n#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #arxiv-2207.05501 #license-apache-2.0 #region-us \n### Image Classification### Feature Map Extraction### Image Embeddings\n\n\nModel Comparison\n----------------### By Top-1"
] | [
-0.09636243432760239,
0.08958321809768677,
-0.0038628829643130302,
0.0920121967792511,
0.07080025970935822,
0.01051587238907814,
0.07051923871040344,
0.08707913011312485,
0.041644323617219925,
-0.0504513680934906,
0.10490208119153976,
0.13758918642997742,
0.05837717652320862,
0.07992157340049744,
-0.00456247990950942,
-0.25518304109573364,
0.05392490699887276,
-0.0037102841306477785,
0.04124191403388977,
0.11982481181621552,
0.0811581015586853,
-0.13299685716629028,
0.08726481348276138,
-0.011344862170517445,
-0.07473120838403702,
0.03536978363990784,
0.016875024884939194,
-0.07811307162046432,
0.10734886676073074,
-0.05763684958219528,
0.07212948799133301,
0.04106689617037773,
0.07298385351896286,
-0.14646664261817932,
0.03702881932258606,
0.024171456694602966,
-0.0870424285531044,
0.08159748464822769,
0.21527807414531708,
-0.03086278587579727,
0.04759849235415459,
0.002334655961021781,
-0.05914333090186119,
-0.000889539544004947,
-0.06876467168331146,
-0.1538228690624237,
-0.053771596401929855,
0.20008590817451477,
0.1568566858768463,
0.03323731943964958,
-0.01615499146282673,
0.10579373687505722,
-0.172556072473526,
0.09133937209844589,
0.1411391943693161,
-0.2234921157360077,
-0.03339390829205513,
0.08343690633773804,
-0.03148240968585014,
0.025646328926086426,
-0.06155110523104668,
0.0226140059530735,
0.01559405867010355,
-0.021278686821460724,
0.03511078283190727,
-0.00010415440920041874,
-0.08336224406957626,
-0.00850435346364975,
-0.13194997608661652,
-0.08259618282318115,
0.2157735526561737,
0.15542617440223694,
0.043466903269290924,
-0.039130937308073044,
-0.09658254683017731,
0.0024254319723695517,
-0.03501230850815773,
0.06675831228494644,
0.061602070927619934,
0.025460610166192055,
0.022108787670731544,
0.058910977095365524,
-0.1582302749156952,
-0.021096467971801758,
-0.14157257974147797,
-0.09625858813524246,
0.029925785958766937,
0.10537519305944443,
-0.09454554319381714,
0.08061660081148148,
-0.03443600609898567,
-0.14599406719207764,
0.06627871096134186,
-0.09023762494325638,
0.07418705523014069,
0.03096098266541958,
0.0811329036951065,
0.034722648561000824,
0.11329144984483719,
0.12022861838340759,
-0.049228399991989136,
0.03554627299308777,
-0.07428254932165146,
0.1433194875717163,
0.030554546043276787,
0.04803347587585449,
-0.16111505031585693,
0.04310738667845726,
0.060195811092853546,
0.05785948410630226,
0.09791151434183121,
0.004559491761028767,
-0.09023717790842056,
0.011160574853420258,
0.11905037611722946,
0.02985546737909317,
0.07290509343147278,
-0.009493676014244556,
-0.1015884131193161,
-0.052425313740968704,
0.22813910245895386,
-0.027120118960738182,
-0.01574735902249813,
0.014835639856755733,
-0.048023954033851624,
-0.021620020270347595,
0.04129086062312126,
0.028226889669895172,
-0.024548375979065895,
0.056369829922914505,
-0.06721023470163345,
0.06194429472088814,
0.00911510270088911,
-0.015473698265850544,
0.06822172552347183,
-0.04013986140489578,
-0.004903791937977076,
-0.1285521686077118,
-0.12239458411931992,
0.048230886459350586,
0.04236266762018204,
-0.026844745501875877,
-0.014713792130351067,
0.035568416118621826,
-0.061998117715120316,
-0.0055758231319487095,
-0.014071053825318813,
-0.014154491014778614,
-0.1006024107336998,
0.07227983325719833,
-0.10254475474357605,
0.08134932816028595,
-0.04323108494281769,
0.01545912679284811,
-0.14019621908664703,
0.036984339356422424,
-0.19867101311683655,
0.015264135785400867,
-0.0705023780465126,
0.11521919071674347,
-0.09675919264554977,
-0.08684706687927246,
-0.11065774410963058,
-0.04284289851784706,
-0.040110647678375244,
0.18117506802082062,
-0.18168941140174866,
-0.009601790457963943,
0.1507936716079712,
-0.1215595230460167,
-0.1356934905052185,
0.08678647130727768,
-0.007943321019411087,
-0.11169861257076263,
0.027826359495520592,
0.2409891039133072,
-0.04862334951758385,
-0.043951164931058884,
-0.08361595869064331,
0.07064300030469894,
-0.08250455558300018,
-0.02629409171640873,
0.11508657783269882,
0.0224674791097641,
-0.035860173404216766,
0.004903212655335665,
-0.12213941663503647,
0.08489926159381866,
-0.057531312108039856,
-0.094296894967556,
-0.02914511226117611,
-0.01777004636824131,
0.08389952033758163,
0.07179960608482361,
0.02096518687903881,
-0.06373847275972366,
-0.05508701503276825,
-0.0902327448129654,
0.09009650349617004,
0.040365882217884064,
-0.04027532786130905,
-0.06958407163619995,
0.17108984291553497,
-0.1287860870361328,
-0.03132127597928047,
-0.13895772397518158,
0.018626950681209564,
0.022028805688023567,
0.02573796547949314,
0.0333290696144104,
-0.10014960914850235,
0.05745252966880798,
0.006887424271553755,
-0.029692038893699646,
-0.12299051880836487,
0.0012409249320626259,
-0.017744330689311028,
0.011388768441975117,
-0.2065012902021408,
-0.01298505812883377,
0.00505823502317071,
0.1242038831114769,
-0.10349573940038681,
-0.053265780210494995,
0.04835658147931099,
0.1337202936410904,
0.027385259047150612,
0.031249627470970154,
0.019459009170532227,
-0.06202981248497963,
-0.059308454394340515,
-0.048234812915325165,
0.10398460924625397,
-0.03413105010986328,
0.008669856004416943,
0.07251276820898056,
-0.009972739033401012,
0.12003304064273834,
0.19731907546520233,
-0.2973620295524597,
0.007794809993356466,
-0.02080945298075676,
-0.02789013646543026,
0.022417211905121803,
-0.03611164540052414,
0.03486190363764763,
-0.04420599341392517,
-0.025843823328614235,
0.059744030237197876,
-0.10342248529195786,
-0.01871756836771965,
0.017169242724776268,
-0.023166878148913383,
-0.08954495191574097,
0.08481862396001816,
0.22792288661003113,
-0.2730877697467804,
0.12495702505111694,
0.3472680151462555,
0.01769988238811493,
0.03722153231501579,
-0.06515514105558395,
-0.05847856402397156,
0.008726534433662891,
0.040092721581459045,
-0.04815570265054703,
0.17144452035427094,
-0.0958382859826088,
0.033190853893756866,
0.08965327590703964,
-0.051429759711027145,
0.025637555867433548,
-0.1778573989868164,
-0.018345139920711517,
0.0004289354255888611,
-0.04757937416434288,
-0.10216343402862549,
-0.01934841461479664,
0.016197295859456062,
0.12683509290218353,
-0.04296351224184036,
-0.09329916536808014,
0.03446105122566223,
-0.036928776651620865,
-0.07484008371829987,
0.17601685225963593,
-0.117931067943573,
-0.3162304759025574,
-0.05009270831942558,
0.0549594983458519,
-0.08267761766910553,
-0.009545600973069668,
0.035816580057144165,
-0.1256653219461441,
-0.0509430356323719,
-0.07536083459854126,
-0.1505686491727829,
0.05733085423707962,
-0.0034857760183513165,
-0.04586903005838394,
0.03773486614227295,
0.059781093150377274,
-0.07817638665437698,
-0.028156321495771408,
-0.018001554533839226,
0.005503889173269272,
0.15499843657016754,
-0.027998195961117744,
0.1038590669631958,
0.13644422590732574,
-0.003447622526437044,
0.04132360592484474,
-0.001089713303372264,
0.20400109887123108,
-0.06735511124134064,
0.05735619366168976,
0.18575458228588104,
-0.0024501068983227015,
0.07627682387828827,
0.1745310127735138,
0.04309722036123276,
-0.030743319541215897,
-0.03750548139214516,
0.000864303030539304,
-0.045119937509298325,
-0.14287930727005005,
-0.07861533761024475,
-0.02234150469303131,
0.04409110173583031,
0.12322201579809189,
0.10163462162017822,
0.02745729126036167,
0.09865599870681763,
-0.03958142548799515,
-0.09156903624534607,
0.06401792168617249,
-0.00019907676323782653,
-0.0037631443701684475,
-0.022144807502627373,
0.08983879536390305,
-0.0697895959019661,
-0.06767483800649643,
0.11333473026752472,
0.032611191272735596,
0.2400340586900711,
0.051599565893411636,
-0.06209759786725044,
0.09257194399833679,
0.24370291829109192,
0.07144607603549957,
0.05890403315424919,
-0.0032388153485953808,
-0.00380648672580719,
-0.021203579381108284,
-0.08573547005653381,
0.07094957679510117,
0.01739443838596344,
0.018660342320799828,
-0.03753918409347534,
0.000742999545764178,
-0.044418517500162125,
0.1160462275147438,
0.11206614226102829,
0.10507932305335999,
-0.2926905155181885,
0.11079080402851105,
0.04275360703468323,
0.045395344495773315,
-0.034812673926353455,
0.06698943674564362,
0.012286308221518993,
-0.041727215051651,
0.13768845796585083,
-0.056010253727436066,
0.09458514302968979,
-0.042052850127220154,
-0.03644431754946709,
-0.012696283869445324,
-0.09396157413721085,
0.026140261441469193,
0.08652861416339874,
-0.0210878923535347,
0.27003639936447144,
0.004165979567915201,
-0.06623334437608719,
-0.09087180346250534,
-0.05061552673578262,
0.12832948565483093,
0.1833341121673584,
0.1896253377199173,
0.03886926546692848,
-0.05608430132269859,
-0.08892632275819778,
-0.1447414606809616,
-0.012716415338218212,
0.03971119597554207,
-0.039739686995744705,
-0.025162354111671448,
-0.0050504435785114765,
-0.0464717335999012,
-0.02259298786520958,
0.04580671712756157,
-0.13984273374080658,
-0.01735411398112774,
-0.04374581202864647,
0.003685730043798685,
0.0006909397779963911,
-0.08692880719900131,
-0.047926634550094604,
-0.0973883792757988,
-0.002803226001560688,
-0.05909522622823715,
-0.05187579244375229,
-0.0734202116727829,
0.0222348440438509,
0.07362000644207001,
-0.05830860882997513,
0.06837311387062073,
-0.045819833874702454,
0.0927729606628418,
0.031593549996614456,
-0.18570174276828766,
0.10865960270166397,
-0.10344094038009644,
-0.03045581839978695,
-0.06148960813879967,
0.1445760875940323,
-0.037091437727212906,
0.02203739620745182,
0.04077836871147156,
0.04658257216215134,
-0.0338616818189621,
-0.05892520770430565,
0.07338255643844604,
-0.0035599414259195328,
0.05858312174677849,
0.1442960649728775,
-0.024055475369095802,
-0.16970200836658478,
-0.05183783918619156,
0.03064536489546299,
0.1433953493833542,
0.23811836540699005,
-0.10356022417545319,
0.047636982053518295,
0.08170390874147415,
0.00841857772320509,
-0.28868967294692993,
-0.03817283734679222,
-0.0369725227355957,
-0.06995920091867447,
0.12804023921489716,
-0.055167511105537415,
0.13360820710659027,
0.1213274747133255,
-0.10185312479734421,
0.15767796337604523,
-0.2567442059516907,
-0.08861517161130905,
0.14742843806743622,
0.09302102774381638,
0.10625413805246353,
-0.1382579356431961,
-0.05579283460974693,
-0.022313952445983887,
-0.029846467077732086,
0.09247719496488571,
-0.09109682589769363,
0.007692293263971806,
0.014140667393803596,
-0.10431914776563644,
-0.005628937855362892,
-0.03194456920027733,
0.15690839290618896,
-0.038857169449329376,
0.13853172957897186,
-0.0944456234574318,
-0.04659556224942207,
0.10079418122768402,
-0.022844886407256126,
0.05383231118321419,
-0.029970282688736916,
0.07758761942386627,
-0.10475114732980728,
0.039220865815877914,
-0.07289217412471771,
0.04224325343966484,
0.0312870629131794,
-0.006059125531464815,
-0.09011576324701309,
0.022292472422122955,
-0.01717025600373745,
0.04759751632809639,
0.1810881346464157,
0.042498890310525894,
-0.012072842568159103,
0.12267015874385834,
0.05375862866640091,
-0.07609573006629944,
-0.13843262195587158,
-0.14803095161914825,
-0.056710224598646164,
0.0738082081079483,
-0.1676865667104721,
0.06290600448846817,
0.07904090732336044,
0.019464170560240746,
0.07636241614818573,
0.045887723565101624,
-0.0008675057906657457,
0.001641564886085689,
0.20310163497924805,
-0.1314924955368042,
-0.09343049675226212,
-0.05791308358311653,
0.04098711907863617,
0.028505617752671242,
0.00886484608054161,
0.07239209860563278,
0.008463451638817787,
-0.026107817888259888,
0.0298012625426054,
0.07830777764320374,
-0.006136888172477484,
0.08295531570911407,
0.12394069135189056,
-0.0060889539308846,
-0.10868153721094131,
0.18649159371852875,
0.06119316443800926,
-0.08111705631017685,
-0.09351049363613129,
0.06703319400548935,
-0.07271377742290497,
-0.12107553333044052,
0.04937610402703285,
0.0945400819182396,
-0.07703658193349838,
-0.0776614174246788,
-0.0706222653388977,
-0.07685469835996628,
0.03496779501438141,
0.01387622207403183,
0.10773573070764542,
-0.009869271889328957,
0.0817493423819542,
-0.0626157820224762,
0.02628154493868351,
0.11985771358013153,
0.023420168086886406,
0.038403842598199844,
-0.2523103654384613,
-0.10268673300743103,
0.046657927334308624,
0.10561618208885193,
-0.0617174357175827,
0.004182941745966673,
-0.03356100246310234,
0.04363083466887474,
-0.11612074077129364,
0.10042599588632584,
-0.0757952407002449,
-0.002078433521091938,
-0.011445282958447933,
-0.021896053105592728,
-0.0636550635099411,
-0.00425998168066144,
-0.11639464646577835,
-0.025922013446688652,
0.016820019111037254,
0.058502040803432465,
-0.10432949662208557,
-0.05939484387636185,
0.07605459541082382,
-0.019433705136179924,
0.10450476408004761,
0.030898744240403175,
-0.04774309694766998,
0.03242281451821327,
-0.1447271853685379,
-0.12981580197811127,
0.14696872234344482,
0.040035273879766464,
-0.054288532584905624,
-0.006394419353455305,
0.054600998759269714,
0.018583253026008606,
-0.0832725465297699,
-0.006612749304622412,
0.012530476786196232,
-0.11224514245986938,
-0.0760449692606926,
-0.11278337985277176,
-0.09584754705429077,
-0.009080572985112667,
0.021960850805044174,
0.12405764311552048,
-0.024803562089800835,
0.15977826714515686,
-0.04413514956831932,
0.02417932264506817,
-0.19591225683689117,
0.019412720575928688,
-0.05799626186490059,
-0.13104338943958282,
-0.14859329164028168,
-0.010428027249872684,
0.010723385028541088,
-0.08510144054889679,
0.15313059091567993,
0.11135957390069962,
-0.06819978356361389,
0.022066732868552208,
0.18543891608715057,
0.03584011644124985,
0.05620575696229935,
0.25769904255867004,
-0.006763666868209839,
-0.046734631061553955,
-0.05830314755439758,
0.03474780544638634,
0.05105675384402275,
-0.059726666659116745,
0.037346258759498596,
0.22248345613479614,
-0.05679071694612503,
-0.00240327138453722,
0.1491062492132187,
-0.03346066176891327,
-0.0932689681649208,
-0.022972092032432556,
-0.021574659273028374,
0.1035420149564743,
0.027149664238095284,
0.10199496895074844,
0.1907235085964203,
-0.10295882821083069,
-0.004274163395166397,
-0.0015320158563554287,
-0.0004767488280776888,
-0.08115294575691223,
-0.22594936192035675,
-0.09717800468206406,
-0.1846923530101776,
0.042454157024621964,
-0.061362091451883316,
-0.04587329179048538,
0.20521362125873566,
0.03862045332789421,
-0.07787402719259262,
0.09076017141342163,
-0.0887233316898346,
-0.08040633052587509,
0.1199001744389534,
0.01809280551970005,
-0.0864848718047142,
0.006439706776291132,
-0.034174174070358276,
0.06858643144369125,
-0.025574255734682083,
-0.03599195554852486,
-0.03487676382064819,
-0.04030521959066391,
0.05564424395561218,
-0.07670509070158005,
-0.09944441169500351,
-0.02929132804274559,
-0.03374217823147774,
-0.0010596479987725616,
0.10414449870586395,
-0.0007069369894452393,
0.05358733609318733,
0.03751286864280701,
0.16146476566791534,
-0.04004666954278946,
-0.04011883959174156,
-0.052436746656894684,
0.08008923381567001,
-0.08877728134393692,
0.019539114087820053,
0.033051736652851105,
-0.08180421590805054,
0.037084661424160004,
0.19037945568561554,
0.21204940974712372,
-0.07453841716051102,
-0.00563496258109808,
-0.04132990911602974,
0.000732084852643311,
-0.016723429784178734,
0.058654095977544785,
0.06952987611293793,
0.1492450088262558,
-0.10297687351703644,
-0.01356273703277111,
-0.07493461668491364,
-0.001375528983771801,
-0.06409166753292084,
0.003850744804367423,
0.09324179589748383,
-0.07001432031393051,
-0.1226971298456192,
0.14917078614234924,
-0.03297191113233566,
0.10340400785207748,
0.10123947262763977,
-0.09865404665470123,
-0.11235126852989197,
-0.02896694466471672,
0.12081532925367355,
0.06542382389307022,
-0.04260534048080444,
-0.11623378843069077,
0.011859663762152195,
-0.05883493646979332,
0.019598329439759254,
-0.22318477928638458,
-0.10542605072259903,
-0.011684350669384003,
0.003907190170139074,
0.26564133167266846,
-0.004232931882143021,
0.07381193339824677,
0.06602168083190918,
-0.00820966251194477,
-0.1161179170012474,
0.030765803530812263,
0.002585484879091382,
-0.000827099138405174,
0.011962628923356533,
0.03402460739016533,
0.015841370448470116,
-0.0929981991648674,
0.08899941295385361,
-0.03186783194541931,
-0.01916445791721344,
0.013043921440839767,
-0.06695821136236191,
-0.08613437414169312,
0.09664905071258545,
-0.09953352808952332,
0.06078430265188217,
0.020012784749269485,
-0.020750101655721664,
-0.04489806666970253,
-0.08876538276672363,
0.022650133818387985,
0.06128743290901184,
-0.11559933423995972,
0.04391907900571823,
0.005354562308639288,
-0.010147674940526485,
-0.06623176485300064,
0.00559185491874814,
-0.07599113136529922,
-0.06817084550857544,
-0.07634287327528,
-0.026138488203287125,
-0.11138242483139038,
0.08232326805591583,
0.15311814844608307,
0.00854517798870802,
0.006425292696803808,
0.07025334984064102,
0.01848892867565155,
0.02869359776377678,
-0.04332093894481659,
-0.04302224889397621
] |
null | null | timm | # Model card for nextvit_small.bd_ssld_6m_in1k
A Next-ViT image classification model. Trained by paper authors on an unknown 6M sample dataset and ImageNet-1k using SSLD distillation.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model Stats:**
- Params (M): 31.8
- GMACs: 5.8
- Activations (M): 17.6
- Image size: 224 x 224
- **Pretrain Dataset:** Unknown-6M
- **Dataset:** ImageNet-1k
- **Papers:**
- Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios: https://arxiv.org/abs/2207.05501
- **Original:** https://github.com/bytedance/Next-ViT
## Model Usage
### Image Classification
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model('nextvit_small.bd_ssld_6m_in1k', pretrained=True)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
top5_probabilities, top5_class_indices = torch.topk(output.softmax(dim=1) * 100, k=5)
```
### Feature Map Extraction
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model(
'nextvit_small.bd_ssld_6m_in1k',
pretrained=True,
features_only=True,
)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
for o in output:
# print shape of each feature map in output
# e.g.:
# torch.Size([1, 96, 56, 56])
# torch.Size([1, 256, 28, 28])
# torch.Size([1, 512, 14, 14])
# torch.Size([1, 1024, 7, 7])
print(o.shape)
```
### Image Embeddings
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model(
'nextvit_small.bd_ssld_6m_in1k',
pretrained=True,
num_classes=0, # remove classifier nn.Linear
)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor
# or equivalently (without needing to set num_classes=0)
output = model.forward_features(transforms(img).unsqueeze(0))
# output is unpooled, a (1, 1024, 7, 7) shaped tensor
output = model.forward_head(output, pre_logits=True)
# output is a (1, num_features) shaped tensor
```
## Model Comparison
### By Top-1
|model |top1 |top1_err|top5 |top5_err|param_count|
|---------------------------------|------|--------|------|--------|-----------|
|nextvit_large.bd_ssld_6m_in1k_384|86.542|13.458 |98.142|1.858 |57.87 |
|nextvit_base.bd_ssld_6m_in1k_384 |86.352|13.648 |98.04 |1.96 |44.82 |
|nextvit_small.bd_ssld_6m_in1k_384|85.964|14.036 |97.908|2.092 |31.76 |
|nextvit_large.bd_ssld_6m_in1k |85.48 |14.52 |97.696|2.304 |57.87 |
|nextvit_base.bd_ssld_6m_in1k |85.186|14.814 |97.59 |2.41 |44.82 |
|nextvit_large.bd_in1k_384 |84.924|15.076 |97.294|2.706 |57.87 |
|nextvit_small.bd_ssld_6m_in1k |84.862|15.138 |97.382|2.618 |31.76 |
|nextvit_base.bd_in1k_384 |84.706|15.294 |97.224|2.776 |44.82 |
|nextvit_small.bd_in1k_384 |84.022|15.978 |96.99 |3.01 |31.76 |
|nextvit_large.bd_in1k |83.626|16.374 |96.694|3.306 |57.87 |
|nextvit_base.bd_in1k |83.472|16.528 |96.656|3.344 |44.82 |
|nextvit_small.bd_in1k |82.61 |17.39 |96.226|3.774 |31.76 |
## Citation
```bibtex
@article{li2022next,
title={Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios},
author={Li, Jiashi and Xia, Xin and Li, Wei and Li, Huixia and Wang, Xing and Xiao, Xuefeng and Wang, Rui and Zheng, Min and Pan, Xin},
journal={arXiv preprint arXiv:2207.05501},
year={2022}
}
```
| {"license": "apache-2.0", "library_name": "timm", "tags": ["image-classification", "timm"], "datasets": ["imagenet-1k", "unknown-6m"]} | image-classification | timm/nextvit_small.bd_ssld_6m_in1k | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"dataset:unknown-6m",
"arxiv:2207.05501",
"license:apache-2.0",
"region:us"
] | 2024-02-11T00:33:06+00:00 | [
"2207.05501"
] | [] | TAGS
#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #dataset-unknown-6m #arxiv-2207.05501 #license-apache-2.0 #region-us
| Model card for nextvit\_small.bd\_ssld\_6m\_in1k
================================================
A Next-ViT image classification model. Trained by paper authors on an unknown 6M sample dataset and ImageNet-1k using SSLD distillation.
Model Details
-------------
* Model Type: Image classification / feature backbone
* Model Stats:
+ Params (M): 31.8
+ GMACs: 5.8
+ Activations (M): 17.6
+ Image size: 224 x 224
* Pretrain Dataset: Unknown-6M
* Dataset: ImageNet-1k
* Papers:
+ Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios: URL
* Original: URL
Model Usage
-----------
### Image Classification
### Feature Map Extraction
### Image Embeddings
Model Comparison
----------------
### By Top-1
| [
"### Image Classification",
"### Feature Map Extraction",
"### Image Embeddings\n\n\nModel Comparison\n----------------",
"### By Top-1"
] | [
"TAGS\n#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #dataset-unknown-6m #arxiv-2207.05501 #license-apache-2.0 #region-us \n",
"### Image Classification",
"### Feature Map Extraction",
"### Image Embeddings\n\n\nModel Comparison\n----------------",
"### By Top-1"
] | [
56,
5,
6,
12,
5
] | [
"passage: TAGS\n#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #dataset-unknown-6m #arxiv-2207.05501 #license-apache-2.0 #region-us \n### Image Classification### Feature Map Extraction### Image Embeddings\n\n\nModel Comparison\n----------------### By Top-1"
] | [
-0.09558708965778351,
0.09347394853830338,
-0.00299403490498662,
0.10520054399967194,
0.07291311025619507,
0.012559691444039345,
0.062246110290288925,
0.08803897351026535,
0.03287670761346817,
-0.041789185255765915,
0.11235252022743225,
0.13096554577350616,
0.05655141547322273,
0.08482521027326584,
-0.015286432579159737,
-0.23364990949630737,
0.05155707150697708,
-0.005953880026936531,
0.056405965238809586,
0.11184614896774292,
0.06843625009059906,
-0.13275767862796783,
0.09081137180328369,
-0.030113454908132553,
-0.07863062620162964,
0.02934487909078598,
0.013566946610808372,
-0.07839283347129822,
0.09259331971406937,
-0.06770337373018265,
0.05526963248848915,
0.04437292739748955,
0.08331260085105896,
-0.1080613061785698,
0.0284743569791317,
0.015033003874123096,
-0.07671426236629486,
0.07311322540044785,
0.20175740122795105,
-0.028766576200723648,
0.02208654396235943,
-0.002298174425959587,
-0.06283358484506607,
-0.009130110032856464,
-0.05433163791894913,
-0.1523350179195404,
-0.06192190572619438,
0.17882226407527924,
0.13364389538764954,
0.05033490061759949,
-0.012173596769571304,
0.12204702198505402,
-0.1740248054265976,
0.08050484210252762,
0.1411627233028412,
-0.21766330301761627,
-0.027000045403838158,
0.08109380304813385,
-0.03788871318101883,
0.034920383244752884,
-0.053310327231884,
0.00964007806032896,
0.027365567162632942,
-0.003837174503132701,
0.030367178842425346,
0.008300426416099072,
-0.07884874939918518,
-0.004154783673584461,
-0.12808267772197723,
-0.07409441471099854,
0.24344520270824432,
0.14758169651031494,
0.03846818208694458,
-0.03928784653544426,
-0.08756875991821289,
0.01031971164047718,
-0.02658696472644806,
0.07799483090639114,
0.05681709945201874,
0.01283130794763565,
-0.008337614126503468,
0.06370620429515839,
-0.1462528258562088,
-0.017349500209093094,
-0.1524721086025238,
-0.08909036219120026,
0.028268098831176758,
0.11880890280008316,
-0.08945166319608688,
0.08243481069803238,
-0.04861928150057793,
-0.1329241842031479,
0.06866148114204407,
-0.08242746442556381,
0.07497505843639374,
0.040115535259246826,
0.07445070892572403,
0.02648226171731949,
0.10421928763389587,
0.10993774980306625,
-0.03075791522860527,
0.02116631343960762,
-0.07143659889698029,
0.1353973001241684,
0.027597026899456978,
0.03184673935174942,
-0.168073832988739,
0.03319035470485687,
0.060989778488874435,
0.07650230079889297,
0.10122565180063248,
-0.0006558281602337956,
-0.08514881134033203,
0.009537837468087673,
0.12851865589618683,
0.017137285321950912,
0.08842682093381882,
-0.008033460937440395,
-0.10018431395292282,
-0.06064440682530403,
0.22916187345981598,
-0.03395469859242439,
-0.020387200638651848,
0.008137711323797703,
-0.05704581364989281,
-0.0239932332187891,
0.048498090356588364,
0.027234245091676712,
-0.02136918529868126,
0.05074744671583176,
-0.07190001755952835,
0.04940683767199516,
0.00571137061342597,
-0.022458702325820923,
0.07695623487234116,
-0.05216311663389206,
-0.006435836665332317,
-0.1175767034292221,
-0.13422934710979462,
0.06017563119530678,
0.03853278607130051,
-0.034127794206142426,
-0.015136833302676678,
0.03270628675818443,
-0.08406492322683334,
0.004329846706241369,
-0.010297833010554314,
-0.0014764930820092559,
-0.09163115173578262,
0.06724830716848373,
-0.08598141372203827,
0.0843457281589508,
-0.059828415513038635,
0.026755349710583687,
-0.14912694692611694,
0.036444246768951416,
-0.1783161163330078,
0.022829068824648857,
-0.07335842400789261,
0.10544736683368683,
-0.09136992692947388,
-0.08565674722194672,
-0.09759186208248138,
-0.05024686083197594,
-0.02591802179813385,
0.17204086482524872,
-0.1921125054359436,
-0.005587227176874876,
0.1273060142993927,
-0.11727612465620041,
-0.13039842247962952,
0.07781845331192017,
0.0012696784688159823,
-0.10486451536417007,
0.019158978015184402,
0.22733600437641144,
-0.075113944709301,
-0.04531674459576607,
-0.10057050734758377,
0.06094831973314285,
-0.06990103423595428,
-0.05881810933351517,
0.12343203276395798,
0.015371610410511494,
-0.041035182774066925,
0.018542125821113586,
-0.10435658693313599,
0.07150362432003021,
-0.06857339292764664,
-0.09679179638624191,
-0.04979955032467842,
-0.02762562781572342,
0.08245130628347397,
0.06977207213640213,
0.023059213533997536,
-0.060269907116889954,
-0.05366865545511246,
-0.08795847743749619,
0.08702987432479858,
0.02715953439474106,
-0.04263463243842125,
-0.06387859582901001,
0.1712300181388855,
-0.1513533890247345,
-0.029068473726511,
-0.14413034915924072,
0.014694181270897388,
0.03241952881217003,
0.026729710400104523,
0.030340705066919327,
-0.11321180313825607,
0.04766267165541649,
0.011228871531784534,
-0.02973194047808647,
-0.10931674391031265,
0.01070065051317215,
-0.016022546216845512,
0.0013052156427875161,
-0.1875678151845932,
-0.02290727198123932,
-0.0012173126451671124,
0.1090201884508133,
-0.10200527310371399,
-0.05544091388583183,
0.03133605420589447,
0.1246073767542839,
0.028024811297655106,
0.02060684747993946,
0.01731315813958645,
-0.0551796518266201,
-0.05820794403553009,
-0.04687844589352608,
0.09801702946424484,
-0.037059664726257324,
-0.006597775500267744,
0.05062747746706009,
-0.00975062046200037,
0.09834805876016617,
0.1868835836648941,
-0.2448369264602661,
0.011397312395274639,
-0.012942364439368248,
-0.03337012976408005,
0.0025844601914286613,
-0.03140377253293991,
0.036910638213157654,
-0.05921214073896408,
-0.031548384577035904,
0.05648422986268997,
-0.1066335141658783,
-0.012599027715623379,
0.027406975626945496,
-0.02050682157278061,
-0.10175776481628418,
0.09351391345262527,
0.21877892315387726,
-0.2656879127025604,
0.12511366605758667,
0.3312479555606842,
0.0008102115243673325,
0.019048422574996948,
-0.06815836578607559,
-0.07529519498348236,
0.0068797096610069275,
0.03470737114548683,
-0.03905649110674858,
0.16271041333675385,
-0.0747879147529602,
0.04001716896891594,
0.09844362735748291,
-0.04895138368010521,
0.024417422711849213,
-0.16585946083068848,
-0.02678094245493412,
-0.019540291279554367,
-0.03999538719654083,
-0.10672440379858017,
-0.00937816221266985,
0.01839459501206875,
0.1217767745256424,
-0.04437003657221794,
-0.08880233764648438,
0.04827999323606491,
-0.03549637272953987,
-0.06528531014919281,
0.17564865946769714,
-0.11833243817090988,
-0.30709517002105713,
-0.04774559289216995,
0.06789609789848328,
-0.0931229218840599,
-0.021504797041416168,
0.03719712793827057,
-0.1190883219242096,
-0.04765754193067551,
-0.079276442527771,
-0.16537484526634216,
0.053101032972335815,
-0.006289829965680838,
-0.02808643877506256,
0.03083314560353756,
0.06294508278369904,
-0.07364541292190552,
-0.030794885009527206,
-0.023397982120513916,
-0.00699926633387804,
0.16569748520851135,
-0.027460401877760887,
0.0983651876449585,
0.1267324835062027,
-0.006489625200629234,
0.036727674305438995,
0.008249090984463692,
0.2078518122434616,
-0.04118591174483299,
0.05342375859618187,
0.1777338981628418,
0.014746671542525291,
0.06999237090349197,
0.1705477088689804,
0.037929099053144455,
-0.027453776448965073,
-0.0358283631503582,
0.007734373211860657,
-0.047374092042446136,
-0.15631341934204102,
-0.08335157483816147,
-0.015884486958384514,
0.04839640110731125,
0.11345633119344711,
0.09474849700927734,
0.015104448422789574,
0.0887218713760376,
-0.036342501640319824,
-0.08028140664100647,
0.04685024917125702,
-0.007394097745418549,
-0.01134442538022995,
-0.009161235764622688,
0.10316181182861328,
-0.06482475996017456,
-0.050376005470752716,
0.10848541557788849,
0.04662366211414337,
0.26863518357276917,
0.02965763956308365,
-0.051108382642269135,
0.0865011140704155,
0.25863707065582275,
0.061141349375247955,
0.060096874833106995,
0.0013740723952651024,
-0.004729153122752905,
-0.012291166000068188,
-0.09081355482339859,
0.07971104234457016,
0.014993593096733093,
0.006302401423454285,
-0.007220427971333265,
-0.007515354547649622,
-0.01882636547088623,
0.10163114219903946,
0.10774721205234528,
0.10965513437986374,
-0.2970282733440399,
0.10182203352451324,
0.03816639259457588,
0.05176613852381706,
-0.027951380237936974,
0.06119716167449951,
0.012779408134520054,
-0.03970348834991455,
0.12989689409732819,
-0.05700010806322098,
0.08568719774484634,
-0.025839755311608315,
-0.04237660765647888,
-0.0031244116835296154,
-0.0819648951292038,
0.028508247807621956,
0.08861616998910904,
-0.03073979914188385,
0.26992908120155334,
0.0110603217035532,
-0.05531863495707512,
-0.1002783253788948,
-0.05904461815953255,
0.10908224433660507,
0.1619715839624405,
0.19445770978927612,
0.038054920732975006,
-0.029624516144394875,
-0.07594960182905197,
-0.1725604385137558,
-0.0066139837726950645,
0.033884357661008835,
-0.016386747360229492,
-0.018131038174033165,
-0.00019216712098568678,
-0.036242853850126266,
-0.020923664793372154,
0.049251988530159,
-0.15166644752025604,
-0.026593312621116638,
-0.03235277533531189,
0.013551196083426476,
-0.035095520317554474,
-0.09046449512243271,
-0.06597679108381271,
-0.06968842446804047,
-0.001007384737022221,
-0.039819277822971344,
-0.05726943910121918,
-0.07407018542289734,
0.04268734157085419,
0.10142776370048523,
-0.05801993981003761,
0.057932253926992416,
-0.05280216038227081,
0.07413946092128754,
0.04410206526517868,
-0.19263723492622375,
0.10251416265964508,
-0.10384245216846466,
-0.0431235134601593,
-0.05192733183503151,
0.1318531334400177,
-0.024671521037817,
0.03258083388209343,
0.03064463846385479,
0.05155542120337486,
-0.035022735595703125,
-0.04683700576424599,
0.07533110678195953,
0.006688425783067942,
0.08595919609069824,
0.1479768604040146,
-0.02304976060986519,
-0.18310779333114624,
-0.03770356997847557,
0.019776450470089912,
0.13244199752807617,
0.22727686166763306,
-0.09973486512899399,
0.05956464260816574,
0.08641742169857025,
0.011143737472593784,
-0.28984060883522034,
-0.030514689162373543,
-0.014930388890206814,
-0.06786762177944183,
0.12122689187526703,
-0.05118178203701973,
0.14786791801452637,
0.12710346281528473,
-0.0990428701043129,
0.15168839693069458,
-0.2666371166706085,
-0.07912390679121017,
0.12900929152965546,
0.08426015824079514,
0.12343820929527283,
-0.1345721334218979,
-0.05578961223363876,
-0.03021705336868763,
-0.04364160820841789,
0.0942864716053009,
-0.09063147008419037,
0.021339233964681625,
-0.0077917869202792645,
-0.07978846877813339,
-0.0025135446339845657,
-0.03976554051041603,
0.14506272971630096,
-0.03341023251414299,
0.12941449880599976,
-0.08815647661685944,
-0.055636681616306305,
0.10641978681087494,
-0.02510310895740986,
0.08124282956123352,
-0.03306174278259277,
0.08510290831327438,
-0.08729737997055054,
0.032789237797260284,
-0.08664518594741821,
0.037206247448921204,
0.02904965542256832,
-0.0006546168006025255,
-0.0774259865283966,
0.020284319296479225,
-0.015781544148921967,
0.03749863803386688,
0.1714378148317337,
0.06194593757390976,
-0.01254437118768692,
0.1209028884768486,
0.04742331802845001,
-0.0807717889547348,
-0.12110801041126251,
-0.1449497491121292,
-0.06376311182975769,
0.07071897387504578,
-0.1723714917898178,
0.051864415407180786,
0.08947820961475372,
0.022969607263803482,
0.08251079171895981,
0.049085553735494614,
-0.016767874360084534,
0.007849594578146935,
0.18983757495880127,
-0.12041892856359482,
-0.09218040108680725,
-0.05508391559123993,
0.04792298004031181,
0.0040941121987998486,
0.026476072147488594,
0.06401689350605011,
-0.0016119760693982244,
-0.02854369580745697,
0.019548611715435982,
0.08415304869413376,
-0.0021306099370121956,
0.09646657854318619,
0.12707480788230896,
-0.007176406215876341,
-0.11561364680528641,
0.21365289390087128,
0.060904089361429214,
-0.06906075775623322,
-0.07978857308626175,
0.06004982069134712,
-0.07291270047426224,
-0.11463116109371185,
0.06513769179582596,
0.08921052515506744,
-0.07161717116832733,
-0.06912650167942047,
-0.05944724380970001,
-0.06156078353524208,
0.040722284466028214,
0.0033622614573687315,
0.09712453931570053,
-0.02214656211435795,
0.07444337755441666,
-0.07321640104055405,
0.014312142506241798,
0.12923923134803772,
0.03098922036588192,
0.03120419569313526,
-0.2438916563987732,
-0.11412815749645233,
0.04429321363568306,
0.11010130494832993,
-0.057233043015003204,
0.008364040404558182,
-0.030409134924411774,
0.03486211970448494,
-0.12901100516319275,
0.09365731477737427,
-0.07095839083194733,
-0.008668214082717896,
-0.007613814435899258,
-0.01708294451236725,
-0.05635865032672882,
0.0068297553807497025,
-0.11019492149353027,
-0.03465009108185768,
0.0198921337723732,
0.05717609450221062,
-0.09856188297271729,
-0.06625355035066605,
0.06501995027065277,
-0.012699401937425137,
0.10515736788511276,
0.044813115149736404,
-0.041278619319200516,
0.02407616376876831,
-0.12347212433815002,
-0.12832961976528168,
0.13823851943016052,
0.043500274419784546,
-0.038782089948654175,
-0.000751709914766252,
0.041823357343673706,
0.030766714364290237,
-0.0758868083357811,
-0.003738056169822812,
0.023807231336832047,
-0.11607074737548828,
-0.09207354485988617,
-0.11413059383630753,
-0.0923347994685173,
-0.020104466006159782,
0.03214595094323158,
0.12458261847496033,
-0.011438416317105293,
0.1618741899728775,
-0.039760369807481766,
0.019312990829348564,
-0.1902395337820053,
0.00822246540337801,
-0.06712886691093445,
-0.12191889435052872,
-0.15043124556541443,
0.020257841795682907,
0.01918010599911213,
-0.08486706018447876,
0.14394326508045197,
0.0998462364077568,
-0.07181564718484879,
0.00584214786067605,
0.18495438992977142,
0.03254101425409317,
0.04777875170111656,
0.2621777653694153,
-0.0025326518807560205,
-0.03957464173436165,
-0.04145905375480652,
0.03382370248436928,
0.0338132418692112,
-0.026012703776359558,
0.03140011057257652,
0.2077554315328598,
-0.05545042082667351,
0.002034688601270318,
0.15199176967144012,
-0.04848643019795418,
-0.10049263387918472,
-0.02508520521223545,
-0.014406753703951836,
0.11127090454101562,
0.026558293029665947,
0.10070822387933731,
0.17038322985172272,
-0.09408210963010788,
-0.01281367614865303,
-0.019283680245280266,
-0.012679210864007473,
-0.0732622742652893,
-0.2458578646183014,
-0.0938401147723198,
-0.1690852791070938,
0.04336492717266083,
-0.06742154806852341,
-0.041557569056749344,
0.2119486927986145,
0.034445181488990784,
-0.07459647953510284,
0.07772204279899597,
-0.08293332904577255,
-0.07390832901000977,
0.11538808792829514,
0.016135919839143753,
-0.09289689362049103,
0.026820825412869453,
-0.023224137723445892,
0.08146164566278458,
-0.015937648713588715,
-0.03362659737467766,
-0.030067449435591698,
-0.04272592067718506,
0.06169411167502403,
-0.06952366977930069,
-0.099983349442482,
-0.02992498129606247,
-0.026587679982185364,
0.004761030897498131,
0.11274732649326324,
-0.005901442375034094,
0.049883052706718445,
0.03561237454414368,
0.17053157091140747,
-0.04362403228878975,
-0.048648759722709656,
-0.04819987341761589,
0.08755578100681305,
-0.09921266883611679,
0.010937793180346489,
0.03781677037477493,
-0.085264191031456,
0.036174360662698746,
0.17040124535560608,
0.21199318766593933,
-0.06729425489902496,
-0.010666552931070328,
-0.027967259287834167,
-0.005833773873746395,
-0.024327317252755165,
0.053415052592754364,
0.07022560387849808,
0.14416977763175964,
-0.10622814297676086,
-0.012901951558887959,
-0.08384152501821518,
-0.0005722328787669539,
-0.07120873779058456,
-0.0013522123917937279,
0.082132987678051,
-0.07515542209148407,
-0.11771388351917267,
0.1275981068611145,
-0.018719859421253204,
0.12092740833759308,
0.08858198672533035,
-0.08711713552474976,
-0.11992879956960678,
-0.03430861979722977,
0.10746527463197708,
0.06044609844684601,
-0.047769177705049515,
-0.11610282212495804,
0.031726252287626266,
-0.06308862566947937,
0.0053240288980305195,
-0.22319486737251282,
-0.08953199535608292,
-0.01092473417520523,
0.012743031606078148,
0.25724369287490845,
0.004156704526394606,
0.096891850233078,
0.06037759780883789,
0.00033465062733739614,
-0.12798568606376648,
0.0412558950483799,
0.003600991563871503,
0.018738482147455215,
0.01912340335547924,
0.03397819772362709,
0.013567214831709862,
-0.08533857762813568,
0.0832674652338028,
-0.024303119629621506,
-0.03128518909215927,
0.0476636104285717,
-0.060483336448669434,
-0.08745377510786057,
0.0870208814740181,
-0.09346145391464233,
0.07200261205434799,
0.019538750872015953,
-0.03342553973197937,
-0.05026359483599663,
-0.08786170184612274,
0.027947604656219482,
0.06408059597015381,
-0.11801222711801529,
0.049338459968566895,
-0.01517682895064354,
-0.0025540145579725504,
-0.07212197780609131,
0.016759350895881653,
-0.0986495316028595,
-0.0557665079832077,
-0.08094363659620285,
-0.04558420926332474,
-0.1085735335946083,
0.07255124300718307,
0.15407414734363556,
0.0044595724903047085,
0.0001401340268785134,
0.09515812993049622,
0.010009600780904293,
0.02658083289861679,
-0.057622846215963364,
-0.042780082672834396
] |
null | null | timm | # Model card for nextvit_small.bd_ssld_6m_in1k_384
A Next-ViT image classification model. Trained by paper authors on an unknown 6M sample dataset and ImageNet-1k using SSLD distillation.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model Stats:**
- Params (M): 31.8
- GMACs: 17.0
- Activations (M): 51.7
- Image size: 384 x 384
- **Pretrain Dataset:** Unknown-6M
- **Dataset:** ImageNet-1k
- **Papers:**
- Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios: https://arxiv.org/abs/2207.05501
- **Original:** https://github.com/bytedance/Next-ViT
## Model Usage
### Image Classification
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model('nextvit_small.bd_ssld_6m_in1k_384', pretrained=True)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
top5_probabilities, top5_class_indices = torch.topk(output.softmax(dim=1) * 100, k=5)
```
### Feature Map Extraction
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model(
'nextvit_small.bd_ssld_6m_in1k_384',
pretrained=True,
features_only=True,
)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
for o in output:
# print shape of each feature map in output
# e.g.:
# torch.Size([1, 96, 96, 96])
# torch.Size([1, 256, 48, 48])
# torch.Size([1, 512, 24, 24])
# torch.Size([1, 1024, 12, 12])
print(o.shape)
```
### Image Embeddings
```python
from urllib.request import urlopen
from PIL import Image
import timm
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
model = timm.create_model(
'nextvit_small.bd_ssld_6m_in1k_384',
pretrained=True,
num_classes=0, # remove classifier nn.Linear
)
model = model.eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
output = model(transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor
# or equivalently (without needing to set num_classes=0)
output = model.forward_features(transforms(img).unsqueeze(0))
# output is unpooled, a (1, 1024, 12, 12) shaped tensor
output = model.forward_head(output, pre_logits=True)
# output is a (1, num_features) shaped tensor
```
## Model Comparison
### By Top-1
|model |top1 |top1_err|top5 |top5_err|param_count|
|---------------------------------|------|--------|------|--------|-----------|
|nextvit_large.bd_ssld_6m_in1k_384|86.542|13.458 |98.142|1.858 |57.87 |
|nextvit_base.bd_ssld_6m_in1k_384 |86.352|13.648 |98.04 |1.96 |44.82 |
|nextvit_small.bd_ssld_6m_in1k_384|85.964|14.036 |97.908|2.092 |31.76 |
|nextvit_large.bd_ssld_6m_in1k |85.48 |14.52 |97.696|2.304 |57.87 |
|nextvit_base.bd_ssld_6m_in1k |85.186|14.814 |97.59 |2.41 |44.82 |
|nextvit_large.bd_in1k_384 |84.924|15.076 |97.294|2.706 |57.87 |
|nextvit_small.bd_ssld_6m_in1k |84.862|15.138 |97.382|2.618 |31.76 |
|nextvit_base.bd_in1k_384 |84.706|15.294 |97.224|2.776 |44.82 |
|nextvit_small.bd_in1k_384 |84.022|15.978 |96.99 |3.01 |31.76 |
|nextvit_large.bd_in1k |83.626|16.374 |96.694|3.306 |57.87 |
|nextvit_base.bd_in1k |83.472|16.528 |96.656|3.344 |44.82 |
|nextvit_small.bd_in1k |82.61 |17.39 |96.226|3.774 |31.76 |
## Citation
```bibtex
@article{li2022next,
title={Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios},
author={Li, Jiashi and Xia, Xin and Li, Wei and Li, Huixia and Wang, Xing and Xiao, Xuefeng and Wang, Rui and Zheng, Min and Pan, Xin},
journal={arXiv preprint arXiv:2207.05501},
year={2022}
}
```
| {"license": "apache-2.0", "library_name": "timm", "tags": ["image-classification", "timm"], "datasets": ["imagenet-1k", "unknown-6m"]} | image-classification | timm/nextvit_small.bd_ssld_6m_in1k_384 | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"dataset:unknown-6m",
"arxiv:2207.05501",
"license:apache-2.0",
"region:us"
] | 2024-02-11T00:33:15+00:00 | [
"2207.05501"
] | [] | TAGS
#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #dataset-unknown-6m #arxiv-2207.05501 #license-apache-2.0 #region-us
| Model card for nextvit\_small.bd\_ssld\_6m\_in1k\_384
=====================================================
A Next-ViT image classification model. Trained by paper authors on an unknown 6M sample dataset and ImageNet-1k using SSLD distillation.
Model Details
-------------
* Model Type: Image classification / feature backbone
* Model Stats:
+ Params (M): 31.8
+ GMACs: 17.0
+ Activations (M): 51.7
+ Image size: 384 x 384
* Pretrain Dataset: Unknown-6M
* Dataset: ImageNet-1k
* Papers:
+ Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios: URL
* Original: URL
Model Usage
-----------
### Image Classification
### Feature Map Extraction
### Image Embeddings
Model Comparison
----------------
### By Top-1
| [
"### Image Classification",
"### Feature Map Extraction",
"### Image Embeddings\n\n\nModel Comparison\n----------------",
"### By Top-1"
] | [
"TAGS\n#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #dataset-unknown-6m #arxiv-2207.05501 #license-apache-2.0 #region-us \n",
"### Image Classification",
"### Feature Map Extraction",
"### Image Embeddings\n\n\nModel Comparison\n----------------",
"### By Top-1"
] | [
56,
5,
6,
12,
5
] | [
"passage: TAGS\n#timm #pytorch #safetensors #image-classification #dataset-imagenet-1k #dataset-unknown-6m #arxiv-2207.05501 #license-apache-2.0 #region-us \n### Image Classification### Feature Map Extraction### Image Embeddings\n\n\nModel Comparison\n----------------### By Top-1"
] | [
-0.09558708965778351,
0.09347394853830338,
-0.00299403490498662,
0.10520054399967194,
0.07291311025619507,
0.012559691444039345,
0.062246110290288925,
0.08803897351026535,
0.03287670761346817,
-0.041789185255765915,
0.11235252022743225,
0.13096554577350616,
0.05655141547322273,
0.08482521027326584,
-0.015286432579159737,
-0.23364990949630737,
0.05155707150697708,
-0.005953880026936531,
0.056405965238809586,
0.11184614896774292,
0.06843625009059906,
-0.13275767862796783,
0.09081137180328369,
-0.030113454908132553,
-0.07863062620162964,
0.02934487909078598,
0.013566946610808372,
-0.07839283347129822,
0.09259331971406937,
-0.06770337373018265,
0.05526963248848915,
0.04437292739748955,
0.08331260085105896,
-0.1080613061785698,
0.0284743569791317,
0.015033003874123096,
-0.07671426236629486,
0.07311322540044785,
0.20175740122795105,
-0.028766576200723648,
0.02208654396235943,
-0.002298174425959587,
-0.06283358484506607,
-0.009130110032856464,
-0.05433163791894913,
-0.1523350179195404,
-0.06192190572619438,
0.17882226407527924,
0.13364389538764954,
0.05033490061759949,
-0.012173596769571304,
0.12204702198505402,
-0.1740248054265976,
0.08050484210252762,
0.1411627233028412,
-0.21766330301761627,
-0.027000045403838158,
0.08109380304813385,
-0.03788871318101883,
0.034920383244752884,
-0.053310327231884,
0.00964007806032896,
0.027365567162632942,
-0.003837174503132701,
0.030367178842425346,
0.008300426416099072,
-0.07884874939918518,
-0.004154783673584461,
-0.12808267772197723,
-0.07409441471099854,
0.24344520270824432,
0.14758169651031494,
0.03846818208694458,
-0.03928784653544426,
-0.08756875991821289,
0.01031971164047718,
-0.02658696472644806,
0.07799483090639114,
0.05681709945201874,
0.01283130794763565,
-0.008337614126503468,
0.06370620429515839,
-0.1462528258562088,
-0.017349500209093094,
-0.1524721086025238,
-0.08909036219120026,
0.028268098831176758,
0.11880890280008316,
-0.08945166319608688,
0.08243481069803238,
-0.04861928150057793,
-0.1329241842031479,
0.06866148114204407,
-0.08242746442556381,
0.07497505843639374,
0.040115535259246826,
0.07445070892572403,
0.02648226171731949,
0.10421928763389587,
0.10993774980306625,
-0.03075791522860527,
0.02116631343960762,
-0.07143659889698029,
0.1353973001241684,
0.027597026899456978,
0.03184673935174942,
-0.168073832988739,
0.03319035470485687,
0.060989778488874435,
0.07650230079889297,
0.10122565180063248,
-0.0006558281602337956,
-0.08514881134033203,
0.009537837468087673,
0.12851865589618683,
0.017137285321950912,
0.08842682093381882,
-0.008033460937440395,
-0.10018431395292282,
-0.06064440682530403,
0.22916187345981598,
-0.03395469859242439,
-0.020387200638651848,
0.008137711323797703,
-0.05704581364989281,
-0.0239932332187891,
0.048498090356588364,
0.027234245091676712,
-0.02136918529868126,
0.05074744671583176,
-0.07190001755952835,
0.04940683767199516,
0.00571137061342597,
-0.022458702325820923,
0.07695623487234116,
-0.05216311663389206,
-0.006435836665332317,
-0.1175767034292221,
-0.13422934710979462,
0.06017563119530678,
0.03853278607130051,
-0.034127794206142426,
-0.015136833302676678,
0.03270628675818443,
-0.08406492322683334,
0.004329846706241369,
-0.010297833010554314,
-0.0014764930820092559,
-0.09163115173578262,
0.06724830716848373,
-0.08598141372203827,
0.0843457281589508,
-0.059828415513038635,
0.026755349710583687,
-0.14912694692611694,
0.036444246768951416,
-0.1783161163330078,
0.022829068824648857,
-0.07335842400789261,
0.10544736683368683,
-0.09136992692947388,
-0.08565674722194672,
-0.09759186208248138,
-0.05024686083197594,
-0.02591802179813385,
0.17204086482524872,
-0.1921125054359436,
-0.005587227176874876,
0.1273060142993927,
-0.11727612465620041,
-0.13039842247962952,
0.07781845331192017,
0.0012696784688159823,
-0.10486451536417007,
0.019158978015184402,
0.22733600437641144,
-0.075113944709301,
-0.04531674459576607,
-0.10057050734758377,
0.06094831973314285,
-0.06990103423595428,
-0.05881810933351517,
0.12343203276395798,
0.015371610410511494,
-0.041035182774066925,
0.018542125821113586,
-0.10435658693313599,
0.07150362432003021,
-0.06857339292764664,
-0.09679179638624191,
-0.04979955032467842,
-0.02762562781572342,
0.08245130628347397,
0.06977207213640213,
0.023059213533997536,
-0.060269907116889954,
-0.05366865545511246,
-0.08795847743749619,
0.08702987432479858,
0.02715953439474106,
-0.04263463243842125,
-0.06387859582901001,
0.1712300181388855,
-0.1513533890247345,
-0.029068473726511,
-0.14413034915924072,
0.014694181270897388,
0.03241952881217003,
0.026729710400104523,
0.030340705066919327,
-0.11321180313825607,
0.04766267165541649,
0.011228871531784534,
-0.02973194047808647,
-0.10931674391031265,
0.01070065051317215,
-0.016022546216845512,
0.0013052156427875161,
-0.1875678151845932,
-0.02290727198123932,
-0.0012173126451671124,
0.1090201884508133,
-0.10200527310371399,
-0.05544091388583183,
0.03133605420589447,
0.1246073767542839,
0.028024811297655106,
0.02060684747993946,
0.01731315813958645,
-0.0551796518266201,
-0.05820794403553009,
-0.04687844589352608,
0.09801702946424484,
-0.037059664726257324,
-0.006597775500267744,
0.05062747746706009,
-0.00975062046200037,
0.09834805876016617,
0.1868835836648941,
-0.2448369264602661,
0.011397312395274639,
-0.012942364439368248,
-0.03337012976408005,
0.0025844601914286613,
-0.03140377253293991,
0.036910638213157654,
-0.05921214073896408,
-0.031548384577035904,
0.05648422986268997,
-0.1066335141658783,
-0.012599027715623379,
0.027406975626945496,
-0.02050682157278061,
-0.10175776481628418,
0.09351391345262527,
0.21877892315387726,
-0.2656879127025604,
0.12511366605758667,
0.3312479555606842,
0.0008102115243673325,
0.019048422574996948,
-0.06815836578607559,
-0.07529519498348236,
0.0068797096610069275,
0.03470737114548683,
-0.03905649110674858,
0.16271041333675385,
-0.0747879147529602,
0.04001716896891594,
0.09844362735748291,
-0.04895138368010521,
0.024417422711849213,
-0.16585946083068848,
-0.02678094245493412,
-0.019540291279554367,
-0.03999538719654083,
-0.10672440379858017,
-0.00937816221266985,
0.01839459501206875,
0.1217767745256424,
-0.04437003657221794,
-0.08880233764648438,
0.04827999323606491,
-0.03549637272953987,
-0.06528531014919281,
0.17564865946769714,
-0.11833243817090988,
-0.30709517002105713,
-0.04774559289216995,
0.06789609789848328,
-0.0931229218840599,
-0.021504797041416168,
0.03719712793827057,
-0.1190883219242096,
-0.04765754193067551,
-0.079276442527771,
-0.16537484526634216,
0.053101032972335815,
-0.006289829965680838,
-0.02808643877506256,
0.03083314560353756,
0.06294508278369904,
-0.07364541292190552,
-0.030794885009527206,
-0.023397982120513916,
-0.00699926633387804,
0.16569748520851135,
-0.027460401877760887,
0.0983651876449585,
0.1267324835062027,
-0.006489625200629234,
0.036727674305438995,
0.008249090984463692,
0.2078518122434616,
-0.04118591174483299,
0.05342375859618187,
0.1777338981628418,
0.014746671542525291,
0.06999237090349197,
0.1705477088689804,
0.037929099053144455,
-0.027453776448965073,
-0.0358283631503582,
0.007734373211860657,
-0.047374092042446136,
-0.15631341934204102,
-0.08335157483816147,
-0.015884486958384514,
0.04839640110731125,
0.11345633119344711,
0.09474849700927734,
0.015104448422789574,
0.0887218713760376,
-0.036342501640319824,
-0.08028140664100647,
0.04685024917125702,
-0.007394097745418549,
-0.01134442538022995,
-0.009161235764622688,
0.10316181182861328,
-0.06482475996017456,
-0.050376005470752716,
0.10848541557788849,
0.04662366211414337,
0.26863518357276917,
0.02965763956308365,
-0.051108382642269135,
0.0865011140704155,
0.25863707065582275,
0.061141349375247955,
0.060096874833106995,
0.0013740723952651024,
-0.004729153122752905,
-0.012291166000068188,
-0.09081355482339859,
0.07971104234457016,
0.014993593096733093,
0.006302401423454285,
-0.007220427971333265,
-0.007515354547649622,
-0.01882636547088623,
0.10163114219903946,
0.10774721205234528,
0.10965513437986374,
-0.2970282733440399,
0.10182203352451324,
0.03816639259457588,
0.05176613852381706,
-0.027951380237936974,
0.06119716167449951,
0.012779408134520054,
-0.03970348834991455,
0.12989689409732819,
-0.05700010806322098,
0.08568719774484634,
-0.025839755311608315,
-0.04237660765647888,
-0.0031244116835296154,
-0.0819648951292038,
0.028508247807621956,
0.08861616998910904,
-0.03073979914188385,
0.26992908120155334,
0.0110603217035532,
-0.05531863495707512,
-0.1002783253788948,
-0.05904461815953255,
0.10908224433660507,
0.1619715839624405,
0.19445770978927612,
0.038054920732975006,
-0.029624516144394875,
-0.07594960182905197,
-0.1725604385137558,
-0.0066139837726950645,
0.033884357661008835,
-0.016386747360229492,
-0.018131038174033165,
-0.00019216712098568678,
-0.036242853850126266,
-0.020923664793372154,
0.049251988530159,
-0.15166644752025604,
-0.026593312621116638,
-0.03235277533531189,
0.013551196083426476,
-0.035095520317554474,
-0.09046449512243271,
-0.06597679108381271,
-0.06968842446804047,
-0.001007384737022221,
-0.039819277822971344,
-0.05726943910121918,
-0.07407018542289734,
0.04268734157085419,
0.10142776370048523,
-0.05801993981003761,
0.057932253926992416,
-0.05280216038227081,
0.07413946092128754,
0.04410206526517868,
-0.19263723492622375,
0.10251416265964508,
-0.10384245216846466,
-0.0431235134601593,
-0.05192733183503151,
0.1318531334400177,
-0.024671521037817,
0.03258083388209343,
0.03064463846385479,
0.05155542120337486,
-0.035022735595703125,
-0.04683700576424599,
0.07533110678195953,
0.006688425783067942,
0.08595919609069824,
0.1479768604040146,
-0.02304976060986519,
-0.18310779333114624,
-0.03770356997847557,
0.019776450470089912,
0.13244199752807617,
0.22727686166763306,
-0.09973486512899399,
0.05956464260816574,
0.08641742169857025,
0.011143737472593784,
-0.28984060883522034,
-0.030514689162373543,
-0.014930388890206814,
-0.06786762177944183,
0.12122689187526703,
-0.05118178203701973,
0.14786791801452637,
0.12710346281528473,
-0.0990428701043129,
0.15168839693069458,
-0.2666371166706085,
-0.07912390679121017,
0.12900929152965546,
0.08426015824079514,
0.12343820929527283,
-0.1345721334218979,
-0.05578961223363876,
-0.03021705336868763,
-0.04364160820841789,
0.0942864716053009,
-0.09063147008419037,
0.021339233964681625,
-0.0077917869202792645,
-0.07978846877813339,
-0.0025135446339845657,
-0.03976554051041603,
0.14506272971630096,
-0.03341023251414299,
0.12941449880599976,
-0.08815647661685944,
-0.055636681616306305,
0.10641978681087494,
-0.02510310895740986,
0.08124282956123352,
-0.03306174278259277,
0.08510290831327438,
-0.08729737997055054,
0.032789237797260284,
-0.08664518594741821,
0.037206247448921204,
0.02904965542256832,
-0.0006546168006025255,
-0.0774259865283966,
0.020284319296479225,
-0.015781544148921967,
0.03749863803386688,
0.1714378148317337,
0.06194593757390976,
-0.01254437118768692,
0.1209028884768486,
0.04742331802845001,
-0.0807717889547348,
-0.12110801041126251,
-0.1449497491121292,
-0.06376311182975769,
0.07071897387504578,
-0.1723714917898178,
0.051864415407180786,
0.08947820961475372,
0.022969607263803482,
0.08251079171895981,
0.049085553735494614,
-0.016767874360084534,
0.007849594578146935,
0.18983757495880127,
-0.12041892856359482,
-0.09218040108680725,
-0.05508391559123993,
0.04792298004031181,
0.0040941121987998486,
0.026476072147488594,
0.06401689350605011,
-0.0016119760693982244,
-0.02854369580745697,
0.019548611715435982,
0.08415304869413376,
-0.0021306099370121956,
0.09646657854318619,
0.12707480788230896,
-0.007176406215876341,
-0.11561364680528641,
0.21365289390087128,
0.060904089361429214,
-0.06906075775623322,
-0.07978857308626175,
0.06004982069134712,
-0.07291270047426224,
-0.11463116109371185,
0.06513769179582596,
0.08921052515506744,
-0.07161717116832733,
-0.06912650167942047,
-0.05944724380970001,
-0.06156078353524208,
0.040722284466028214,
0.0033622614573687315,
0.09712453931570053,
-0.02214656211435795,
0.07444337755441666,
-0.07321640104055405,
0.014312142506241798,
0.12923923134803772,
0.03098922036588192,
0.03120419569313526,
-0.2438916563987732,
-0.11412815749645233,
0.04429321363568306,
0.11010130494832993,
-0.057233043015003204,
0.008364040404558182,
-0.030409134924411774,
0.03486211970448494,
-0.12901100516319275,
0.09365731477737427,
-0.07095839083194733,
-0.008668214082717896,
-0.007613814435899258,
-0.01708294451236725,
-0.05635865032672882,
0.0068297553807497025,
-0.11019492149353027,
-0.03465009108185768,
0.0198921337723732,
0.05717609450221062,
-0.09856188297271729,
-0.06625355035066605,
0.06501995027065277,
-0.012699401937425137,
0.10515736788511276,
0.044813115149736404,
-0.041278619319200516,
0.02407616376876831,
-0.12347212433815002,
-0.12832961976528168,
0.13823851943016052,
0.043500274419784546,
-0.038782089948654175,
-0.000751709914766252,
0.041823357343673706,
0.030766714364290237,
-0.0758868083357811,
-0.003738056169822812,
0.023807231336832047,
-0.11607074737548828,
-0.09207354485988617,
-0.11413059383630753,
-0.0923347994685173,
-0.020104466006159782,
0.03214595094323158,
0.12458261847496033,
-0.011438416317105293,
0.1618741899728775,
-0.039760369807481766,
0.019312990829348564,
-0.1902395337820053,
0.00822246540337801,
-0.06712886691093445,
-0.12191889435052872,
-0.15043124556541443,
0.020257841795682907,
0.01918010599911213,
-0.08486706018447876,
0.14394326508045197,
0.0998462364077568,
-0.07181564718484879,
0.00584214786067605,
0.18495438992977142,
0.03254101425409317,
0.04777875170111656,
0.2621777653694153,
-0.0025326518807560205,
-0.03957464173436165,
-0.04145905375480652,
0.03382370248436928,
0.0338132418692112,
-0.026012703776359558,
0.03140011057257652,
0.2077554315328598,
-0.05545042082667351,
0.002034688601270318,
0.15199176967144012,
-0.04848643019795418,
-0.10049263387918472,
-0.02508520521223545,
-0.014406753703951836,
0.11127090454101562,
0.026558293029665947,
0.10070822387933731,
0.17038322985172272,
-0.09408210963010788,
-0.01281367614865303,
-0.019283680245280266,
-0.012679210864007473,
-0.0732622742652893,
-0.2458578646183014,
-0.0938401147723198,
-0.1690852791070938,
0.04336492717266083,
-0.06742154806852341,
-0.041557569056749344,
0.2119486927986145,
0.034445181488990784,
-0.07459647953510284,
0.07772204279899597,
-0.08293332904577255,
-0.07390832901000977,
0.11538808792829514,
0.016135919839143753,
-0.09289689362049103,
0.026820825412869453,
-0.023224137723445892,
0.08146164566278458,
-0.015937648713588715,
-0.03362659737467766,
-0.030067449435591698,
-0.04272592067718506,
0.06169411167502403,
-0.06952366977930069,
-0.099983349442482,
-0.02992498129606247,
-0.026587679982185364,
0.004761030897498131,
0.11274732649326324,
-0.005901442375034094,
0.049883052706718445,
0.03561237454414368,
0.17053157091140747,
-0.04362403228878975,
-0.048648759722709656,
-0.04819987341761589,
0.08755578100681305,
-0.09921266883611679,
0.010937793180346489,
0.03781677037477493,
-0.085264191031456,
0.036174360662698746,
0.17040124535560608,
0.21199318766593933,
-0.06729425489902496,
-0.010666552931070328,
-0.027967259287834167,
-0.005833773873746395,
-0.024327317252755165,
0.053415052592754364,
0.07022560387849808,
0.14416977763175964,
-0.10622814297676086,
-0.012901951558887959,
-0.08384152501821518,
-0.0005722328787669539,
-0.07120873779058456,
-0.0013522123917937279,
0.082132987678051,
-0.07515542209148407,
-0.11771388351917267,
0.1275981068611145,
-0.018719859421253204,
0.12092740833759308,
0.08858198672533035,
-0.08711713552474976,
-0.11992879956960678,
-0.03430861979722977,
0.10746527463197708,
0.06044609844684601,
-0.047769177705049515,
-0.11610282212495804,
0.031726252287626266,
-0.06308862566947937,
0.0053240288980305195,
-0.22319486737251282,
-0.08953199535608292,
-0.01092473417520523,
0.012743031606078148,
0.25724369287490845,
0.004156704526394606,
0.096891850233078,
0.06037759780883789,
0.00033465062733739614,
-0.12798568606376648,
0.0412558950483799,
0.003600991563871503,
0.018738482147455215,
0.01912340335547924,
0.03397819772362709,
0.013567214831709862,
-0.08533857762813568,
0.0832674652338028,
-0.024303119629621506,
-0.03128518909215927,
0.0476636104285717,
-0.060483336448669434,
-0.08745377510786057,
0.0870208814740181,
-0.09346145391464233,
0.07200261205434799,
0.019538750872015953,
-0.03342553973197937,
-0.05026359483599663,
-0.08786170184612274,
0.027947604656219482,
0.06408059597015381,
-0.11801222711801529,
0.049338459968566895,
-0.01517682895064354,
-0.0025540145579725504,
-0.07212197780609131,
0.016759350895881653,
-0.0986495316028595,
-0.0557665079832077,
-0.08094363659620285,
-0.04558420926332474,
-0.1085735335946083,
0.07255124300718307,
0.15407414734363556,
0.0044595724903047085,
0.0001401340268785134,
0.09515812993049622,
0.010009600780904293,
0.02658083289861679,
-0.057622846215963364,
-0.042780082672834396
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | text-generation | Americo/phi2-finetued-farma-last | [
"transformers",
"safetensors",
"phi",
"text-generation",
"custom_code",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T00:33:27+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #phi #text-generation #custom_code #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #phi #text-generation #custom_code #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
51,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #phi #text-generation #custom_code #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.07441530376672745,
0.13596796989440918,
-0.0039025098085403442,
0.027505790814757347,
0.12266930937767029,
0.005486504640430212,
0.0640522912144661,
0.10635033994913101,
-0.02424517273902893,
0.12324316799640656,
0.022558843716979027,
0.10996841639280319,
0.10686804354190826,
0.18769802153110504,
-0.005247652996331453,
-0.20407868921756744,
0.052618369460105896,
-0.1339786946773529,
-0.005346748046576977,
0.12320936471223831,
0.12734514474868774,
-0.11981219798326492,
0.07206547260284424,
-0.04122542217373848,
-0.006963358726352453,
-0.03489234298467636,
-0.05797455459833145,
-0.048964742571115494,
0.06430605798959732,
0.06026479974389076,
0.0595458559691906,
0.01642736792564392,
0.09416768699884415,
-0.2770709991455078,
0.02226952090859413,
0.08239509910345078,
0.005618265364319086,
0.06627916544675827,
0.07169265300035477,
-0.07693344354629517,
0.08495151996612549,
-0.0664825439453125,
0.14687298238277435,
0.07982858270406723,
-0.09438081085681915,
-0.1880333423614502,
-0.09057903289794922,
0.09343822300434113,
0.18868158757686615,
0.059760916978120804,
-0.030585795640945435,
0.13118816912174225,
-0.06512762606143951,
0.01845625787973404,
0.06895748525857925,
-0.07347869127988815,
-0.05359777435660362,
0.06372594088315964,
0.0695996955037117,
0.09846188873052597,
-0.12773703038692474,
-0.009679428301751614,
0.0320039726793766,
0.013185882940888405,
0.10711356997489929,
0.015842726454138756,
0.12049184739589691,
0.03668152913451195,
-0.14256839454174042,
-0.048429738730192184,
0.08701564371585846,
0.036932192742824554,
-0.0556931346654892,
-0.24876362085342407,
-0.020193742588162422,
-0.038236599415540695,
-0.035524725914001465,
-0.04393884912133217,
0.045244693756103516,
-0.02178187482059002,
0.08087658137083054,
-0.0036660772748291492,
-0.06963636726140976,
-0.05113578215241432,
0.08353596180677414,
0.07143381237983704,
0.028143590316176414,
-0.026850108057260513,
0.01174293551594019,
0.11898057907819748,
0.11549804359674454,
-0.11481842398643494,
-0.051060616970062256,
-0.06272978335618973,
-0.08522246032953262,
-0.04741254821419716,
0.03236919641494751,
0.04775122553110123,
0.05512697622179985,
0.21314972639083862,
-0.0013204539427533746,
0.04992509260773659,
0.03274988383054733,
0.01066634152084589,
0.06731437146663666,
0.08677016198635101,
-0.06419411301612854,
-0.13046035170555115,
-0.02145533822476864,
0.11218346655368805,
0.01231331005692482,
-0.0314481221139431,
-0.038787633180618286,
0.06697112321853638,
0.030200589448213577,
0.12535712122917175,
0.07337819784879684,
0.02016271837055683,
-0.07914318144321442,
-0.06071794033050537,
0.17465178668498993,
-0.16488726437091827,
0.031738489866256714,
0.025622278451919556,
-0.050521157681941986,
-0.018783841282129288,
0.01899137534201145,
0.016399497166275978,
-0.02034466527402401,
0.0874326080083847,
-0.057896632701158524,
-0.03757679834961891,
-0.11592794209718704,
-0.05162535607814789,
0.026356054469943047,
0.005852686706930399,
-0.030844759196043015,
-0.04131776839494705,
-0.11982329934835434,
-0.07797703891992569,
0.07937561720609665,
-0.06747156381607056,
-0.04716470465064049,
-0.03360702842473984,
-0.07821470499038696,
0.012420105747878551,
0.0004091960145160556,
0.11594925820827484,
-0.030400289222598076,
0.05072459205985069,
-0.05188135802745819,
0.07153815776109695,
0.14497826993465424,
0.027334017679095268,
-0.06379645317792892,
0.056507088243961334,
-0.23278117179870605,
0.10387995839118958,
-0.07912862300872803,
0.04115021973848343,
-0.16289231181144714,
-0.01469900831580162,
0.03982052579522133,
0.02627355046570301,
-0.006934128236025572,
0.1390630006790161,
-0.19293013215065002,
-0.03536631911993027,
0.18081475794315338,
-0.11522960662841797,
-0.08808764070272446,
0.052698906511068344,
-0.054467298090457916,
0.12280778586864471,
0.050916753709316254,
-0.02316596917808056,
0.030826477333903313,
-0.1417923867702484,
-0.01687287911772728,
-0.06468956172466278,
-0.025315633043646812,
0.15359161794185638,
0.05711430311203003,
-0.051229238510131836,
0.052433162927627563,
0.020726939663290977,
-0.021120568737387657,
-0.04788779839873314,
-0.03371148556470871,
-0.09498532861471176,
0.009590674191713333,
-0.0753822848200798,
0.01856466382741928,
-0.029109936207532883,
-0.09291869401931763,
-0.035687901079654694,
-0.15461255609989166,
0.005384957883507013,
0.09633282572031021,
-0.0055311573669314384,
-0.025023676455020905,
-0.10565053671598434,
-0.004781804513186216,
0.016855718567967415,
-0.00016373902326449752,
-0.15187151730060577,
-0.05655598267912865,
0.019132478162646294,
-0.16505438089370728,
0.02767706662416458,
-0.047599732875823975,
0.045580726116895676,
0.04182368889451027,
-0.03936924785375595,
-0.03521854057908058,
0.018329832702875137,
0.020268244668841362,
-0.01465248316526413,
-0.2745935916900635,
-0.018261034041643143,
-0.04086336866021156,
0.17035499215126038,
-0.2475264072418213,
0.04439546912908554,
0.059322256594896317,
0.1307375431060791,
0.01173730194568634,
-0.03705551475286484,
0.03161298856139183,
-0.06255152821540833,
-0.033266592770814896,
-0.0667189359664917,
-0.009362515062093735,
-0.03631554916501045,
-0.03938153013586998,
0.03835300728678703,
-0.17000539600849152,
-0.03406575322151184,
0.11603987962007523,
0.04540814831852913,
-0.15477602183818817,
-0.05056281015276909,
-0.04004296287894249,
-0.05738358572125435,
-0.07204438000917435,
-0.05216284841299057,
0.09743187576532364,
0.05571887642145157,
0.05545826256275177,
-0.05951985344290733,
-0.061445724219083786,
0.009554018266499043,
-0.02068808674812317,
-0.01867086999118328,
0.08103828877210617,
0.07077015191316605,
-0.11522045731544495,
0.09927672892808914,
0.08799781650304794,
0.08139653503894806,
0.10005104541778564,
0.0010666352463886142,
-0.09291157126426697,
-0.02339044213294983,
0.027750657871365547,
0.014336124062538147,
0.14687193930149078,
-0.04000900313258171,
0.0429966077208519,
0.04120675474405289,
-0.01584675721824169,
0.008143718354403973,
-0.09446796029806137,
0.02997143194079399,
0.02818182110786438,
-0.010246568359434605,
0.037614114582538605,
-0.056816551834344864,
0.019303709268569946,
0.10318583995103836,
0.03345242142677307,
0.04412994161248207,
0.009559271857142448,
-0.04857930168509483,
-0.11974377185106277,
0.1767151653766632,
-0.11110951006412506,
-0.23173309862613678,
-0.12149907648563385,
-0.01399032212793827,
0.02910485304892063,
-0.011633564718067646,
0.02006695233285427,
-0.06405475735664368,
-0.1171390563249588,
-0.09921693801879883,
0.045627593994140625,
0.07059439271688461,
-0.08641253411769867,
-0.06378761678934097,
0.06134819984436035,
0.04600827768445015,
-0.13516096770763397,
0.02277415804564953,
0.03902184218168259,
-0.08909334987401962,
0.007867258042097092,
0.07907920330762863,
0.07120607048273087,
0.17945720255374908,
0.012182043865323067,
-0.024257373064756393,
0.019671371206641197,
0.20478034019470215,
-0.13766378164291382,
0.10145840793848038,
0.14393620193004608,
-0.06286554783582687,
0.08066798746585846,
0.20545852184295654,
0.036268092691898346,
-0.1057758554816246,
0.044006094336509705,
0.03648979216814041,
-0.02651887945830822,
-0.24340394139289856,
-0.08019697666168213,
0.004161624237895012,
-0.06197261065244675,
0.08161719888448715,
0.08306818455457687,
0.09198566526174545,
0.02785661816596985,
-0.1081320270895958,
-0.06691340357065201,
0.05036139488220215,
0.11249116063117981,
-0.008557078428566456,
-0.007815919816493988,
0.09523359686136246,
-0.02225065603852272,
0.029176659882068634,
0.09147068858146667,
0.01374965999275446,
0.18282483518123627,
0.045852772891521454,
0.14848409593105316,
0.09157159924507141,
0.059395745396614075,
0.01233623269945383,
0.01314469799399376,
0.019094863906502724,
0.026712998747825623,
-0.015145753510296345,
-0.08685000985860825,
-0.012303872965276241,
0.1268911212682724,
0.010885220021009445,
0.04597875103354454,
0.0076150596141815186,
-0.04230163246393204,
0.08450151234865189,
0.17545753717422485,
0.01328173466026783,
-0.21406996250152588,
-0.06688741594552994,
0.06981010735034943,
-0.08051439374685287,
-0.10911136865615845,
-0.024429909884929657,
0.03406251221895218,
-0.18049609661102295,
0.02387341856956482,
-0.025180401280522346,
0.10069414228200912,
-0.12370731681585312,
-0.018827902153134346,
0.052628833800554276,
0.07052139192819595,
-0.018700284883379936,
0.06386490911245346,
-0.17778280377388,
0.13549263775348663,
0.013200430199503899,
0.07557245343923569,
-0.09068016707897186,
0.08482389152050018,
0.0111467270180583,
-0.002043683547526598,
0.1468254029750824,
-0.0010637122904881835,
-0.05408002436161041,
-0.11050406098365784,
-0.0906725600361824,
-0.011339336633682251,
0.11465787142515182,
-0.12593887746334076,
0.10165182501077652,
-0.016582757234573364,
-0.044178079813718796,
-0.0030248011462390423,
-0.12813955545425415,
-0.14044401049613953,
-0.17314541339874268,
0.04187968373298645,
-0.13014033436775208,
0.0451013408601284,
-0.10672678053379059,
-0.05035872012376785,
-0.05017208307981491,
0.19719818234443665,
-0.21763156354427338,
-0.07621806859970093,
-0.15351133048534393,
-0.06420157849788666,
0.11623851954936981,
-0.04613782465457916,
0.08647869527339935,
0.012962628155946732,
0.18781377375125885,
0.014061033725738525,
-0.015962716192007065,
0.10993410646915436,
-0.10395599156618118,
-0.21440888941287994,
-0.10220180451869965,
0.13403694331645966,
0.13545545935630798,
0.03708728775382042,
0.00035940390080213547,
0.03232092037796974,
-0.007850716821849346,
-0.11358384788036346,
0.023570599034428596,
0.18197759985923767,
0.11685380339622498,
0.037179335951805115,
-0.034665536135435104,
-0.13531899452209473,
-0.0839521661400795,
-0.042324043810367584,
0.008525622077286243,
0.18976294994354248,
-0.06857912987470627,
0.1652597337961197,
0.15934355556964874,
-0.055173277854919434,
-0.21036414802074432,
0.0313970185816288,
0.033629804849624634,
0.0021239151246845722,
0.05604655668139458,
-0.20132838189601898,
0.0957157164812088,
0.00788893923163414,
-0.057729288935661316,
0.12271249294281006,
-0.18383583426475525,
-0.14666838943958282,
0.0679788589477539,
0.07568002492189407,
-0.18666845560073853,
-0.12836617231369019,
-0.09530680626630783,
-0.04426150023937225,
-0.1240062341094017,
0.0767902210354805,
-0.019116053357720375,
0.009703016839921474,
0.03049294650554657,
0.017553992569446564,
0.010632803663611412,
-0.04766656085848808,
0.18440434336662292,
-0.005318623501807451,
0.050052255392074585,
-0.07833196222782135,
-0.05977580323815346,
0.04439995810389519,
-0.06766178458929062,
0.07768969982862473,
-0.011583259329199791,
0.012072126381099224,
-0.10826653987169266,
-0.05835650488734245,
-0.03404201939702034,
0.024099772796034813,
-0.08059826493263245,
-0.09612218290567398,
-0.037487708032131195,
0.09951330721378326,
0.09140417724847794,
-0.03928857669234276,
-0.06511175632476807,
-0.08731205761432648,
0.032564677298069,
0.21537625789642334,
0.17581914365291595,
0.05872897058725357,
-0.06627403944730759,
-0.004332480486482382,
-0.013938636519014835,
0.0518467053771019,
-0.20769350230693817,
0.054770588874816895,
0.037577200680971146,
0.03502080589532852,
0.11540760844945908,
-0.02692747861146927,
-0.15991008281707764,
-0.04947725683450699,
0.054892536252737045,
-0.07749488949775696,
-0.16381342709064484,
0.014566776342689991,
0.0698530450463295,
-0.15249542891979218,
-0.023638471961021423,
0.04465564340353012,
-0.019799569621682167,
-0.033337272703647614,
0.003100043162703514,
0.08220522850751877,
0.016223285347223282,
0.09557998180389404,
0.05498101934790611,
0.09563100337982178,
-0.10772447288036346,
0.06952618062496185,
0.07929857820272446,
-0.10225345939397812,
0.03691693767905235,
0.06498466432094574,
-0.07187005877494812,
-0.035860974341630936,
0.04298849776387215,
0.09064827114343643,
0.03834117203950882,
-0.05791795626282692,
0.006768029183149338,
-0.1019822508096695,
0.058791015297174454,
0.11939579248428345,
0.043310075998306274,
0.008954020217061043,
0.03660706803202629,
0.039979103952646255,
-0.09563424438238144,
0.12395429611206055,
0.04702746868133545,
0.03306521847844124,
-0.05115185305476189,
-0.030670443549752235,
0.033765602856874466,
-0.03013032302260399,
-0.016100779175758362,
-0.04014170542359352,
-0.06690575927495956,
-0.012527769431471825,
-0.17551913857460022,
0.004580955021083355,
-0.05460330843925476,
0.004814730025827885,
0.01808975264430046,
-0.030708830803632736,
0.006335208658128977,
0.01802607998251915,
-0.07054036855697632,
-0.05601222440600395,
-0.007826367393136024,
0.10339196026325226,
-0.17446856200695038,
0.014777671545743942,
0.07612703740596771,
-0.12507562339305878,
0.0856013149023056,
0.019583139568567276,
0.0037027799990028143,
0.030126722529530525,
-0.12974882125854492,
0.04562569037079811,
-0.008532330393791199,
0.0110886599868536,
0.04916682839393616,
-0.2144635170698166,
-0.00006298656080616638,
-0.048669952899217606,
-0.06047982722520828,
-0.008075869642198086,
-0.022350680083036423,
-0.11814062297344208,
0.10634202510118484,
0.011746841482818127,
-0.07358573377132416,
-0.025499174371361732,
0.039712198078632355,
0.09615115076303482,
-0.03705960139632225,
0.15897074341773987,
-0.017435546964406967,
0.06202258542180061,
-0.18289825320243835,
-0.022887926548719406,
-0.01893971487879753,
0.02133350446820259,
-0.041365109384059906,
-0.009923189878463745,
0.053397808223962784,
-0.0207329411059618,
0.20566853880882263,
-0.017383437603712082,
0.03804474696516991,
0.06314582377672195,
-0.013027135282754898,
-0.014618457295000553,
0.10731750726699829,
0.048464275896549225,
0.011181623674929142,
0.02981831505894661,
0.010703807696700096,
-0.03417062386870384,
-0.005388245452195406,
-0.1523161679506302,
0.077239029109478,
0.16865576803684235,
0.08118049800395966,
-0.008775852620601654,
0.054247766733169556,
-0.11114349961280823,
-0.11427582800388336,
0.0913289338350296,
-0.056236591190099716,
-0.013130106031894684,
-0.05957726389169693,
0.14178913831710815,
0.15433260798454285,
-0.1893889456987381,
0.06022936478257179,
-0.06838760524988174,
-0.04934924468398094,
-0.10593041032552719,
-0.172664612531662,
-0.05883026123046875,
-0.05516333505511284,
-0.0200477484613657,
-0.055225640535354614,
0.065329410135746,
0.09025082737207413,
0.016052771359682083,
0.013859162107110023,
0.08703679591417313,
-0.017933277413249016,
0.0062139625661075115,
0.030186165124177933,
0.06423898041248322,
0.011570695787668228,
-0.04630725830793381,
0.008485673926770687,
-0.0025986286345869303,
0.032309141010046005,
0.051715679466724396,
0.03794151917099953,
-0.025615144520998,
0.009215989150106907,
-0.028480391949415207,
-0.11046841740608215,
0.039721209555864334,
-0.025451408699154854,
-0.0637175589799881,
0.14837713539600372,
0.02840440161526203,
-0.0067321667447686195,
-0.023941997438669205,
0.2540489137172699,
-0.07580790668725967,
-0.08472823351621628,
-0.1372121125459671,
0.14538848400115967,
-0.03086796961724758,
0.06126725301146507,
0.039360348135232925,
-0.11396372318267822,
0.03298129141330719,
0.1398884356021881,
0.14529621601104736,
-0.051987502723932266,
0.017118316143751144,
0.014656228013336658,
0.0029644023161381483,
-0.038789160549640656,
0.05346855893731117,
0.06594305485486984,
0.1253807246685028,
-0.05399900674819946,
0.08479224145412445,
-0.004516707267612219,
-0.10068650543689728,
-0.03351442143321037,
0.1215558722615242,
-0.0051100910641252995,
0.021343640983104706,
-0.07243939489126205,
0.12681175768375397,
-0.04128829762339592,
-0.26241305470466614,
0.06438590586185455,
-0.06042512133717537,
-0.14796359837055206,
-0.0250939279794693,
0.042521025985479355,
-0.005583211313933134,
0.02851193957030773,
0.06835387647151947,
-0.06482896208763123,
0.1890970915555954,
0.037300046533346176,
-0.05160627141594887,
-0.06661834567785263,
0.07295969873666763,
-0.10394251346588135,
0.2989484369754791,
0.006831952836364508,
0.056051596999168396,
0.10134656727313995,
-0.031050942838191986,
-0.14268989861011505,
0.031161298975348473,
0.08590974658727646,
-0.06741449981927872,
0.055566806346178055,
0.2119295448064804,
-0.00888585951179266,
0.10927559435367584,
0.07252391427755356,
-0.08921248465776443,
0.04874938353896141,
-0.10592100024223328,
-0.09221301972866058,
-0.08717742562294006,
0.09235067665576935,
-0.0555795282125473,
0.14914315938949585,
0.12058565765619278,
-0.04728509485721588,
0.021935351192951202,
-0.021421335637569427,
0.050473760813474655,
0.004591043572872877,
0.12314941734075546,
0.022128529846668243,
-0.19706779718399048,
0.026956038549542427,
-0.0006028058123774827,
0.10154236108064651,
-0.21685825288295746,
-0.09420528262853622,
0.04897189885377884,
0.00334720266982913,
-0.06139703094959259,
0.1250954121351242,
0.05242267996072769,
0.041330695152282715,
-0.046910692006349564,
-0.030460618436336517,
-0.00651969201862812,
0.1657109558582306,
-0.10882015526294708,
-0.004513995256274939
] |
null | null | diffusers |
# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test
These are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following.
| {"license": "creativeml-openrail-m", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "textual_inversion"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "inference": true} | text-to-image | Stelath/textual_inversion_comic_strip_test | [
"diffusers",
"tensorboard",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"textual_inversion",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | 2024-02-11T00:34:33+00:00 | [] | [] | TAGS
#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us
|
# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test
These are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following.
!img_0
!img_1
!img_2
!img_3
| [
"# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test\nThese are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
"TAGS\n#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us \n",
"# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test\nThese are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
108,
86
] | [
"passage: TAGS\n#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us \n# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test\nThese are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
-0.12564118206501007,
-0.10199816524982452,
-0.0036781728267669678,
0.0028595104813575745,
0.06154044345021248,
-0.0014107469469308853,
0.2095247060060501,
0.1278240978717804,
0.09875844419002533,
0.1198037788271904,
0.07856301218271255,
0.06516625732183456,
0.027537906542420387,
0.050159238278865814,
-0.07338200509548187,
-0.1671273410320282,
0.008385444059967995,
0.0038244593888521194,
-0.06113622710108757,
0.10609543323516846,
0.0929517149925232,
-0.06360045075416565,
0.07612685114145279,
0.023109959438443184,
-0.09398896992206573,
0.005586731713265181,
0.047696612775325775,
-0.08513443917036057,
0.09936098754405975,
0.015353298746049404,
0.06262470781803131,
0.1660502701997757,
0.01352710835635662,
-0.13697747886180878,
0.028618812561035156,
0.05832767114043236,
0.01671077497303486,
0.06055067107081413,
-0.008772443979978561,
-0.03503047302365303,
0.04309314489364624,
-0.044863469898700714,
-0.025332974269986153,
0.018390031531453133,
-0.0503503642976284,
-0.034838926047086716,
-0.10440833121538162,
-0.02097100205719471,
0.037916261702775955,
0.024298906326293945,
-0.00845368206501007,
0.12681466341018677,
-0.05924045294523239,
0.03455376625061035,
0.27143552899360657,
-0.27704790234565735,
-0.01093425415456295,
0.11925510317087173,
0.1510966718196869,
0.10017213225364685,
-0.02845107577741146,
0.11586924642324448,
0.07071718573570251,
-0.01138747576624155,
0.04414910078048706,
-0.053535327315330505,
0.1481436789035797,
-0.002269480610266328,
-0.12771297991275787,
0.06922383606433868,
0.13563664257526398,
-0.02117842808365822,
-0.08695950359106064,
-0.19250871241092682,
-0.0033962647430598736,
0.12224601209163666,
-0.030271083116531372,
-0.06323959678411484,
-0.008103403262794018,
-0.02394687943160534,
0.022984573617577553,
-0.05589151382446289,
-0.09875389188528061,
-0.08424098789691925,
-0.06994681060314178,
0.1273784637451172,
-0.017225464805960655,
-0.010252708569169044,
0.052999380975961685,
0.10626733303070068,
-0.14387072622776031,
-0.1424466073513031,
-0.012029961682856083,
-0.06175645813345909,
-0.009193508885800838,
-0.023951368406414986,
-0.04675566405057907,
-0.3035958707332611,
0.06745810061693192,
0.034383442252874374,
0.02824721671640873,
0.013044335879385471,
-0.048041656613349915,
0.11006122827529907,
-0.02448245882987976,
0.07940178364515305,
-0.05639581009745598,
0.007265028543770313,
0.0053871748968958855,
0.1126425564289093,
0.06450452655553818,
-0.01915786787867546,
-0.05156582593917847,
-0.0457562692463398,
-0.00146747927647084,
0.030937515199184418,
0.0016001502517610788,
0.018126115202903748,
-0.0812070444226265,
-0.006441445555537939,
0.10536347329616547,
-0.07507466524839401,
0.0374961718916893,
-0.02784017287194729,
0.016072284430265427,
0.12483829259872437,
0.12796998023986816,
0.021100511774420738,
-0.010383404791355133,
0.06922528892755508,
-0.03913325443863869,
0.06971525400876999,
-0.003572650020942092,
-0.11630163341760635,
0.02123606763780117,
-0.12912653386592865,
-0.06493370234966278,
-0.10557131469249725,
-0.09955236315727234,
0.013424856588244438,
0.026656925678253174,
-0.03931797295808792,
0.09169577807188034,
0.030131086707115173,
-0.027414673939347267,
0.03685504570603371,
0.01902691088616848,
-0.12009673565626144,
-0.03586846590042114,
0.049056630581617355,
0.05459943413734436,
0.09115369617938995,
0.033040281385183334,
-0.0033078042324632406,
-0.0643351674079895,
0.04207197204232216,
-0.3191680610179901,
0.10205597430467606,
-0.10886033624410629,
-0.021356696262955666,
-0.08630593866109848,
-0.03575318679213524,
-0.08092129975557327,
0.06962014734745026,
0.06255261600017548,
0.23541267216205597,
-0.26189109683036804,
-0.07578722387552261,
0.14119689166545868,
-0.16368550062179565,
-0.12524546682834625,
0.11043038219213486,
0.01847721077501774,
0.045055143535137177,
0.03427184745669365,
0.11121433973312378,
0.027894694358110428,
-0.26143544912338257,
0.034491244703531265,
-0.018740441650152206,
-0.05201306566596031,
0.01506356056779623,
0.05630865320563316,
-0.05444278195500374,
0.05229530110955238,
0.022690944373607635,
-0.13851727545261383,
0.054894447326660156,
-0.05515754967927933,
0.02508782595396042,
-0.0774858221411705,
-0.008952352218329906,
0.11916499584913254,
0.03854968398809433,
0.02939365617930889,
-0.05109553039073944,
-0.10047949105501175,
0.10386358946561813,
-0.00526534765958786,
-0.08400952070951462,
0.041442256420850754,
-0.05092431232333183,
0.17989544570446014,
-0.14778146147727966,
-0.017003536224365234,
-0.13976486027240753,
0.0050626457668840885,
0.03469390794634819,
0.15484029054641724,
0.030724354088306427,
0.05491974949836731,
0.13449953496456146,
0.006151129957288504,
-0.01913456805050373,
0.010013340041041374,
0.08400856703519821,
0.015127149410545826,
-0.07986223697662354,
-0.14858579635620117,
0.04383077844977379,
-0.08201710134744644,
0.07406065613031387,
-0.2182171493768692,
0.05465695261955261,
-0.003704144386574626,
0.14629466831684113,
0.07483798265457153,
-0.027882134541869164,
0.011930974200367928,
-0.02104494720697403,
-0.09064120799303055,
-0.03566204011440277,
0.002653865609318018,
-0.015464500524103642,
-0.05915283039212227,
0.21907003223896027,
-0.13768720626831055,
0.12202315777540207,
0.11257664114236832,
-0.012469414621591568,
-0.07696095108985901,
-0.14780081808567047,
-0.0034071330446749926,
0.023209918290376663,
-0.05526581034064293,
-0.03477306291460991,
0.0016820025630295277,
0.0380355566740036,
0.11480354517698288,
-0.061497271060943604,
0.0017813702579587698,
0.03410083055496216,
-0.07358913123607635,
-0.03090011142194271,
0.056439220905303955,
0.019106058403849602,
0.006052188575267792,
0.008906365372240543,
0.15139713883399963,
-0.04649997875094414,
0.02607208490371704,
-0.05547133460640907,
-0.10854717344045639,
-0.028815163299441338,
0.07751672714948654,
0.07755689322948456,
0.12808313965797424,
-0.02190699428319931,
-0.025096677243709564,
0.018756994977593422,
-0.02908826805651188,
0.015825901180505753,
-0.09872091561555862,
0.0006921314052306116,
0.08996112644672394,
-0.04925857484340668,
0.07998424768447876,
0.05599195882678032,
-0.01824713684618473,
0.10170295834541321,
-0.0829169750213623,
-0.03096717968583107,
-0.011887685395777225,
-0.012386859394609928,
-0.1308228224515915,
0.1516578495502472,
-0.05655466392636299,
-0.12972046434879303,
-0.1163933202624321,
-0.0004266265605110675,
0.04054959490895271,
0.010500254109501839,
0.036113232374191284,
-0.03631681203842163,
-0.06156960502266884,
-0.13281436264514923,
0.05400913953781128,
0.11720576137304306,
0.04345168173313141,
0.0015410681953653693,
-0.05431422218680382,
0.03185679391026497,
-0.07387755811214447,
-0.01592741161584854,
-0.020703088492155075,
0.08589937537908554,
0.0671115592122078,
0.02132374607026577,
0.09132371097803116,
0.12049812823534012,
-0.01858879253268242,
0.01751434989273548,
0.012040961533784866,
0.05586742237210274,
-0.049822982400655746,
0.11251500993967056,
0.18081925809383392,
-0.011173030361533165,
0.04690219461917877,
0.05511663481593132,
0.017376922070980072,
0.00854095071554184,
0.023922080174088478,
-0.007006458006799221,
-0.07334335148334503,
-0.1406083106994629,
-0.06096283718943596,
-0.06148253381252289,
-0.03784242272377014,
-0.019317353144288063,
0.014367402531206608,
0.10079478472471237,
0.09670202434062958,
0.06478424370288849,
-0.04946862906217575,
0.05179879814386368,
0.05718265101313591,
0.09940861910581589,
-0.030627455562353134,
0.08834604918956757,
-0.049290161579847336,
-0.06144953891634941,
0.08256402611732483,
-0.08860539644956589,
0.12014041095972061,
-0.05588580295443535,
0.07379473745822906,
0.056707289069890976,
0.043125249445438385,
0.07116168737411499,
0.09772602468729019,
-0.04203323274850845,
-0.07510940730571747,
0.025145750492811203,
-0.11780271679162979,
0.05097299814224243,
0.042937230318784714,
0.03699171543121338,
-0.04474220052361488,
-0.05728749558329582,
0.016259968280792236,
0.059659142047166824,
0.018616531044244766,
0.13663680851459503,
-0.26744258403778076,
-0.022757122293114662,
-0.007967695593833923,
0.024229880422353745,
-0.003116236301138997,
-0.028098253533244133,
0.14713911712169647,
-0.0299860630184412,
0.052058856934309006,
-0.12350057065486908,
0.05616217479109764,
0.042276106774806976,
-0.02080201357603073,
-0.024868695065379143,
0.13877274096012115,
-0.05313099920749664,
-0.020544499158859253,
-0.1944301724433899,
0.06718555837869644,
0.013774564489722252,
-0.006311691831797361,
-0.04622634872794151,
0.020305532962083817,
0.05555723235011101,
0.09608159959316254,
0.09877175092697144,
-0.022999383509159088,
0.043010611087083817,
-0.028236916288733482,
-0.12060347199440002,
-0.03332960978150368,
0.07574193924665451,
-0.01208128035068512,
0.0662904754281044,
0.01535098161548376,
-0.02576112188398838,
0.04852921888232231,
0.0035561511758714914,
-0.2368645966053009,
-0.10346512496471405,
0.056617897003889084,
-0.013691321946680546,
-0.10472510755062103,
-0.10390828549861908,
-0.10576220601797104,
-0.17824289202690125,
0.25023695826530457,
-0.039453618228435516,
-0.055667776614427567,
-0.12753939628601074,
-0.002764742588624358,
0.11551429331302643,
-0.024943286553025246,
0.0063726031221449375,
-0.019085343927145004,
0.09155609458684921,
-0.06408867239952087,
-0.12777240574359894,
0.08997886627912521,
-0.07171255350112915,
-0.08853618800640106,
-0.09021735191345215,
0.14073120057582855,
0.00845443457365036,
-0.008068809285759926,
0.034704823046922684,
0.007986281998455524,
0.05033088102936745,
-0.06655493378639221,
0.034083571285009384,
0.0324840173125267,
-0.018416740000247955,
0.06957428902387619,
-0.03670482337474823,
-0.02262977883219719,
-0.02050529420375824,
0.025511963292956352,
0.1171770691871643,
0.13075807690620422,
-0.08597050607204437,
0.07481484115123749,
0.05438745766878128,
-0.03398318588733673,
-0.1943272352218628,
0.05420960485935211,
-0.01869501918554306,
0.0581156425178051,
0.09857585281133652,
-0.02691272459924221,
0.1194821149110794,
0.05946630239486694,
0.004911620635539293,
0.2179946005344391,
-0.32178670167922974,
-0.13685278594493866,
0.0556764155626297,
0.0794372484087944,
0.023820964619517326,
-0.16505677998065948,
-0.12363046407699585,
0.05266806110739708,
-0.09807851910591125,
0.03536040708422661,
-0.05888998508453369,
0.043828338384628296,
-0.027966806665062904,
-0.07778690755367279,
0.02887800708413124,
-0.07469417154788971,
0.14631758630275726,
-0.08261852711439133,
0.0012123705819249153,
-0.08797495067119598,
0.052363160997629166,
0.07056284695863724,
-0.06908222287893295,
0.07826947420835495,
-0.21419855952262878,
0.033476561307907104,
-0.14812664687633514,
-0.01605599746108055,
-0.005798890721052885,
0.08032375574111938,
-0.005957591813057661,
-0.0018392031779512763,
-0.07827619463205338,
0.008267153054475784,
-0.03962291032075882,
-0.029664423316717148,
0.07446935772895813,
-0.05298617482185364,
0.08726436644792557,
0.18495021760463715,
0.10901948064565659,
-0.03031250834465027,
-0.07145699858665466,
-0.0037858576979488134,
-0.008113136515021324,
0.022220635786652565,
-0.11303441971540451,
0.0030105707701295614,
0.1335529237985611,
0.07328624278306961,
0.1211571916937828,
0.03556646406650543,
-0.09606431424617767,
0.0412420928478241,
0.11668356508016586,
-0.07540716975927353,
-0.02004457637667656,
-0.01660817489027977,
-0.014417415484786034,
-0.004738637711852789,
0.06091219559311867,
0.137492835521698,
-0.03924129530787468,
0.027888773009181023,
0.011546147055923939,
0.032756365835666656,
-0.053881190717220306,
0.1512591689825058,
0.05131500959396362,
0.026061831042170525,
-0.03415243700146675,
0.06676862388849258,
-0.06595607846975327,
-0.11316640675067902,
-0.02750347927212715,
0.07137840241193771,
-0.07602855563163757,
-0.047277484089136124,
0.08396997302770615,
0.1118602529168129,
-0.09081995487213135,
0.012592380866408348,
-0.11404763162136078,
-0.17107272148132324,
-0.016214922070503235,
0.1441413015127182,
0.0566832572221756,
-0.016225231811404228,
0.0025835006963461637,
-0.018933335319161415,
-0.05474196374416351,
0.08353567868471146,
0.13522027432918549,
0.10109595954418182,
-0.15662214159965515,
-0.03262864798307419,
-0.036055609583854675,
-0.020131733268499374,
-0.07948367297649384,
0.0013535041362047195,
-0.05591713637113571,
-0.04110788181424141,
-0.14951974153518677,
0.04479469358921051,
-0.12420831620693207,
-0.08224056661128998,
0.009794473648071289,
-0.07653512060642242,
0.012589615769684315,
-0.006893262732774019,
-0.030590586364269257,
-0.016958605498075485,
-0.030429275706410408,
0.018263651058077812,
-0.10153622925281525,
-0.027492975816130638,
0.003791968571022153,
-0.12001293897628784,
0.08003025501966476,
0.03333889693021774,
-0.05616924166679382,
-0.006876274012029171,
-0.21655696630477905,
-0.0026739947497844696,
0.11535897850990295,
-0.00922895222902298,
0.0017450039740651846,
-0.07074292004108429,
0.06295216828584671,
0.033232614398002625,
0.0106961689889431,
-0.002424232428893447,
0.01844359189271927,
-0.04487815871834755,
0.02595607005059719,
-0.1121954694390297,
0.018652252852916718,
-0.05374547094106674,
0.07449450343847275,
0.13873222470283508,
0.09165582805871964,
0.12244261056184769,
-0.13101382553577423,
0.06500118970870972,
-0.16963614523410797,
0.007625898811966181,
0.020062658935785294,
-0.019515840336680412,
0.10683517158031464,
0.017511136829853058,
0.017956744879484177,
-0.028101027011871338,
0.1283349245786667,
-0.034422360360622406,
-0.09989236295223236,
0.020488059148192406,
-0.03421805799007416,
0.1122482568025589,
0.03807383030653,
0.17758770287036896,
0.019658468663692474,
0.024478033185005188,
-0.1414409726858139,
0.04250868037343025,
0.10007727891206741,
-0.16674914956092834,
0.14968514442443848,
0.15762954950332642,
-0.1055903285741806,
0.1370546966791153,
0.04173482954502106,
-0.03905792906880379,
0.005963945761322975,
0.06825271248817444,
-0.09511949867010117,
0.11990801244974136,
0.008856697008013725,
0.09903861582279205,
0.15268146991729736,
-0.061139073222875595,
0.0006640661740675569,
0.01896868646144867,
-0.05988331139087677,
-0.0604131855070591,
-0.130680114030838,
-0.040348391979932785,
-0.1904054880142212,
-0.0022215330973267555,
-0.05429988354444504,
0.030782030895352364,
-0.00048324899398721755,
0.062182094901800156,
0.040324222296476364,
0.12767671048641205,
0.04242638498544693,
-0.06848081946372986,
0.13369503617286682,
-0.015769708901643753,
-0.05940743163228035,
0.09080296009778976,
-0.0026929122395813465,
0.04991995170712471,
0.03465227037668228,
0.010947166942059994,
0.06309013813734055,
0.04775916785001755,
0.03305749595165253,
-0.029191607609391212,
-0.0974745899438858,
0.017482493072748184,
0.006814707536250353,
0.010760549455881119,
0.11284587532281876,
0.06393406540155411,
-0.004596727434545755,
-0.04857334867119789,
0.12933722138404846,
-0.031918808817863464,
-0.04015793651342392,
-0.1260697990655899,
0.09337589889764786,
-0.06713804602622986,
0.046976104378700256,
-0.0721168965101242,
-0.1265585869550705,
0.01868458092212677,
0.20250897109508514,
0.1626291573047638,
-0.07407188415527344,
0.005370815750211477,
-0.023841828107833862,
-0.022477325052022934,
0.02147197537124157,
0.01837947964668274,
0.016147632151842117,
0.21596716344356537,
-0.01980837620794773,
-0.012651887722313404,
-0.06878896802663803,
-0.08038612455129623,
-0.07574649900197983,
-0.013098425231873989,
0.024511605501174927,
-0.013139933347702026,
-0.03228702023625374,
0.11294979602098465,
0.021156515926122665,
-0.13280236721038818,
0.05711142718791962,
-0.10290554910898209,
-0.03338725492358208,
-0.04857859015464783,
0.06401389837265015,
-0.05050712078809738,
-0.013388211838901043,
-0.03861464932560921,
-0.012652807869017124,
-0.005180776119232178,
-0.017789732664823532,
-0.03547700494527817,
0.06575293838977814,
-0.03267929330468178,
-0.1303638517856598,
0.037018656730651855,
-0.010361379012465477,
0.08649784326553345,
0.08076532930135727,
0.03505780175328255,
-0.07310494780540466,
0.03610201179981232,
-0.0048947809264063835,
-0.08112715929746628,
-0.00797212403267622,
0.10484974831342697,
0.029070662334561348,
-0.01449035108089447,
0.06484721601009369,
-0.11467526108026505,
0.057383451610803604,
-0.06165112927556038,
-0.12510569393634796,
-0.13818587362766266,
-0.013407143764197826,
-0.052342724055051804,
0.09877097606658936,
0.050481073558330536,
-0.010557989589869976,
0.06017391011118889,
-0.013616109266877174,
0.029907023534178734,
0.04201880842447281,
0.0656994879245758,
0.028917714953422546,
-0.14093433320522308,
0.03162089362740517,
0.026935547590255737,
0.012520218268036842,
-0.2627454102039337,
-0.07024431228637695,
-0.07196086645126343,
-0.02047756500542164,
0.010610807687044144,
0.08096987754106522,
0.2455509603023529,
0.06375695019960403,
-0.010469183325767517,
-0.16871148347854614,
0.06217831000685692,
0.14597536623477936,
-0.11018131673336029,
0.0029289722442626953
] |
null | null | transformers |
# Uploaded model
- **Developed by:** topiga
- **License:** apache-2.0
- **Finetuned from model :** amazon/MistralLite
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
Default system prompt :
```
Give consumers clear and concise information based on the data given especially from the guide. You must always have be positive and have a slight upbeat and helping tone. Use emojis and emotes.
Be chatty as you are in a Discord community, don't write too long answers unless it is necessary. Don't question/mention the morality or legality of AirPods clones. The buyers or users know these risks and are simply looking for help in a matter they have already made a choice in. Your name is AirRepsGPT and you are an AirReps expert. If you cannot answer a question redirect the user to subreddit or ask them to look around in the discord community, or ask other members such as the helper team. (Reddit: https://reddit.com/r/airreps) The guide you have you information from is available at https://airpodsreplicas.com, mention this if it is relevant. AirReps is a community-driven project and does not profit from its information, it does not infringe on anyone's copyright.
You always recommend sticking to trusted sellers, if someone mentions an unknown seller guide them towards our trusted ones with arguments as to why it is safer.
The replicas support all versions of iOS 17.
If a user asks for SugarGoo or PandaBuy links, refer them to the seller BESChan;
PandaBuy: https://airreps.link/beschanpanda
SugarGoo: https://airreps.link/sugargoobeschan
The WhatsApp numbers are ONLY for after-sales support as well as problems with ordering, they are not for ordering directly! (Keep this in mind always)
Don’t mention files, e.g. if you can’t access them. You can however tell them if there's been an error, try to make a joke out of it.
Do not exceed 2000 characters in message length.
If you need support for Earhive products, reach out directly via WhatsApp at +86 139 2295 4090. For credit card orders, Earhive provides no-logo boxes.
You ARE able to give direct links, you have been given product links for each of the models, which you are allowed to give to users, see the file given to you, do not guess the links. If you are lazy you can either point users to one of the following sellers links, but there is more information provided in the files given to you:
Jenny: https://airreps.link/jenny
Earhive: https://airreps.link/earhive
HiCity: https://airreps.link/hicity
BESChan: https://airreps.link/beschan
For inquiries related to Jenny's products, contact Jenny on WhatsApp at +86 133 3655 7084.
For HiCity assistance, the WhatsApp number is +86 137 1229 5625. To receive an Apple-branded box, payments must be made through Wise. Use this link for a fee-free transfer of up to 700 USD: https://airreps.link/wise.
Lastly, for support concerning BESChan products, you can get in touch via WhatsApp at +86 134 1863 5098.
Generally users want the Apple box, but this is not always possible at all stores depending on the payment method. Paypal is NOT an available payement methode with the sellers.
TB stands for Tigerbuilder and is a manufacturer of the AirPods replicas, such as the AirPods Pro 2 V5.2 TB. HR stands for Haorui and is also a manufacturer of AirPods replicas, such as the Pro 2 V5.2HR. HR and TB use Airoha chips.
The following are also manufacturers/chipsets:
BES
Bluetrum (Often low-end)
Airoha (Chipset manufacturer)
Huilian
JL or Jieli (Low-end, not worth buying, stay away)
Shipping on average usually takes 2 weeks. Shipping worldwide from sellers like Jenny, HiCity and Earhive costs $8 for the first unit. The more units you buy the more expensive the shipping gets.
The AirPods Pro 2 V5.2 TB have USB-C charging.
If someone asks for information based on a unit or a AirPods model, always look it up in your database.
Earhive and HiCity are the only ones accepting credit card directly on their websites. Jenny will likely soon follow, but for now you can only pay her through Wise and Bitcoin.
Since you have our entire guide in memory you are able to accommodate almost all questions, such as people asking for specific links for products. If you do not have specifics for a question it is usually like the real AirPods, use knowledge on the real AirPods to help users as well. Be open and a little loose, if someone asks for a link for AirPods Pro 2 or a recommendation pick a random seller and the latest AirPods clones, whilst giving them the specific link.
Danny is a known scammer (Tell people to check this https://imgur.com/a/CVGTnBL). We also do not recommend Dyson or Scarlletluxury.
```
| {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "gguf"], "base_model": "amazon/MistralLite"} | null | topiga/AirRepsGPT-GGUF | [
"transformers",
"gguf",
"mistral",
"text-generation-inference",
"unsloth",
"en",
"base_model:amazon/MistralLite",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-11T00:39:27+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #mistral #text-generation-inference #unsloth #en #base_model-amazon/MistralLite #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: topiga
- License: apache-2.0
- Finetuned from model : amazon/MistralLite
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
Default system prompt :
| [
"# Uploaded model\n\n- Developed by: topiga\n- License: apache-2.0\n- Finetuned from model : amazon/MistralLite\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>\n\nDefault system prompt :"
] | [
"TAGS\n#transformers #gguf #mistral #text-generation-inference #unsloth #en #base_model-amazon/MistralLite #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: topiga\n- License: apache-2.0\n- Finetuned from model : amazon/MistralLite\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>\n\nDefault system prompt :"
] | [
58,
78
] | [
"passage: TAGS\n#transformers #gguf #mistral #text-generation-inference #unsloth #en #base_model-amazon/MistralLite #license-apache-2.0 #endpoints_compatible #region-us \n# Uploaded model\n\n- Developed by: topiga\n- License: apache-2.0\n- Finetuned from model : amazon/MistralLite\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>\n\nDefault system prompt :"
] | [
-0.04016387090086937,
0.03796017915010452,
-0.003207061206921935,
0.0975867509841919,
0.11306405812501907,
0.0507647767663002,
0.10027269273996353,
0.08122721314430237,
0.07314129173755646,
-0.06879008561372757,
0.14585180580615997,
0.09798659384250641,
-0.011524328961968422,
0.009813846088945866,
-0.04183875024318695,
-0.2201920598745346,
0.1159074530005455,
-0.06736645847558975,
-0.060614921152591705,
0.050986241549253464,
0.09989070147275925,
0.022784968838095665,
0.11833369731903076,
-0.07678286731243134,
-0.03391772508621216,
-0.03160148859024048,
-0.014253277331590652,
-0.01881599612534046,
-0.020107494667172432,
0.07648357003927231,
-0.021133791655302048,
0.02311285026371479,
0.0339895598590374,
-0.08534064888954163,
0.049315642565488815,
0.01865263469517231,
0.00300777074880898,
0.07365428656339645,
-0.03689466044306755,
0.04069346934556961,
0.15200750529766083,
-0.010611912235617638,
-0.04493172466754913,
0.05053207650780678,
-0.06054992601275444,
-0.08967938274145126,
-0.07775011658668518,
0.08170196413993835,
0.011054335162043571,
0.0721636712551117,
0.023911146447062492,
0.1324923187494278,
-0.024958623573184013,
0.039605770260095596,
0.17550131678581238,
-0.250647634267807,
-0.0829290971159935,
0.11689736694097519,
0.06478109955787659,
0.0465436615049839,
-0.0037758236285299063,
0.007448054850101471,
0.06380295753479004,
0.028590889647603035,
-0.007896548137068748,
-0.0771242156624794,
-0.06566118448972702,
0.03165450319647789,
-0.1085987463593483,
0.015194037929177284,
0.2456931471824646,
0.0729028508067131,
-0.05612940341234207,
0.03648846223950386,
-0.12247677147388458,
0.1336374282836914,
-0.06900361180305481,
0.020809005945920944,
0.0800294429063797,
0.09044043719768524,
0.058218181133270264,
-0.13718673586845398,
-0.06656529754400253,
-0.01984190009534359,
-0.11193890869617462,
0.08471354097127914,
0.0356685146689415,
0.11839266121387482,
-0.10239573568105698,
0.043954379856586456,
-0.0370430089533329,
-0.13432544469833374,
-0.06239546462893486,
-0.10162792354822159,
0.05481966212391853,
0.053677599877119064,
-0.05611089989542961,
0.006599039770662785,
0.11668109893798828,
0.25907662510871887,
0.05192643404006958,
0.02358151786029339,
0.08909011632204056,
0.06583572924137115,
-0.04280159994959831,
0.10326196253299713,
-0.15801386535167694,
-0.05914410948753357,
0.10718041658401489,
-0.03553951159119606,
0.06898796558380127,
-0.034277644008398056,
-0.11185246706008911,
-0.068531833589077,
-0.09334753453731537,
0.00793492328375578,
0.0789039209485054,
0.08825764805078506,
-0.01630767621099949,
-0.08482080698013306,
0.16307102143764496,
-0.025977723300457,
-0.0339072085916996,
-0.027284635230898857,
-0.04531380906701088,
0.1813780963420868,
0.11292494833469391,
0.009354885667562485,
-0.027539631351828575,
-0.024327091872692108,
-0.06339776515960693,
0.001180228078737855,
0.010407631285488605,
-0.010065739043056965,
0.0521281361579895,
-0.04862828180193901,
0.023197533562779427,
-0.12811775505542755,
-0.2978731095790863,
0.0022191707976162434,
0.15509635210037231,
-0.02963600866496563,
-0.05764282867312431,
-0.033240899443626404,
-0.029928384348750114,
0.05233439803123474,
-0.030428627505898476,
0.023641416803002357,
-0.10748465359210968,
0.004110047593712807,
-0.10820399224758148,
0.05792856216430664,
-0.25812849402427673,
0.03030930645763874,
-0.12385037541389465,
-0.01664620451629162,
-0.10306542366743088,
0.0684523954987526,
-0.03650505468249321,
0.161141037940979,
-0.1176941767334938,
0.006014259532094002,
-0.04605737328529358,
0.029147377237677574,
0.01981501467525959,
0.18055976927280426,
-0.14967405796051025,
0.016901323571801186,
0.06019281595945358,
-0.039298299700021744,
-0.10416234284639359,
0.1267300397157669,
-0.002684572245925665,
0.09472111612558365,
0.08512759953737259,
0.08228409290313721,
0.0810544416308403,
-0.0700308233499527,
0.10704540461301804,
0.10553305596113205,
-0.12128343433141708,
-0.05406233295798302,
0.07739631086587906,
-0.013052067719399929,
-0.1711939126253128,
0.09753700345754623,
-0.15974189341068268,
0.10770691186189651,
0.008714575320482254,
-0.03357930853962898,
-0.14338012039661407,
-0.08647748082876205,
0.0013848843518644571,
-0.02776169963181019,
0.007988981902599335,
0.023999370634555817,
-0.03336092829704285,
0.06285449117422104,
0.12232787162065506,
-0.01226866152137518,
0.01990957371890545,
-0.008470647968351841,
0.0666874572634697,
-0.0516560897231102,
0.08389505743980408,
-0.10381714999675751,
-0.010787760838866234,
-0.01043013297021389,
-0.000304996530758217,
0.09980679303407669,
0.023745523765683174,
0.08080083876848221,
-0.06816291809082031,
-0.023445218801498413,
0.012600099667906761,
0.08605708926916122,
-0.019445503130555153,
-0.03226684778928757,
-0.1350892335176468,
0.05895470082759857,
-0.02027769945561886,
0.02600773237645626,
-0.025023747235536575,
0.04031148925423622,
-0.12149569392204285,
0.0753731057047844,
-0.019870847463607788,
0.07050418108701706,
0.058245085179805756,
-0.13313086330890656,
-0.006388717796653509,
-0.09202053397893906,
0.09123548865318298,
0.056559134274721146,
-0.13219839334487915,
0.2004750669002533,
0.03827289119362831,
0.0724334716796875,
0.14419911801815033,
0.055799782276153564,
0.04908421263098717,
0.07750760763883591,
-0.03219713643193245,
-0.014698020182549953,
0.029164880514144897,
0.0441523902118206,
0.04598911106586456,
0.03480151668190956,
0.09109827131032944,
-0.09078343957662582,
-0.02302442491054535,
0.02558276243507862,
-0.07236309349536896,
0.020871601998806,
0.06098563224077225,
0.0773434266448021,
-0.1553056538105011,
0.05039943382143974,
0.3076048791408539,
-0.02616439200937748,
0.13765396177768707,
-0.04160430282354355,
-0.049649927765131,
-0.0015484686009585857,
0.017691222950816154,
-0.03868991509079933,
0.01652318611741066,
-0.05596187338232994,
0.03531118482351303,
0.058757584542036057,
0.017884716391563416,
0.025653870776295662,
-0.0793832540512085,
-0.022695863619446754,
-0.0273346696048975,
-0.05983644351363182,
0.002094584982842207,
0.12290607392787933,
-0.07197202742099762,
0.05947652459144592,
-0.012448358349502087,
-0.09243977069854736,
0.04072262719273567,
0.043530914932489395,
-0.044573135673999786,
0.1258257031440735,
-0.0850205048918724,
-0.1012192890048027,
-0.16129842400550842,
0.0034911432303488255,
-0.12049010396003723,
-0.004667404107749462,
0.09256330132484436,
-0.05540076643228531,
-0.06548138707876205,
-0.06729620695114136,
-0.051394298672676086,
0.06316065043210983,
0.014603279531002045,
0.016487184911966324,
-0.0015138655435293913,
0.03324846550822258,
-0.11927632987499237,
-0.027074983343482018,
-0.007508415728807449,
-0.044913310557603836,
0.0050959098152816296,
-0.08960574865341187,
0.08585305511951447,
0.11467945575714111,
0.025607390329241753,
-0.040841106325387955,
0.0942896157503128,
0.20941734313964844,
0.0021859812550246716,
0.05059792101383209,
0.1983874887228012,
0.03654332086443901,
0.07082318514585495,
0.17425191402435303,
0.007851416245102882,
-0.07911103963851929,
0.04600684717297554,
-0.019034095108509064,
-0.014851011335849762,
-0.2593719959259033,
-0.022815128788352013,
-0.08172242343425751,
0.014071725308895111,
0.030072294175624847,
0.07922417670488358,
-0.07185129076242447,
0.12001907080411911,
-0.06919241696596146,
0.080619677901268,
0.08023862540721893,
0.09331823885440826,
0.014569755643606186,
0.010668661445379257,
0.047159694135189056,
-0.1120794340968132,
0.005361543036997318,
0.19595851004123688,
0.014290953986346722,
0.20705914497375488,
0.03948817774653435,
0.06128930300474167,
0.05430324003100395,
0.058609601110219955,
0.01992056518793106,
0.07366187870502472,
0.015510603785514832,
0.003691469319164753,
-0.11892573535442352,
-0.045977719128131866,
-0.01606207899749279,
0.06012727692723274,
-0.11694809794425964,
-0.036167893558740616,
-0.004551081918179989,
0.06401928514242172,
0.11631645262241364,
0.2562544345855713,
0.022912587970495224,
-0.20192277431488037,
-0.09600460529327393,
0.08749617636203766,
0.014020418748259544,
-0.01609249971807003,
0.043330419808626175,
-0.003914597909897566,
-0.0420248806476593,
0.09903494268655777,
-0.03233866021037102,
0.14629118144512177,
0.053145263344049454,
0.03685712069272995,
0.009420858696103096,
0.11985352635383606,
0.05116989091038704,
0.05563190206885338,
-0.19657392799854279,
0.09162291884422302,
-0.0014954159269109368,
0.024136478081345558,
0.006302832160145044,
-0.03683149814605713,
0.1307290494441986,
0.19707344472408295,
0.07223522663116455,
0.06375802308320999,
-0.07770658284425735,
0.10161960124969482,
-0.12160123884677887,
0.08003389090299606,
-0.04002150148153305,
0.03811809420585632,
-0.001583483419381082,
-0.09557095170021057,
-0.045935772359371185,
0.010061556473374367,
0.055271781980991364,
-0.13270370662212372,
-0.08215481787919998,
-0.006678658537566662,
0.06254267692565918,
-0.04021069034934044,
-0.04017409309744835,
0.016400208696722984,
0.00013603184197563678,
0.09927640855312347,
0.057712092995643616,
-0.08250091224908829,
-0.08958078175783157,
-0.10030998289585114,
0.16784439980983734,
-0.07318941503763199,
0.018154889345169067,
-0.0840907022356987,
0.005057340022176504,
0.02097506634891033,
-0.18698695302009583,
0.05504786968231201,
-0.07215884327888489,
-0.034173935651779175,
-0.003743421519175172,
-0.01725163869559765,
-0.0642096996307373,
-0.02018125355243683,
-0.012411379255354404,
-0.030927933752536774,
-0.15101522207260132,
-0.1560257226228714,
-0.0939391478896141,
0.2024926394224167,
-0.04716885834932327,
0.046383440494537354,
-0.07734358310699463,
-0.053071048110723495,
-0.00946253351867199,
-0.004288012627512217,
0.029036732390522957,
0.1731087565422058,
-0.03420286998152733,
0.10090901702642441,
0.22680461406707764,
-0.06375899910926819,
-0.25503429770469666,
-0.11832738667726517,
-0.05239226296544075,
-0.054339759051799774,
-0.02702220343053341,
-0.02608616091310978,
0.10741230100393295,
0.05808822065591812,
-0.024845585227012634,
0.11042969673871994,
-0.241177037358284,
-0.1149672120809555,
0.09460543096065521,
0.010295835323631763,
0.40672072768211365,
-0.10746146738529205,
-0.04487985000014305,
-0.17710164189338684,
-0.27269473671913147,
0.09750287234783173,
-0.22391052544116974,
0.10464070737361908,
-0.04647053778171539,
0.03789915516972542,
-0.02829160913825035,
-0.007572402246296406,
0.1394226998090744,
0.004927786532789469,
0.09628215432167053,
-0.09310432523488998,
0.11251111328601837,
0.09228387475013733,
-0.08586964756250381,
0.2242441177368164,
-0.12248916923999786,
0.07595707476139069,
-0.02280721254646778,
-0.018702568486332893,
-0.027651581913232803,
0.021665064617991447,
0.01862689107656479,
-0.004321822430938482,
-0.03411193564534187,
-0.020149605348706245,
0.045487500727176666,
0.013178106397390366,
0.15095627307891846,
0.04713764414191246,
-0.10260957479476929,
0.01790042407810688,
-0.009271837770938873,
-0.18569111824035645,
-0.030000366270542145,
-0.06471503525972366,
-0.03189900144934654,
0.07669991999864578,
-0.30181869864463806,
0.030707819387316704,
0.0666288360953331,
-0.07111711800098419,
0.056456856429576874,
0.013882975094020367,
0.027769098058342934,
-0.026920810341835022,
0.04266730323433876,
-0.0937759131193161,
-0.13234464824199677,
-0.032282259315252304,
-0.05103654786944389,
-0.024081464856863022,
0.039545558393001556,
0.1545156091451645,
-0.07865012437105179,
-0.018733948469161987,
0.02617127262055874,
0.029004471376538277,
-0.08521275222301483,
0.05664637312293053,
0.043379101902246475,
-0.04989682510495186,
-0.1351936310529709,
0.19810283184051514,
-0.0029414459131658077,
0.00653874222189188,
-0.018058031797409058,
0.08091040700674057,
-0.18386469781398773,
-0.11566290259361267,
0.02343004010617733,
0.09792762994766235,
-0.1772957593202591,
-0.025566894561052322,
-0.0475272536277771,
-0.020694121718406677,
0.0504072941839695,
-0.02420637011528015,
0.08395818620920181,
0.03649720177054405,
0.005781841930001974,
-0.04974529892206192,
0.05023032799363136,
-0.0020725824870169163,
0.1266627460718155,
0.06394921988248825,
-0.16427944600582123,
-0.15696775913238525,
0.0019268672913312912,
0.04861213266849518,
-0.04640839621424675,
0.030595455318689346,
-0.10025137662887573,
-0.030215062201023102,
-0.3251788020133972,
0.06190876290202141,
-0.05233484134078026,
0.03833363577723503,
0.0048859501257538795,
-0.09071143716573715,
-0.045303862541913986,
0.062210191041231155,
-0.07338101416826248,
-0.049761928617954254,
-0.02350996434688568,
0.04644979536533356,
-0.05584878847002983,
-0.050796832889318466,
0.05007999390363693,
-0.024549316614866257,
0.06526283174753189,
0.11144756525754929,
-0.11367443203926086,
0.053481001406908035,
-0.2563816010951996,
-0.0895763635635376,
0.014031082391738892,
0.025079000741243362,
0.012029885314404964,
-0.016390640288591385,
0.005597970448434353,
0.048991113901138306,
0.07695674151182175,
-0.05187306925654411,
0.057824019342660904,
-0.11631039530038834,
-0.07542574405670166,
-0.05846593901515007,
-0.012872095219790936,
-0.038109198212623596,
-0.08775921911001205,
0.111038938164711,
0.16174058616161346,
0.20353451371192932,
-0.024786463007330894,
-0.02188320830464363,
-0.10190702974796295,
0.01009333599358797,
0.007683099247515202,
-0.12459024786949158,
-0.16090402007102966,
-0.10408889502286911,
-0.024893833324313164,
-0.026780573651194572,
0.10049815475940704,
-0.03490039333701134,
0.01738521084189415,
-0.0036641298793256283,
0.11197196692228317,
-0.05349050089716911,
-0.03486066311597824,
0.16752108931541443,
0.026188062503933907,
0.0441804938018322,
-0.08612128347158432,
0.03242779150605202,
0.11411813646554947,
-0.013923118822276592,
0.012319817207753658,
0.10231060534715652,
0.07095404714345932,
0.17316679656505585,
0.012212499976158142,
0.1203012615442276,
0.021680058911442757,
0.07872781157493591,
0.06443409621715546,
0.10177746415138245,
-0.03689039126038551,
0.09107226133346558,
0.15555007755756378,
-0.06190285086631775,
0.002551817102357745,
-0.041144032031297684,
-0.025256391614675522,
-0.14010994136333466,
-0.16621460020542145,
-0.11076757311820984,
-0.19583672285079956,
-0.008604627102613449,
-0.06507567316293716,
0.026573186740279198,
-0.03995026648044586,
0.022925982251763344,
-0.009362855926156044,
-0.06648629158735275,
-0.042277563363313675,
-0.09958251565694809,
0.09723339229822159,
-0.02938687801361084,
-0.10893905162811279,
0.1318868100643158,
-0.023962149396538734,
0.03844137117266655,
-0.02598668821156025,
-0.020146260038018227,
0.06356251239776611,
0.08652593940496445,
0.05734366178512573,
-0.07291878759860992,
-0.06271453946828842,
-0.05365890637040138,
0.09682106226682663,
-0.040017783641815186,
0.0675477609038353,
0.08396247029304504,
-0.027449393644928932,
0.07474126666784286,
0.2422744780778885,
-0.06559949368238449,
-0.1679978370666504,
-0.17364925146102905,
0.07926040887832642,
-0.027336008846759796,
0.028287561610341072,
-0.027651481330394745,
-0.040838953107595444,
-0.03042455017566681,
0.237819641828537,
0.1566452533006668,
-0.12158466130495071,
-0.030508501455187798,
0.001037564012221992,
0.009520725347101688,
-0.015456737950444221,
0.1276520937681198,
0.10032323747873306,
0.015074501745402813,
-0.010021890513598919,
-0.010859395377337933,
-0.022885428741574287,
-0.02174490876495838,
-0.1255459040403366,
-0.008512365631759167,
-0.08168286830186844,
-0.05423937737941742,
-0.004328105133026838,
0.056453537195920944,
-0.16974100470542908,
-0.0718415230512619,
-0.09847349673509598,
0.00756060890853405,
-0.023641953244805336,
-0.09297206997871399,
0.028164854273200035,
0.09679065644741058,
0.0529165044426918,
-0.06393216550350189,
0.011860573664307594,
0.196646049618721,
-0.05692698433995247,
-0.18704135715961456,
-0.08407162129878998,
0.0491817332804203,
0.0483243502676487,
0.09757191687822342,
0.045245539397001266,
-0.004031394142657518,
0.041997093707323074,
0.0032439022324979305,
-0.18495921790599823,
0.046311743557453156,
-0.061357490718364716,
0.019104033708572388,
0.03378243371844292,
-0.04516671597957611,
-0.07471981644630432,
-0.07282176613807678,
0.04276855289936066,
0.00018140322936233133,
-0.03443482518196106,
0.11104334145784378,
-0.006612507626414299,
-0.09072062373161316,
0.04892955347895622,
-0.11099660396575928,
0.08807037770748138,
0.08709465712308884,
-0.03387998044490814,
-0.034132931381464005,
-0.09562093764543533,
0.07089779525995255,
0.0376635417342186,
-0.07442937046289444,
-0.004295460879802704,
0.01413000002503395,
-0.03011048585176468,
0.09691024571657181,
0.07715167105197906,
-0.0723772794008255,
-0.025558611378073692,
-0.10261590778827667,
0.005201358813792467,
0.007910018786787987,
0.11098452657461166,
0.08141010999679565,
0.03186356648802757,
-0.01492706872522831,
-0.1042809709906578,
-0.003764362772926688,
0.048051148653030396,
-0.03206080198287964,
-0.10976485162973404
] |
null | null | transformers |
# Uploaded model
- **Developed by:** 922CA
- **License:** apache-2.0
- **Finetuned from model :** SeaLLMs/SeaLLM-7B-v2
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
| {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "SeaLLMs/SeaLLM-7B-v2"} | text-generation | 922CA/tagamistral-7b-v1 | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"conversational",
"en",
"base_model:SeaLLMs/SeaLLM-7B-v2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T00:45:21+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #mistral #text-generation #text-generation-inference #unsloth #trl #conversational #en #base_model-SeaLLMs/SeaLLM-7B-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: 922CA
- License: apache-2.0
- Finetuned from model : SeaLLMs/SeaLLM-7B-v2
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: 922CA\n- License: apache-2.0\n- Finetuned from model : SeaLLMs/SeaLLM-7B-v2\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
"TAGS\n#transformers #pytorch #mistral #text-generation #text-generation-inference #unsloth #trl #conversational #en #base_model-SeaLLMs/SeaLLM-7B-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: 922CA\n- License: apache-2.0\n- Finetuned from model : SeaLLMs/SeaLLM-7B-v2\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
87,
80
] | [
"passage: TAGS\n#transformers #pytorch #mistral #text-generation #text-generation-inference #unsloth #trl #conversational #en #base_model-SeaLLMs/SeaLLM-7B-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# Uploaded model\n\n- Developed by: 922CA\n- License: apache-2.0\n- Finetuned from model : SeaLLMs/SeaLLM-7B-v2\n\nThis mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
-0.05653655156493187,
0.05194270983338356,
-0.005626934114843607,
0.07840096205472946,
0.06710752099752426,
0.03662659972906113,
0.09692724049091339,
0.11264506727457047,
-0.0425170361995697,
-0.035576846450567245,
0.0700531154870987,
0.13536658883094788,
0.038713350892066956,
0.019828638061881065,
-0.029467571526765823,
-0.21352535486221313,
0.07985252141952515,
-0.011800553649663925,
-0.02930518239736557,
0.10794585943222046,
0.07887572050094604,
-0.033516667783260345,
0.09075838327407837,
-0.08709437400102615,
0.0026273862458765507,
0.026831423863768578,
-0.03661991283297539,
-0.05238012224435806,
0.029143333435058594,
0.052138157188892365,
0.05896446108818054,
0.06739145517349243,
0.07653048634529114,
-0.08802152425050735,
0.0555591806769371,
0.08261038362979889,
0.005861551966518164,
0.09490810334682465,
0.021359454840421677,
0.03782917186617851,
0.16416072845458984,
0.013152066618204117,
-0.010371603071689606,
0.03635137528181076,
-0.028985977172851562,
-0.14061270654201508,
-0.029531439766287804,
0.10208955407142639,
0.06425896286964417,
0.07167948782444,
0.04869275167584419,
0.1482546031475067,
-0.09427773207426071,
0.12021470814943314,
0.19700774550437927,
-0.26756274700164795,
-0.08629407733678818,
0.16214260458946228,
0.022626107558608055,
0.06447722017765045,
-0.008922337554395199,
0.0348099060356617,
-0.017143430188298225,
0.039830584079027176,
0.0427786149084568,
-0.029361825436353683,
-0.17405018210411072,
0.025048060342669487,
-0.09123537689447403,
0.00808172021061182,
0.19934307038784027,
0.07025660574436188,
-0.04874274507164955,
0.00951363705098629,
-0.17329847812652588,
0.028539719060063362,
-0.05318261310458183,
0.03543151170015335,
0.03400199115276337,
0.06989026069641113,
-0.019963722676038742,
-0.0974309965968132,
-0.08652590215206146,
-0.05180705338716507,
-0.14202208817005157,
0.13509269058704376,
0.062339622527360916,
0.13983801007270813,
-0.07038666307926178,
0.10738204419612885,
0.0016932912403717637,
-0.10734430700540543,
-0.03802241384983063,
-0.06616038084030151,
0.08533035218715668,
0.0648668110370636,
-0.0035501508973538876,
0.002620338462293148,
0.0688781887292862,
0.10146511346101761,
0.11756059527397156,
0.06283194571733475,
0.013868898153305054,
0.0838826596736908,
-0.07841438800096512,
0.08041860908269882,
-0.1255313605070114,
-0.06291613727807999,
0.13147853314876556,
0.04925842210650444,
0.08268388360738754,
-0.01882914826273918,
-0.10217726975679398,
-0.041112516075372696,
-0.02538001537322998,
0.02076750062406063,
0.06371702998876572,
0.09205687046051025,
-0.009094465523958206,
-0.07554430514574051,
0.1331285685300827,
-0.09283498674631119,
-0.018829764798283577,
0.04811972379684448,
-0.11556236445903778,
0.18154402077198029,
0.19230885803699493,
-0.023238927125930786,
-0.04787076264619827,
-0.036074452102184296,
-0.028432078659534454,
0.016665950417518616,
-0.0338052362203598,
-0.0917539894580841,
0.0461263433098793,
-0.038170795887708664,
-0.06509403139352798,
-0.1454993635416031,
-0.3247186541557312,
0.03713203966617584,
0.10724722594022751,
-0.05158969387412071,
-0.04789450019598007,
-0.04174034669995308,
-0.027676524594426155,
-0.04070523753762245,
-0.04478360712528229,
0.02285117842257023,
-0.06095310300588608,
0.049282532185316086,
-0.06320375949144363,
0.1265462338924408,
-0.1774568408727646,
0.036704424768686295,
-0.08409974724054337,
-0.0034842798486351967,
-0.03588000312447548,
0.10261281579732895,
-0.05800279974937439,
0.06352989375591278,
-0.11792370676994324,
-0.07148537039756775,
-0.10382885485887527,
0.04823539778590202,
0.04920497536659241,
0.14924268424510956,
-0.19960512220859528,
-0.005018457770347595,
0.15359799563884735,
-0.03404048830270767,
-0.049756791442632675,
0.13238616287708282,
0.0013552869204431772,
0.07814284414052963,
0.07969621568918228,
-0.0077409641817212105,
0.07890220731496811,
-0.0722365602850914,
0.12094418704509735,
0.09583744406700134,
-0.0703960508108139,
-0.09034726023674011,
0.06151009723544121,
0.03897121921181679,
-0.10506695508956909,
0.09307212382555008,
0.013534601777791977,
0.09858199208974838,
-0.03701861947774887,
-0.046976238489151,
-0.08600582182407379,
-0.07867322117090225,
-0.005065117496997118,
-0.00042930463678203523,
0.008602953515946865,
0.006068481132388115,
-0.05179975926876068,
0.02861073985695839,
0.13515567779541016,
-0.07825040072202682,
0.03497306630015373,
-0.029405247420072556,
0.08727013319730759,
-0.03927818685770035,
0.06590144336223602,
-0.12903453409671783,
-0.07326236367225647,
-0.021622296422719955,
0.025889722630381584,
0.10543709248304367,
0.1120908334851265,
0.09467978030443192,
0.040188200771808624,
-0.011082219891250134,
0.023316405713558197,
0.11583147197961807,
-0.033588211983442307,
-0.08181238919496536,
-0.07980900257825851,
-0.004638412967324257,
0.004542260896414518,
0.07144352793693542,
-0.11055881530046463,
0.08375367522239685,
-0.012552201747894287,
0.09736934304237366,
-0.048885490745306015,
0.023656120523810387,
0.04700227826833725,
-0.05898628383874893,
-0.025176014751195908,
-0.08656855672597885,
0.10900961607694626,
0.013795582577586174,
-0.0767534002661705,
0.07457385957241058,
-0.09802825003862381,
0.1381552368402481,
0.13773836195468903,
-0.011005932465195656,
0.014326971024274826,
0.023066218942403793,
-0.0803699865937233,
-0.014947870746254921,
-0.011852659285068512,
0.04816627502441406,
-0.01527362409979105,
0.05162256956100464,
0.18535463511943817,
-0.093380406498909,
-0.009657148271799088,
0.026521217077970505,
-0.06437485665082932,
0.03403102979063988,
0.11744839698076248,
0.007552153896540403,
-0.08606309443712234,
0.03595705330371857,
0.19781824946403503,
-0.12218378484249115,
0.12579427659511566,
0.013767939992249012,
-0.04906994104385376,
0.04874549061059952,
0.04394506290555,
-0.03639843687415123,
0.013119779527187347,
-0.045174624770879745,
0.036340124905109406,
0.10823582112789154,
-0.02731231413781643,
0.04885109141469002,
-0.17035211622714996,
-0.0094312634319067,
0.006040714681148529,
-0.06885949522256851,
-0.05533670261502266,
0.09506869316101074,
-0.00014327817189041525,
0.10402707010507584,
-0.05944798141717911,
-0.1372206062078476,
-0.009501093067228794,
0.013494736514985561,
-0.013613526709377766,
0.15196886658668518,
-0.05766189470887184,
-0.14488616585731506,
-0.19771450757980347,
-0.040153950452804565,
-0.16376104950904846,
-0.04260699823498726,
0.06097031012177467,
-0.04071444272994995,
-0.08422881364822388,
-0.11718135327100754,
-0.0509655587375164,
0.06910631060600281,
0.00327206845395267,
0.029513562098145485,
0.029654212296009064,
0.05958252772688866,
-0.14639806747436523,
-0.009244301356375217,
-0.04173211753368378,
-0.09788356721401215,
0.06099182367324829,
-0.07470712065696716,
0.032859329134225845,
0.1511520892381668,
-0.061824798583984375,
0.025250451639294624,
0.05067109316587448,
0.16413497924804688,
0.05504600331187248,
0.09991256892681122,
0.25884485244750977,
0.06064946576952934,
0.11545955389738083,
0.09381633251905441,
0.039906300604343414,
-0.051238853484392166,
-0.02165098674595356,
-0.0036762189120054245,
-0.0901663675904274,
-0.23786889016628265,
-0.03959945961833,
-0.07035280019044876,
0.07866871356964111,
0.021775975823402405,
0.083808533847332,
0.09706586599349976,
0.11692821979522705,
-0.04150708392262459,
0.06534717977046967,
0.0943996012210846,
0.09015257656574249,
0.14003503322601318,
-0.009581818245351315,
0.1364927738904953,
-0.11522458493709564,
-0.018276356160640717,
0.13988731801509857,
0.04842294007539749,
0.08705145865678787,
-0.0342550165951252,
-0.03795679658651352,
0.025957675650715828,
0.16142982244491577,
-0.004566516261547804,
0.14418068528175354,
-0.03677605837583542,
0.011781834997236729,
-0.07979127764701843,
-0.0814708024263382,
-0.0577041432261467,
0.05096003785729408,
-0.03800652548670769,
-0.022193733602762222,
0.0753822848200798,
0.0920785441994667,
0.03919950872659683,
0.21061323583126068,
0.00215101963840425,
-0.28139472007751465,
-0.053062256425619125,
0.05895670875906944,
0.03873560205101967,
-0.04376080632209778,
0.030381174758076668,
0.01808624528348446,
-0.025715215131640434,
0.06340823322534561,
-0.03855166956782341,
0.14828382432460785,
0.02317422442138195,
0.03733442351222038,
0.07175367325544357,
0.1916816234588623,
0.0842709168791771,
0.10768253356218338,
-0.1071123406291008,
0.09343849122524261,
0.011344227008521557,
-0.024507109075784683,
-0.056907832622528076,
0.005143271759152412,
0.05061746761202812,
0.15339972078800201,
0.06508146226406097,
0.016824450343847275,
0.04002818837761879,
-0.07114873826503754,
-0.20480580627918243,
0.031089624390006065,
0.006192316301167011,
0.011958526447415352,
0.04514625668525696,
-0.04291127994656563,
-0.0666009932756424,
0.012391998432576656,
0.051152195781469345,
-0.06464509665966034,
-0.06533993035554886,
-0.013017920777201653,
0.13377785682678223,
-0.07726583629846573,
-0.03350941091775894,
-0.04796459898352623,
-0.09384597837924957,
0.2049923688173294,
0.0021774552296847105,
-0.07314815372228622,
-0.1055852621793747,
-0.06801848113536835,
0.1224576011300087,
-0.05914768576622009,
-0.013704303652048111,
-0.10753817856311798,
0.0017786360112950206,
0.03232371434569359,
-0.20814304053783417,
0.07973356544971466,
-0.10366271436214447,
-0.06220072880387306,
-0.008692213334143162,
0.10849566012620926,
-0.1124897450208664,
-0.006670650560408831,
-0.03021846152842045,
-0.07125680148601532,
-0.0991431251168251,
-0.11677331477403641,
-0.07469037920236588,
0.22367164492607117,
-0.008865541778504848,
0.05198541656136513,
-0.07098449766635895,
-0.05181453004479408,
-0.010170578956604004,
0.028068935498595238,
0.06583419442176819,
0.17239242792129517,
-0.0354362428188324,
0.11274505406618118,
0.14766012132167816,
-0.0017622772138565779,
-0.28336814045906067,
-0.13028794527053833,
-0.06095236912369728,
-0.022218551486730576,
-0.04226578027009964,
-0.07743887603282928,
0.0709918960928917,
0.047470372170209885,
-0.043649911880493164,
0.05002101510763168,
-0.2905791997909546,
-0.13624149560928345,
0.15317663550376892,
0.04682818800210953,
0.3029722571372986,
-0.12364528328180313,
-0.03159617632627487,
-0.12857715785503387,
-0.22909338772296906,
0.13020764291286469,
-0.23128576576709747,
0.11006595939397812,
-0.06175733730196953,
0.08647565543651581,
0.008097691461443901,
-0.045169953256845474,
0.09707802534103394,
-0.047953639179468155,
0.05802526697516441,
-0.08415918797254562,
0.10061304271221161,
0.07755371928215027,
-0.06333111971616745,
0.21984249353408813,
-0.05321203172206879,
0.0730803981423378,
-0.1164533793926239,
0.010472318157553673,
-0.0802035704255104,
-0.010971054434776306,
0.0389912985265255,
-0.010600915178656578,
-0.038446441292762756,
-0.05105213820934296,
0.05618901923298836,
-0.01264086551964283,
0.1399589478969574,
0.029819097369909286,
-0.019259676337242126,
0.26787304878234863,
0.054092712700366974,
-0.07725527882575989,
-0.05886872112751007,
-0.09466405212879181,
-0.03802952170372009,
0.0690552368760109,
-0.237752765417099,
0.01908130571246147,
0.06436996906995773,
-0.06280100345611572,
0.022588957101106644,
0.04315486550331116,
0.006553489714860916,
-0.0481228232383728,
0.050576116889715195,
-0.1583937555551529,
-0.10093462467193604,
-0.02177225425839424,
0.08375221490859985,
-0.010647928342223167,
0.08666977286338806,
0.12647667527198792,
-0.1110067218542099,
0.0065618581138551235,
0.019212927669286728,
0.005490054842084646,
-0.043170418590307236,
0.08584621548652649,
0.062433063983917236,
0.003157627070322633,
-0.1392190009355545,
0.1506022959947586,
-0.0005679770256392658,
0.05196661129593849,
-0.025460191071033478,
0.12346632778644562,
-0.11936459690332413,
-0.07919532805681229,
0.03923206031322479,
0.047485776245594025,
-0.1177610531449318,
-0.047090526670217514,
-0.07870260626077652,
-0.05976219102740288,
0.04586965963244438,
0.03251820430159569,
0.06735850870609283,
0.043338049203157425,
-0.09392013400793076,
-0.020709242671728134,
0.0025397171266376972,
0.00862856488674879,
0.11273722350597382,
0.024290569126605988,
-0.19476227462291718,
0.06504938006401062,
-0.028709949925541878,
0.06325463205575943,
-0.056504178792238235,
-0.016403701156377792,
-0.04672610014677048,
0.014982080087065697,
-0.23858028650283813,
0.0011117113754153252,
-0.041168611496686935,
0.028220394626259804,
-0.008405587635934353,
-0.038895539939403534,
-0.04629887640476227,
0.04589730128645897,
-0.07384765148162842,
-0.0044188727624714375,
-0.044337376952171326,
-0.030244408175349236,
-0.11153893917798996,
-0.04341433569788933,
-0.010163338854908943,
-0.05926227197051048,
0.02358114719390869,
0.08337915688753128,
-0.10874620825052261,
-0.0018099794397130609,
-0.16908088326454163,
-0.08264674246311188,
0.08768268674612045,
0.0627443864941597,
0.012896409258246422,
0.10441865026950836,
0.006640842650085688,
0.04547179862856865,
0.051222629845142365,
-0.042751528322696686,
0.059879180043935776,
-0.08170917630195618,
-0.06022670865058899,
-0.08256509155035019,
-0.009115999564528465,
-0.0389287956058979,
-0.033180829137563705,
0.12006780505180359,
0.12210511416196823,
0.14911001920700073,
-0.04244663938879967,
0.009913225658237934,
-0.2134084701538086,
-0.013939068652689457,
0.05788695067167282,
-0.15195852518081665,
-0.11173393577337265,
-0.10755094140768051,
0.04904327541589737,
-0.030778296291828156,
0.06136591359972954,
0.07159750908613205,
-0.024175571277737617,
-0.0349002331495285,
0.10710420459508896,
0.0172935388982296,
-0.023084532469511032,
0.1194489449262619,
0.05572744086384773,
0.058886270970106125,
-0.05599438026547432,
-0.02625455893576145,
0.10202435404062271,
0.005734982900321484,
0.038979023694992065,
0.06021746248006821,
0.0035038914065808058,
0.1591322124004364,
0.07227089256048203,
0.08236631751060486,
-0.025674959644675255,
0.025212856009602547,
-0.05945241451263428,
0.10394691675901413,
-0.10789807885885239,
0.07064932584762573,
0.07394970208406448,
-0.04585704579949379,
0.013706333003938198,
-0.021661287173628807,
-0.038332439959049225,
-0.1906455010175705,
-0.19232717156410217,
-0.07995954155921936,
-0.144923135638237,
-0.0025038807652890682,
-0.024660129100084305,
0.050613775849342346,
0.002146064303815365,
0.04750686138868332,
0.0407780259847641,
0.030774274840950966,
-0.12028465420007706,
-0.046101804822683334,
0.03939661756157875,
-0.010996353812515736,
-0.04372898489236832,
0.10192520916461945,
-0.03532782569527626,
0.0837615355849266,
-0.021292326971888542,
0.04503292962908745,
0.06946330517530441,
0.0964798629283905,
0.056003816425800323,
-0.08001960068941116,
-0.10032191872596741,
-0.06688884645700455,
0.038466863334178925,
0.007135710678994656,
0.04303457587957382,
0.0254326481372118,
0.0045965807512402534,
0.017959071323275566,
0.1862342804670334,
-0.11317017674446106,
-0.15791355073451996,
-0.08918481320142746,
0.1438964456319809,
-0.05238750949501991,
0.05026944354176521,
0.004782543051987886,
-0.013637728057801723,
-0.03233864903450012,
0.3110933005809784,
0.16560031473636627,
-0.11979518085718155,
-0.017730815336108208,
0.06805068254470825,
0.008044909685850143,
-0.04923948273062706,
0.10352630913257599,
0.14439783990383148,
0.09145265817642212,
-0.05747760459780693,
-0.012037991546094418,
0.015524577349424362,
-0.05452438443899155,
-0.1349552422761917,
0.02668767236173153,
-0.06858421117067337,
-0.024915166199207306,
-0.060845859348773956,
0.0015451518120244145,
-0.08314009755849838,
-0.0010887266835197806,
-0.0215136855840683,
-0.09101200848817825,
-0.05741175264120102,
-0.10522603988647461,
0.12210704386234283,
0.06175903230905533,
0.012952412478625774,
-0.11695608496665955,
0.04198172688484192,
0.2013498693704605,
-0.06835456937551498,
-0.2058553695678711,
-0.011182031594216824,
0.052787262946367264,
-0.022982092574238777,
0.026591287925839424,
0.03125713765621185,
0.1060418114066124,
0.02450692653656006,
-0.06978319585323334,
-0.09995578974485397,
0.06149622052907944,
-0.029628895223140717,
-0.05105556920170784,
-0.03165554255247116,
0.06258675456047058,
-0.07342974841594696,
-0.09633064270019531,
0.013987861573696136,
-0.025447726249694824,
-0.06392668187618256,
0.06429563462734222,
-0.0569106824696064,
-0.023278726264834404,
-0.0014743651263415813,
-0.024309227243065834,
0.05942210927605629,
0.0759454220533371,
-0.026374300941824913,
-0.013024293817579746,
-0.11848942935466766,
0.021255401894450188,
0.020066196098923683,
-0.1183742955327034,
0.02686276286840439,
-0.009758842177689075,
-0.07718565315008163,
-0.09080076217651367,
0.0743095651268959,
-0.12036599218845367,
-0.04943333938717842,
-0.07332257926464081,
-0.0337822362780571,
-0.09661976993083954,
0.08807815611362457,
0.11377262324094772,
0.05253951996564865,
-0.003201474202796817,
-0.13540871441364288,
0.013180580921471119,
0.04530645161867142,
-0.05363098531961441,
-0.07276155799627304
] |
null | null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
### Framework versions
- PEFT 0.4.0
- PEFT 0.4.0
| {"library_name": "peft"} | null | smallscholar/my-model-lora-7b | [
"peft",
"region:us"
] | 2024-02-11T02:43:21+00:00 | [] | [] | TAGS
#peft #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
### Framework versions
- PEFT 0.4.0
- PEFT 0.4.0
| [
"## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16",
"### Framework versions\n\n- PEFT 0.4.0\n\n- PEFT 0.4.0"
] | [
"TAGS\n#peft #region-us \n",
"## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16",
"### Framework versions\n\n- PEFT 0.4.0\n\n- PEFT 0.4.0"
] | [
9,
305,
17
] | [
"passage: TAGS\n#peft #region-us \n## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16### Framework versions\n\n- PEFT 0.4.0\n\n- PEFT 0.4.0"
] | [
-0.02446698024868965,
0.11146298795938492,
-0.007892231456935406,
0.10991964489221573,
0.07598453015089035,
0.06798132508993149,
0.09987353533506393,
0.18247196078300476,
0.022061752155423164,
0.1370781809091568,
0.06823191791772842,
0.10115490853786469,
0.07793579995632172,
0.11668910086154938,
-0.01928015425801277,
-0.013295556418597698,
0.0326867513358593,
-0.07467488944530487,
-0.06516359746456146,
0.03621525317430496,
0.05059470608830452,
-0.02368183620274067,
0.014129727147519588,
-0.06035906821489334,
-0.07768834382295609,
-0.020223526284098625,
-0.020624568685889244,
0.03534484654664993,
0.01448466069996357,
0.048016421496868134,
0.002421439392492175,
0.021879175677895546,
-0.009038131684064865,
-0.2114131897687912,
-0.015289990231394768,
0.13684536516666412,
-0.025825602933764458,
0.0772772952914238,
0.02491602674126625,
0.030421823263168335,
-0.012946748174726963,
-0.04669252783060074,
0.030940940603613853,
0.05767973139882088,
-0.10715098679065704,
-0.16401562094688416,
-0.1087762862443924,
0.06142280995845795,
0.047186724841594696,
0.039241887629032135,
0.0004906340036541224,
0.13691818714141846,
-0.10124339908361435,
0.09535585343837738,
0.08070199936628342,
-0.21171218156814575,
-0.025020942091941833,
0.07800641655921936,
0.006335252895951271,
0.05848000571131706,
-0.0909547433257103,
-0.1135283038020134,
0.009227504953742027,
0.04151655361056328,
-0.04705284163355827,
-0.004852612968534231,
-0.09356983751058578,
-0.007076938636600971,
-0.10067839175462723,
-0.05249352380633354,
0.04857681319117546,
0.007519593462347984,
-0.03366744890809059,
-0.07570701837539673,
-0.06144262105226517,
-0.2558034658432007,
0.04231719672679901,
0.002734551904723048,
-0.028564920648932457,
0.027280554175376892,
0.06006591394543648,
-0.0024982865434139967,
0.009528852067887783,
-0.05089294910430908,
-0.0060735950246453285,
0.0018692552112042904,
0.04344673827290535,
0.02192070707678795,
0.049816492944955826,
0.09345253556966782,
-0.0453154556453228,
-0.07863765209913254,
-0.07971593737602234,
0.001568864332512021,
-0.09834467619657516,
-0.0029336155857890844,
-0.01065158098936081,
0.11792746931314468,
0.07839620858430862,
0.188096284866333,
-0.09672267735004425,
0.15090839564800262,
-0.06743093580007553,
0.02127051167190075,
-0.0292173121124506,
0.04198670759797096,
-0.10697225481271744,
0.06766195595264435,
0.0042987423948943615,
0.1216699555516243,
0.0012262582313269377,
-0.04434427618980408,
-0.05408566817641258,
0.028299866244196892,
0.092783622443676,
0.03689787536859512,
-0.003033056855201721,
0.006281804293394089,
-0.11512966454029083,
-0.04075327143073082,
0.08012592792510986,
-0.11674041301012039,
0.03880445286631584,
0.08222387731075287,
-0.05685215815901756,
0.025436226278543472,
0.14008234441280365,
-0.05271923169493675,
-0.07590330392122269,
-0.023076603189110756,
-0.05224832519888878,
-0.0010203515412285924,
-0.06882081180810928,
-0.09820910543203354,
0.06587186455726624,
-0.07931461185216904,
-0.046767547726631165,
-0.01069442555308342,
-0.06022122502326965,
-0.02508947253227234,
0.0313897542655468,
-0.11425339430570602,
0.027369065210223198,
-0.06352906674146652,
-0.1490868180990219,
0.0025405967608094215,
0.033296309411525726,
0.05157281830906868,
-0.020073331892490387,
0.07143820077180862,
0.029817014932632446,
0.07118826359510422,
0.01444992609322071,
-0.003866268554702401,
0.014872555620968342,
0.09293179214000702,
-0.01929308846592903,
0.1468234658241272,
-0.11107984930276871,
-0.03793967515230179,
-0.08528759330511093,
-0.047046512365341187,
-0.015438864007592201,
-0.070037342607975,
0.0936816930770874,
0.10369876772165298,
-0.132637158036232,
-0.0011324608931317925,
0.07727614045143127,
0.004543130751699209,
-0.06151086091995239,
0.07226448506116867,
-0.03249401971697807,
0.03683622181415558,
-0.03398897871375084,
0.019484831020236015,
0.23877647519111633,
-0.13734649121761322,
-0.02292446419596672,
0.04653181880712509,
0.011145529337227345,
0.06785622984170914,
0.03862996771931648,
0.024435654282569885,
-0.0060175321996212006,
0.029976502060890198,
0.06939858198165894,
0.014767336659133434,
-0.035081956535577774,
-0.07516693323850632,
-0.03508396074175835,
-0.02231883443892002,
0.0675942450761795,
-0.0018072932725772262,
-0.028645092621445656,
-0.037522077560424805,
-0.13036759197711945,
0.0665295273065567,
0.12118694931268692,
-0.02594457007944584,
0.004242200870066881,
-0.12607721984386444,
0.02092490904033184,
-0.014229651540517807,
0.030899064615368843,
-0.12204796075820923,
-0.09059721976518631,
0.05428699776530266,
-0.12491586804389954,
0.0007295737159438431,
0.013865610584616661,
0.06539443880319595,
0.05852866172790527,
-0.02183409221470356,
0.004099052865058184,
-0.0006791838677600026,
-0.006947668734937906,
-0.04885321110486984,
-0.14398550987243652,
-0.0194331593811512,
-0.0012875120155513287,
0.1868933141231537,
-0.1366422325372696,
0.03471427410840988,
0.09327246248722076,
0.11317159235477448,
-0.03341534733772278,
-0.06406194716691971,
-0.021987199783325195,
0.06070515140891075,
-0.019989199936389923,
-0.058132171630859375,
0.019393477588891983,
0.019990788772702217,
-0.04378644749522209,
-0.06764868646860123,
-0.15504370629787445,
-0.020604200661182404,
0.09163593500852585,
0.10274793207645416,
-0.09586118161678314,
0.012865126132965088,
-0.015401644632220268,
-0.07361713796854019,
0.08605325222015381,
-0.029585180804133415,
0.036068566143512726,
0.06573392450809479,
0.09972742199897766,
-0.05399274080991745,
-0.0802609920501709,
0.053354308009147644,
-0.004021387081593275,
-0.03778417780995369,
0.13458353281021118,
-0.03230060636997223,
-0.035020388662815094,
0.06121457368135452,
0.01969234272837639,
-0.08100579679012299,
0.07636470347642899,
0.0008064719149842858,
-0.03005336783826351,
-0.14334966242313385,
0.18215900659561157,
0.06998907029628754,
0.04396958276629448,
-0.06467653065919876,
0.14423328638076782,
0.009262749925255775,
0.003319529118016362,
0.04019692540168762,
-0.1412932276725769,
0.0435338094830513,
-0.016300830990076065,
-0.10291800647974014,
0.007322457619011402,
-0.024100538343191147,
0.04722561687231064,
0.04424714669585228,
0.012696080841124058,
0.0989522859454155,
0.0803755670785904,
-0.045051321387290955,
-0.09052298963069916,
0.1696874350309372,
-0.20487569272518158,
-0.1692933291196823,
-0.23724623024463654,
-0.06010160595178604,
-0.10864808410406113,
-0.06262307614088058,
-0.038171492516994476,
-0.06114901602268219,
-0.004925878252834082,
-0.07229171693325043,
-0.054168231785297394,
-0.02971033565700054,
-0.03804026544094086,
0.00809535477310419,
0.0506107322871685,
0.20288380980491638,
-0.10071706771850586,
0.0035261004231870174,
0.07398133724927902,
-0.04216891527175903,
0.04126870259642601,
0.04389156028628349,
-0.06176188588142395,
0.10831575840711594,
0.02801472321152687,
0.007066147867590189,
0.04583527520298958,
0.26344794034957886,
0.01218415331095457,
0.045077648013830185,
0.12640315294265747,
-0.02713198773562908,
0.11259017139673233,
0.08601365983486176,
0.03075942024588585,
-0.054031748324632645,
0.007260114885866642,
0.07225169986486435,
-0.047237928956747055,
-0.2073739618062973,
-0.024561390280723572,
-0.05593196675181389,
0.02895568497478962,
0.0697668120265007,
0.05509297177195549,
0.06000829488039017,
0.021161211654543877,
-0.014756705611944199,
0.05384201928973198,
0.024022644385695457,
0.05228016898036003,
0.15606452524662018,
0.007494597230106592,
0.08254518359899521,
-0.01857672445476055,
0.06482795625925064,
0.06054738909006119,
0.12018458545207977,
0.06620902568101883,
-0.09340140968561172,
0.06777191907167435,
0.06991378217935562,
0.2309103012084961,
-0.04231749475002289,
0.04044065251946449,
-0.039800919592380524,
0.02160136215388775,
0.04192579537630081,
-0.06852447241544724,
-0.02228674292564392,
0.045454464852809906,
0.04383779317140579,
0.055168379098176956,
-0.012960998341441154,
-0.03251416236162186,
0.061029840260744095,
0.1200735792517662,
0.1410863846540451,
-0.24584956467151642,
-0.08414670825004578,
0.002743758028373122,
0.07593008130788803,
-0.08577446639537811,
-0.03050752729177475,
0.12004736065864563,
-0.09073471277952194,
-0.022157106548547745,
-0.06047871708869934,
0.03776207193732262,
-0.05631180852651596,
-0.013464990071952343,
0.1272226870059967,
0.11868614703416824,
0.03128614276647568,
0.06826592981815338,
-0.1984795182943344,
0.0038924296386539936,
0.046479105949401855,
0.03796008229255676,
-0.032218072563409805,
0.08879438787698746,
-0.02092011459171772,
-0.14536234736442566,
0.06824905425310135,
0.00928464438766241,
0.04412304237484932,
-0.2643653154373169,
-0.08849768340587616,
-0.0640072152018547,
0.1121034324169159,
0.04323500022292137,
0.09194491058588028,
-0.002589261159300804,
0.001596001093275845,
0.038568366318941116,
0.008458205498754978,
-0.024496160447597504,
-0.1217641532421112,
0.08333363384008408,
0.05355434492230415,
-0.12689408659934998,
-0.036906708031892776,
-0.04864383116364479,
-0.025097327306866646,
0.15772239863872528,
-0.29099515080451965,
-0.058513104915618896,
-0.07699800282716751,
-0.017982114106416702,
0.1725522130727768,
-0.03925176337361336,
0.009992221370339394,
-0.05319467559456825,
0.042920563369989395,
-0.011611501686275005,
-0.10756897181272507,
0.05673615261912346,
-0.04581743851304054,
-0.18565620481967926,
-0.06305986642837524,
0.1664780080318451,
0.04615027457475662,
-0.02202915959060192,
-0.08338532596826553,
-0.0004406214866321534,
0.013568607158958912,
-0.12767167389392853,
0.04611111432313919,
0.09552299976348877,
0.023448487743735313,
0.06976861506700516,
-0.12352042645215988,
0.18236160278320312,
-0.04183650016784668,
0.0699080303311348,
-0.001069412799552083,
0.3645954728126526,
-0.07338644564151764,
0.09322954714298248,
0.006827531382441521,
-0.058739520609378815,
-0.1732669472694397,
-0.03291316330432892,
0.11240191757678986,
0.014537257142364979,
0.020160140469670296,
-0.17855104804039001,
0.05038849636912346,
0.11093419790267944,
0.0022051765117794275,
0.15247735381126404,
-0.3038061261177063,
-0.08589451014995575,
0.01703876256942749,
0.020371371880173683,
0.009032954461872578,
-0.07828237861394882,
-0.03694106638431549,
-0.015422027558088303,
-0.0966288298368454,
0.12022463977336884,
-0.038734883069992065,
0.09644187241792679,
-0.043278057128190994,
-0.0025255470536649227,
0.0362173467874527,
-0.04292185604572296,
0.1816140115261078,
-0.010584858246147633,
0.02507949247956276,
-0.02672077715396881,
-0.04981764405965805,
0.08599312603473663,
-0.11739728599786758,
0.008551524952054024,
-0.09161419421434402,
0.07779605686664581,
-0.11091221868991852,
0.02490350790321827,
-0.050743263214826584,
-0.005680577829480171,
-0.10309027135372162,
0.003839876502752304,
-0.05605006217956543,
0.08640586584806442,
0.05445937067270279,
-0.02806430496275425,
-0.03855513408780098,
0.04545958340167999,
0.0833352729678154,
0.4550657868385315,
-0.05735234171152115,
0.06363260746002197,
-0.045327093452215195,
0.04754792898893356,
-0.004855587612837553,
0.018096737563610077,
-0.10447416454553604,
0.05266965180635452,
0.12597908079624176,
0.004702036269009113,
0.10525665432214737,
0.07642999291419983,
-0.14633949100971222,
-0.03259757161140442,
0.04478450119495392,
-0.10463353991508484,
-0.06347131729125977,
0.0041935862973332405,
-0.04780656099319458,
-0.10986195504665375,
-0.05336480587720871,
0.13808315992355347,
0.02157653123140335,
0.029198190197348595,
0.07288564741611481,
0.0606040433049202,
-0.0743301510810852,
0.1521131843328476,
0.031176552176475525,
0.10884132981300354,
-0.06404849886894226,
0.10279126465320587,
0.08866999298334122,
0.018037403002381325,
0.05181301757693291,
0.08700704574584961,
-0.04864339902997017,
0.005802307277917862,
-0.021341852843761444,
-0.017194848507642746,
0.08401943743228912,
-0.006986494641751051,
-0.04401438310742378,
-0.07757842540740967,
0.06006269529461861,
0.08885763585567474,
0.008715443313121796,
0.10366754978895187,
-0.004168495535850525,
-0.003106062300503254,
-0.1058509424328804,
0.11083628982305527,
0.018781334161758423,
0.01452710386365652,
-0.10124165564775467,
0.10264647006988525,
-0.02520686201751232,
0.09393913298845291,
0.021950235590338707,
-0.02448919229209423,
-0.20880027115345,
-0.0182492695748806,
-0.06395450979471207,
0.028829028829932213,
0.005977282300591469,
0.002845623530447483,
0.02528047189116478,
0.05665646120905876,
-0.023120438680052757,
0.052402399480342865,
-0.03787895292043686,
-0.11073435842990875,
-0.011274397373199463,
0.04121885076165199,
-0.10681234300136566,
-0.060493480414152145,
0.04216187447309494,
-0.1458396017551422,
0.030974335968494415,
0.041512299329042435,
-0.010181422345340252,
0.0331222265958786,
0.0326271615922451,
-0.002988602500408888,
0.008626350201666355,
0.06356181204319,
0.01750139892101288,
-0.15342669188976288,
0.05047530308365822,
-0.060931529849767685,
-0.056330230087041855,
0.03606034442782402,
0.08900462836027145,
-0.07716859132051468,
-0.060004331171512604,
-0.1047162264585495,
-0.019210612401366234,
-0.053806040436029434,
0.06085917353630066,
0.10741352289915085,
0.04826906695961952,
0.07662852108478546,
-0.07413529604673386,
0.06135132908821106,
-0.20013539493083954,
-0.0925370454788208,
0.05073818191885948,
-0.02962915599346161,
0.03192107379436493,
-0.01585507206618786,
0.08665382117033005,
-0.04130597412586212,
0.09737052768468857,
-0.0911548063158989,
-0.06677492707967758,
-0.01236429437994957,
-0.14232079684734344,
-0.12473760545253754,
0.024350497871637344,
0.11719990521669388,
0.03798552602529526,
-0.028043707832694054,
-0.0360165499150753,
-0.021167738363146782,
-0.00012206986866658553,
0.021406708285212517,
0.039742305874824524,
0.10759122669696808,
-0.037854962050914764,
0.05906296521425247,
0.08181878924369812,
-0.12233954668045044,
0.06615211814641953,
0.3386395275592804,
-0.09216822683811188,
0.06938411295413971,
-0.1037583127617836,
0.055291227996349335,
0.004188590217381716,
-0.1578167825937271,
0.06562302261590958,
-0.03578029200434685,
-0.11739803850650787,
-0.11170708388090134,
-0.02782140113413334,
-0.06053473427891731,
-0.13573874533176422,
-0.011595813557505608,
-0.08603309839963913,
0.03705992177128792,
0.10971429944038391,
0.040956370532512665,
-0.00005238820085651241,
0.08674224466085434,
-0.08426427841186523,
0.015858959406614304,
-0.026554005220532417,
0.01661234349012375,
0.002373488387092948,
0.03551538661122322,
-0.05148151516914368,
0.13299763202667236,
0.04172953590750694,
0.09105037897825241,
0.0351269356906414,
0.12865841388702393,
0.061613038182258606,
-0.03649081289768219,
-0.08087516576051712,
0.034735057502985,
-0.00866816844791174,
-0.05051290616393089,
0.12854260206222534,
0.04262714460492134,
-0.033818889409303665,
-0.08166546374559402,
0.03717944025993347,
-0.05964770168066025,
-0.03232124447822571,
-0.1490011215209961,
0.21021918952465057,
-0.007090150378644466,
0.05684982240200043,
-0.005340301897376776,
-0.06582194566726685,
-0.10691657662391663,
0.09703747928142548,
0.08361448347568512,
-0.10655521601438522,
-0.027393540367484093,
0.11307748407125473,
-0.014765406958758831,
-0.020656434819102287,
0.11341767758131027,
0.07106324285268784,
0.03892473503947258,
0.015398411080241203,
-0.003652809653431177,
0.011173613369464874,
-0.005519521422684193,
-0.04978426545858383,
0.04659533500671387,
-0.035761214792728424,
0.05047976225614548,
-0.07985086739063263,
-0.039188452064991,
-0.017922507598996162,
-0.11590944230556488,
0.18546512722969055,
-0.14905193448066711,
-0.1380290687084198,
-0.04020044580101967,
-0.04887549951672554,
-0.09633182734251022,
0.023816585540771484,
-0.05823002755641937,
0.011653803288936615,
0.1834726333618164,
-0.06117546558380127,
0.002367545384913683,
-0.08051527291536331,
-0.04205644875764847,
-0.012783233076334,
0.14036932587623596,
-0.004026600159704685,
0.06782373785972595,
0.14765043556690216,
-0.026025420054793358,
-0.0996888130903244,
0.051616817712783813,
0.05496608838438988,
-0.13456571102142334,
-0.0713169053196907,
0.08952119946479797,
-0.024943146854639053,
0.10833890736103058,
0.03626222535967827,
-0.048532821238040924,
-0.012223937548696995,
-0.07644094526767731,
-0.015080156736075878,
-0.09043051302433014,
-0.08735810965299606,
-0.06977803260087967,
0.09255798906087875,
0.24587669968605042,
-0.045966483652591705,
0.01281331293284893,
-0.029883233830332756,
0.030277037993073463,
-0.03763169050216675,
0.09822291880846024,
-0.00890478864312172,
-0.14939691126346588,
0.1223236471414566,
-0.07789045572280884,
0.06981994956731796,
-0.24048568308353424,
-0.09463357925415039,
0.06369028240442276,
-0.03817105293273926,
-0.04082025960087776,
0.1577797383069992,
-0.039682578295469284,
0.05267170071601868,
-0.04048655182123184,
-0.18562555313110352,
-0.05257001146674156,
0.13252989947795868,
-0.02073676884174347,
-0.07391299307346344
] |
null | null | transformers |
# xLakeChat
xLakeChat is a merge of the following models
* [xDAN-AI/xDAN-L1-Chat-RL-v1](https://huggingface.co/xDAN-AI/xDAN-L1-Chat-RL-v1)
* [fhai50032/BeagleLake-7B-Toxic](https://huggingface.co/fhai50032/BeagleLake-7B-Toxic)
## 🧩 Configuration
```yaml
models:
- model: senseable/WestLake-7B-v2
# no params for base model
- model: xDAN-AI/xDAN-L1-Chat-RL-v1
parameters:
weight: 0.73
density: 0.64
- model: fhai50032/BeagleLake-7B-Toxic
parameters:
weight: 0.46
density: 0.55
merge_method: dare_ties
base_model: senseable/WestLake-7B-v2
parameters:
normalize: true
int8_mask: true
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "fhai50032/xLakeChat"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` | {"license": "apache-2.0", "tags": ["merge", "mergekit", "mistral", "xDAN-AI/xDAN-L1-Chat-RL-v1", "fhai50032/BeagleLake-7B-Toxic"], "base_model": ["xDAN-AI/xDAN-L1-Chat-RL-v1", "fhai50032/BeagleLake-7B-Toxic"]} | text-generation | fhai50032/xLakeChat | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"xDAN-AI/xDAN-L1-Chat-RL-v1",
"fhai50032/BeagleLake-7B-Toxic",
"base_model:xDAN-AI/xDAN-L1-Chat-RL-v1",
"base_model:fhai50032/BeagleLake-7B-Toxic",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T02:43:39+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #xDAN-AI/xDAN-L1-Chat-RL-v1 #fhai50032/BeagleLake-7B-Toxic #base_model-xDAN-AI/xDAN-L1-Chat-RL-v1 #base_model-fhai50032/BeagleLake-7B-Toxic #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# xLakeChat
xLakeChat is a merge of the following models
* xDAN-AI/xDAN-L1-Chat-RL-v1
* fhai50032/BeagleLake-7B-Toxic
## Configuration
## Usage
| [
"# xLakeChat\n\nxLakeChat is a merge of the following models \n* xDAN-AI/xDAN-L1-Chat-RL-v1\n* fhai50032/BeagleLake-7B-Toxic",
"## Configuration",
"## Usage"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit #xDAN-AI/xDAN-L1-Chat-RL-v1 #fhai50032/BeagleLake-7B-Toxic #base_model-xDAN-AI/xDAN-L1-Chat-RL-v1 #base_model-fhai50032/BeagleLake-7B-Toxic #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# xLakeChat\n\nxLakeChat is a merge of the following models \n* xDAN-AI/xDAN-L1-Chat-RL-v1\n* fhai50032/BeagleLake-7B-Toxic",
"## Configuration",
"## Usage"
] | [
138,
50,
4,
3
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit #xDAN-AI/xDAN-L1-Chat-RL-v1 #fhai50032/BeagleLake-7B-Toxic #base_model-xDAN-AI/xDAN-L1-Chat-RL-v1 #base_model-fhai50032/BeagleLake-7B-Toxic #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# xLakeChat\n\nxLakeChat is a merge of the following models \n* xDAN-AI/xDAN-L1-Chat-RL-v1\n* fhai50032/BeagleLake-7B-Toxic## Configuration## Usage"
] | [
-0.09689775109291077,
-0.032538462430238724,
-0.0031079337932169437,
0.007663783151656389,
0.03958526626229286,
0.02119937539100647,
0.22607192397117615,
0.10200609266757965,
0.12845967710018158,
0.02314930036664009,
0.044418301433324814,
0.1609904170036316,
0.009159840643405914,
0.21944266557693481,
-0.058539461344480515,
-0.12150108069181442,
0.09828421473503113,
0.015522059984505177,
-0.0904713049530983,
0.09201294928789139,
0.09702165424823761,
-0.0615616999566555,
0.11434703320264816,
-0.0027669123373925686,
-0.08204404264688492,
-0.010677180252969265,
0.05370844528079033,
-0.027091259136795998,
0.11393173784017563,
0.07275592535734177,
0.08765895664691925,
0.07602640986442566,
-0.037158235907554626,
-0.13361628353595734,
0.04915526881814003,
0.013233440928161144,
-0.046299174427986145,
0.050200700759887695,
0.024335209280252457,
-0.10802251845598221,
0.04071316868066788,
-0.004895653109997511,
0.013788357377052307,
0.08897358924150467,
-0.07039724290370941,
-0.18005898594856262,
-0.08687193691730499,
0.0874558836221695,
0.10502567887306213,
0.04976052790880203,
-0.018837090581655502,
0.1492837518453598,
0.0363747775554657,
0.14505356550216675,
0.26076656579971313,
-0.3231922388076782,
-0.014507328160107136,
0.11736293137073517,
0.08394667506217957,
0.04197831079363823,
-0.030932852998375893,
0.0674016997218132,
0.04773150756955147,
-0.022174615412950516,
0.030830688774585724,
-0.06104735657572746,
0.15086565911769867,
-0.06619405746459961,
-0.10688550025224686,
0.03044789284467697,
0.16897529363632202,
0.029936833307147026,
-0.06934411078691483,
-0.04133184626698494,
-0.10646028816699982,
-0.03773347660899162,
-0.05886169150471687,
-0.07138001918792725,
0.005608237814158201,
-0.018564719706773758,
0.017779750749468803,
-0.03080010786652565,
-0.03682612255215645,
-0.06264694035053253,
-0.039857760071754456,
0.21861085295677185,
0.016236431896686554,
0.03656049445271492,
-0.08837413042783737,
0.019155073910951614,
-0.0013858731836080551,
-0.10652311891317368,
-0.027876116335392,
-0.0495351143181324,
-0.04829689487814903,
0.04286940023303032,
-0.007242811378091574,
-0.11652463674545288,
0.11478108912706375,
0.19557447731494904,
-0.09251005202531815,
0.04991241917014122,
-0.03911629691720009,
0.0386488251388073,
-0.04390569403767586,
0.05360150709748268,
-0.014660323970019817,
-0.12358478456735611,
0.047805458307266235,
0.05408649146556854,
0.08058445155620575,
-0.014630547724664211,
-0.091705322265625,
0.008851093240082264,
0.010064440779387951,
0.03940671309828758,
0.030132340267300606,
0.10920331627130508,
-0.08595149964094162,
-0.02770840749144554,
0.14014877378940582,
-0.07013864070177078,
0.007891676388680935,
0.0278308242559433,
-0.014969782903790474,
0.06272262334823608,
0.09850886464118958,
0.013759712688624859,
0.04447052627801895,
-0.008624721318483353,
-0.06172766163945198,
-0.01927514560520649,
-0.05722568929195404,
-0.12240118533372879,
-0.005005843471735716,
0.006316826678812504,
-0.03398968651890755,
-0.14593930542469025,
-0.15021516382694244,
0.01979096792638302,
0.027358736842870712,
0.002293987898156047,
-0.008979644626379013,
-0.055556073784828186,
-0.02578727714717388,
-0.013816135004162788,
0.02239682525396347,
-0.14700111746788025,
0.0005242047482170165,
0.021209532395005226,
0.02483372576534748,
0.11667557060718536,
-0.13326865434646606,
0.01675616391003132,
-0.07527187466621399,
0.08079984039068222,
-0.20672909915447235,
0.09039337933063507,
-0.0791449099779129,
0.11765562742948532,
-0.07467928528785706,
0.03410765156149864,
-0.01619841158390045,
0.014132031239569187,
-0.008681007660925388,
0.14703069627285004,
-0.1547728180885315,
-0.10858774185180664,
0.19143883883953094,
-0.20760689675807953,
-0.18795470893383026,
0.09144594520330429,
0.025158628821372986,
0.02440614439547062,
0.10511904954910278,
0.1374659538269043,
0.10898321866989136,
-0.08477338403463364,
-0.0728541761636734,
-0.000022730017008143477,
-0.038238056004047394,
0.009879833087325096,
0.06598351150751114,
0.0028009130619466305,
-0.14738740026950836,
0.04025348275899887,
-0.06309937685728073,
0.09550941735506058,
-0.027970120310783386,
-0.07176069170236588,
-0.05195607617497444,
-0.07637093961238861,
0.13437844812870026,
-0.056665997952222824,
0.03036786988377571,
-0.07276274263858795,
-0.08973132073879242,
0.007418188266456127,
0.11189086735248566,
-0.041181109845638275,
-0.001150108757428825,
-0.14044292271137238,
0.12494979798793793,
-0.028856540098786354,
0.05874355882406235,
-0.09464287757873535,
-0.13033989071846008,
0.029088344424962997,
-0.04747534170746803,
-0.012733304873108864,
0.009970629587769508,
0.0851944088935852,
0.04555675759911537,
-0.005412338301539421,
-0.0654640793800354,
0.10251779854297638,
0.014220906421542168,
-0.022731613367795944,
-0.19503355026245117,
-0.018664615228772163,
-0.08473915606737137,
0.2132226973772049,
-0.11349908262491226,
0.08862397074699402,
0.03932245075702667,
0.10084977746009827,
0.01976078376173973,
0.019652610644698143,
0.026432698592543602,
-0.023945918306708336,
-0.06344543397426605,
0.005472772289067507,
0.05950929597020149,
-0.026195509359240532,
-0.17497508227825165,
0.10883300006389618,
-0.10697197169065475,
0.20498992502689362,
0.1427161991596222,
0.04061419144272804,
-0.01153124962002039,
0.005569410510361195,
-0.010855233296751976,
-0.03476757928729057,
0.06309111416339874,
-0.0796905979514122,
0.041248004883527756,
0.026441432535648346,
0.10636606812477112,
-0.07161890715360641,
-0.004423721693456173,
0.021705565974116325,
-0.035231560468673706,
-0.03963758051395416,
0.08080770820379257,
-0.12055351585149765,
-0.08539137989282608,
0.09811405092477798,
0.203647181391716,
0.03917989879846573,
0.07045507431030273,
0.019991569221019745,
0.03994647040963173,
-0.06988698244094849,
0.043362028896808624,
0.017365170642733574,
0.0656462162733078,
-0.08345644921064377,
0.02865840122103691,
0.02667381800711155,
-0.029304731637239456,
0.01316714845597744,
-0.08463945984840393,
0.002527607837691903,
0.005647036712616682,
-0.06755141913890839,
0.0345899723470211,
0.08184925466775894,
-0.007589481770992279,
0.0723077729344368,
-0.01822653040289879,
-0.05287224054336548,
0.042681723833084106,
0.0015275743789970875,
-0.09811761230230331,
0.18319082260131836,
-0.14674142003059387,
-0.2887325584888458,
-0.08285247534513474,
-0.05271691456437111,
-0.07535526156425476,
-0.016173269599676132,
0.06926123052835464,
-0.13120681047439575,
-0.03694022446870804,
-0.07033426314592361,
0.1173197403550148,
0.05799409747123718,
0.04521189630031586,
0.04871077463030815,
-0.018292857334017754,
0.055647313594818115,
-0.11791139841079712,
-0.02252800017595291,
0.004832011181861162,
-0.09346438944339752,
0.07274701446294785,
-0.08072725683450699,
0.08422703295946121,
0.11471585184335709,
-0.015968525782227516,
0.018574917688965797,
-0.01762552559375763,
0.17637580633163452,
-0.0425645187497139,
0.07579821348190308,
0.14061562716960907,
-0.03771001845598221,
0.06693485379219055,
0.1391221433877945,
0.006912140641361475,
-0.04642185941338539,
-0.012791193090379238,
-0.005769437178969383,
-0.049648452550172806,
-0.2112307995557785,
-0.08490386605262756,
-0.004795377142727375,
0.11066731810569763,
-0.003600944532081485,
0.07518690824508667,
0.11253120750188828,
0.09927161037921906,
-0.04771518334746361,
-0.0207822248339653,
0.03585178405046463,
0.0502142496407032,
0.06236056983470917,
-0.03274722769856453,
0.11640456318855286,
-0.04997444152832031,
0.0035821967758238316,
0.03551788628101349,
0.048222873359918594,
0.10804617404937744,
0.0729956328868866,
0.12560416758060455,
0.08564682304859161,
0.13366296887397766,
0.08453640341758728,
0.05074639990925789,
-0.05792177841067314,
-0.05042843148112297,
-0.00881968718022108,
-0.09841345995664597,
-0.013575850054621696,
0.043333105742931366,
-0.12736696004867554,
0.12248779088258743,
-0.03107989765703678,
0.10522215813398361,
0.11596300452947617,
0.12383568286895752,
0.028157686814665794,
-0.2582683563232422,
-0.086419478058815,
0.05516397953033447,
0.06526850163936615,
0.024382155388593674,
0.02611004374921322,
0.053646333515644073,
-0.052449654787778854,
0.1321239322423935,
-0.07247819751501083,
0.056753505021333694,
0.011456264182925224,
0.03299297019839287,
-0.007549886591732502,
0.05887046083807945,
-0.007206722162663937,
0.008979232981801033,
-0.24424980580806732,
0.15668216347694397,
0.02468169666826725,
-0.011937536299228668,
0.02482495829463005,
0.03334350511431694,
0.042753417044878006,
0.20321156084537506,
0.10664411634206772,
0.010446755215525627,
-0.08193542808294296,
-0.09342221915721893,
-0.08946508914232254,
0.028178691864013672,
0.0052639576606452465,
-0.03207160159945488,
0.06721380352973938,
-0.04003625363111496,
-0.0687633827328682,
0.011905832216143608,
0.09392000734806061,
-0.1550915688276291,
-0.09620889276266098,
0.03594648465514183,
0.09889458119869232,
0.07015563547611237,
-0.10113867372274399,
-0.04647810384631157,
-0.05552610754966736,
0.16415981948375702,
-0.10816817730665207,
-0.08992081135511398,
-0.08879537135362625,
-0.03459624946117401,
0.05509309098124504,
-0.10082386434078217,
0.03547646850347519,
-0.0479581281542778,
0.0839458554983139,
-0.08264589309692383,
-0.151703342795372,
0.08157511055469513,
-0.12319718301296234,
-0.09732884913682938,
-0.04709253087639809,
0.13689781725406647,
-0.008890890516340733,
0.04080739989876747,
0.028155922889709473,
-0.03294450789690018,
0.0025742030702531338,
-0.06362883746623993,
0.009988777339458466,
0.08189107477664948,
-0.12382693588733673,
0.07691618800163269,
-0.09143923223018646,
-0.21884384751319885,
-0.0849875658750534,
0.007490432821214199,
0.09724773466587067,
0.2694871723651886,
-0.06611206382513046,
0.09153944998979568,
0.16253407299518585,
-0.05409107729792595,
-0.15359234809875488,
-0.03713226690888405,
-0.04760367050766945,
-0.003632873762398958,
0.03333849087357521,
-0.10001543164253235,
0.08044751733541489,
0.09138680249452591,
-0.035738106817007065,
0.08702646195888519,
-0.29693636298179626,
-0.10606596618890762,
0.1408790946006775,
0.0924118384718895,
0.24313215911388397,
-0.18631745874881744,
-0.09589948505163193,
-0.06816539168357849,
-0.10243012756109238,
0.08518259972333908,
-0.10859063267707825,
0.02525467239320278,
-0.013495233841240406,
-0.0032321326434612274,
0.02255946770310402,
-0.012136721052229404,
0.074269138276577,
0.004634612239897251,
0.06349387764930725,
-0.06223268806934357,
-0.12488818913698196,
0.11067213118076324,
-0.020212184637784958,
0.09501752257347107,
-0.17054235935211182,
0.03289184346795082,
0.020682182163000107,
0.011825431138277054,
-0.053990066051483154,
0.07400745898485184,
-0.04490179568529129,
-0.059314027428627014,
-0.06832101196050644,
0.029841752722859383,
-0.009595389477908611,
0.027494238689541817,
0.16370759904384613,
-0.006525570992380381,
0.1575758010149002,
0.12029965966939926,
0.045728616416454315,
-0.10866236686706543,
-0.041414275765419006,
0.007938462309539318,
-0.04342176765203476,
0.07584664225578308,
-0.09474585205316544,
0.015088774263858795,
0.05738315358757973,
-0.012245677411556244,
0.09736252576112747,
0.039578139781951904,
-0.055218301713466644,
0.02914920262992382,
0.10069157183170319,
-0.14899425208568573,
-0.22856420278549194,
-0.021513113752007484,
0.028605487197637558,
0.0065085566602647305,
0.14151723682880402,
0.20282702147960663,
-0.038022562861442566,
0.005370707716792822,
-0.01821497268974781,
0.01818087138235569,
-0.04487410932779312,
0.09228627383708954,
0.0006533510750159621,
0.06487146019935608,
-0.11774337291717529,
0.00348445912823081,
0.029908737167716026,
-0.05931340903043747,
-0.0076088858768343925,
0.08786600083112717,
-0.12093198299407959,
-0.07799642533063889,
-0.08188731968402863,
0.1884985715150833,
-0.04822366684675217,
-0.03991023078560829,
-0.1409122794866562,
-0.1442149579524994,
-0.01636209711432457,
0.16152599453926086,
0.06037091463804245,
0.0731712132692337,
0.06300637871026993,
-0.04079751670360565,
-0.019007829949259758,
0.08625128120183945,
-0.04823784902691841,
0.062159691005945206,
-0.17061924934387207,
0.06043875962495804,
0.02405203878879547,
0.05946803838014603,
-0.03522705286741257,
-0.01893071085214615,
-0.16181813180446625,
-0.039428289979696274,
-0.13688239455223083,
0.01446415577083826,
-0.10369550436735153,
-0.04371672123670578,
-0.022025611251592636,
-0.030305763706564903,
-0.006899852771311998,
0.026472395285964012,
-0.037953734397888184,
-0.021102527156472206,
0.041241925209760666,
0.041246142238378525,
-0.11188488453626633,
-0.017522187903523445,
0.012792717665433884,
-0.03807628154754639,
0.07741441577672958,
0.07774749398231506,
-0.02163725160062313,
-0.005009396933019161,
-0.2148818075656891,
-0.011043337173759937,
0.06548001617193222,
-0.006994308438152075,
0.060874033719301224,
-0.09236694127321243,
-0.014206431806087494,
0.002855303231626749,
-0.01501662191003561,
0.013325956650078297,
0.11247216165065765,
-0.08535755425691605,
0.04175780713558197,
-0.036569155752658844,
-0.01876789703965187,
-0.048498447984457016,
-0.02852502465248108,
0.0682702362537384,
-0.0034074527211487293,
0.14491234719753265,
-0.08248915523290634,
0.05042870342731476,
-0.16915570199489594,
-0.00881318561732769,
0.0004533593892119825,
-0.1447926163673401,
-0.09459702670574188,
-0.03756866231560707,
-0.01750204525887966,
-0.006420107092708349,
0.07673157006502151,
-0.037297818809747696,
-0.07532597333192825,
0.026956932619214058,
-0.05624868720769882,
0.023748962208628654,
0.006989171262830496,
0.14345116913318634,
0.03646430745720863,
0.017773104831576347,
-0.025626683607697487,
0.03404286131262779,
0.030177226290106773,
-0.05304935202002525,
0.06977967917919159,
0.09033026546239853,
0.002080240286886692,
0.09525405615568161,
0.11507976800203323,
-0.007807473186403513,
-0.09109791368246078,
-0.05786523222923279,
-0.10235783457756042,
0.03594795987010002,
-0.00418818136677146,
0.16644488275051117,
0.19470414519309998,
-0.0895572230219841,
0.06931168586015701,
0.031114064157009125,
-0.014534459449350834,
-0.11579680442810059,
-0.08255209028720856,
-0.1032133623957634,
-0.1993502527475357,
-0.03334784507751465,
-0.08302217721939087,
-0.07402674108743668,
-0.0174445491284132,
-0.0028183613903820515,
0.00592784583568573,
0.17914935946464539,
-0.01447001937776804,
-0.004853785503655672,
0.0014777100877836347,
-0.0036942046135663986,
-0.06765831261873245,
0.016706090420484543,
-0.018590068444609642,
0.025863153859972954,
-0.010062736459076405,
-0.047409940510988235,
0.026177676394581795,
-0.006132106296718121,
0.0855397880077362,
-0.03335443511605263,
-0.11698415130376816,
-0.021673088893294334,
0.01227516308426857,
0.053250569850206375,
0.03572605922818184,
0.04564321041107178,
-0.058569177985191345,
-0.014230390079319477,
0.10061434656381607,
-0.01268676295876503,
-0.0346858985722065,
-0.06259091943502426,
0.07386203855276108,
-0.051919125020504,
0.05537126213312149,
-0.02674318104982376,
-0.028416873887181282,
-0.035061538219451904,
0.17567883431911469,
0.2838619649410248,
-0.008110745809972286,
0.03152972459793091,
-0.0564480721950531,
0.00873705092817545,
-0.03424205258488655,
0.04985639452934265,
0.05056764930486679,
0.2323620617389679,
-0.013298901729285717,
0.04807387664914131,
-0.007381313014775515,
-0.04907642677426338,
-0.08143377304077148,
-0.031848687678575516,
-0.006647428032010794,
0.03139976039528847,
0.013036109507083893,
0.08221625536680222,
-0.024813063442707062,
-0.04245394468307495,
0.004869712516665459,
-0.15611706674098969,
-0.06393211334943771,
-0.08853195607662201,
0.1170654296875,
0.030245449393987656,
0.07847785204648972,
-0.032928287982940674,
-0.04374438524246216,
0.13415133953094482,
-0.043111298233270645,
-0.13202111423015594,
-0.09073974192142487,
0.05769254267215729,
-0.10927285999059677,
0.13514657318592072,
-0.008836992084980011,
0.01440939400345087,
0.10634353756904602,
-0.04644657298922539,
-0.11092471331357956,
0.044508326798677444,
-0.01894272118806839,
-0.06151667237281799,
0.003765932284295559,
0.03903378173708916,
-0.007286283653229475,
0.175151988863945,
0.06243780255317688,
-0.08727771043777466,
0.054377105087041855,
0.047523289918899536,
-0.08322697132825851,
-0.040147971361875534,
0.049412548542022705,
-0.04831080511212349,
0.1042882427573204,
0.1533413529396057,
-0.04731065034866333,
-0.005064044613391161,
-0.004531262908130884,
0.040239088237285614,
0.07743758708238602,
0.05178647115826607,
-0.021204210817813873,
-0.18223097920417786,
0.0029625629540532827,
0.060815270990133286,
0.00496510649099946,
-0.28919854760169983,
-0.10726289451122284,
-0.1251872479915619,
-0.0011419248767197132,
-0.0903291180729866,
0.02384512685239315,
0.17230527102947235,
0.06821034848690033,
0.00428090151399374,
-0.1281050741672516,
-0.01497148908674717,
0.11548826843500137,
-0.08065829426050186,
-0.1068766787648201
] |
null | null | null |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
``` | {"license": "other", "tags": ["autotrain", "text-generation"], "widget": [{"text": "I love AutoTrain because "}]} | text-generation | InnerI/NousResearch-Llama2-chat | [
"tensorboard",
"safetensors",
"autotrain",
"text-generation",
"conversational",
"license:other",
"endpoints_compatible",
"region:us"
] | 2024-02-11T02:46:32+00:00 | [] | [] | TAGS
#tensorboard #safetensors #autotrain #text-generation #conversational #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
| [
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
"TAGS\n#tensorboard #safetensors #autotrain #text-generation #conversational #license-other #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
41,
29,
3
] | [
"passage: TAGS\n#tensorboard #safetensors #autotrain #text-generation #conversational #license-other #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.# Usage"
] | [
-0.027139926329255104,
0.05549413338303566,
-0.001086072763428092,
0.0458357073366642,
0.11233107000589371,
-0.03919310122728348,
0.25330719351768494,
0.05724795535206795,
-0.03235183656215668,
-0.07674083113670349,
0.18840105831623077,
0.18488869071006775,
-0.03171338140964508,
0.14625823497772217,
-0.03068830817937851,
-0.2556142807006836,
0.014358164742588997,
0.0045296261087059975,
0.09734679758548737,
0.10690443962812424,
0.13996313512325287,
-0.08409817516803741,
0.04779442772269249,
0.05504542589187622,
-0.21212154626846313,
0.03396059572696686,
0.07364731281995773,
-0.10847485810518265,
0.1812181919813156,
0.05314876511693001,
0.13394244015216827,
0.03942825272679329,
0.11810304969549179,
-0.10978661477565765,
0.027138201519846916,
0.02522261068224907,
-0.028195848688483238,
0.07583968341350555,
0.07542945444583893,
-0.032452408224344254,
0.0983496606349945,
0.17407329380512238,
0.1203153133392334,
0.04488663002848625,
-0.09238871932029724,
0.02062407322227955,
-0.012019496411085129,
0.01698697917163372,
0.1256086677312851,
0.10495282709598541,
-0.0233027134090662,
0.21972255408763885,
-0.12350398302078247,
0.09147249907255173,
-0.10042452067136765,
-0.2998514175415039,
-0.02898949384689331,
0.23076921701431274,
0.0885743498802185,
0.000009943089935404714,
-0.13909539580345154,
0.0714062973856926,
0.10903196036815643,
-0.008379057981073856,
0.06390078365802765,
-0.023791620507836342,
-0.04102479666471481,
-0.003995601553469896,
-0.09138286113739014,
0.03857232257723808,
0.16629371047019958,
-0.06115882471203804,
-0.0014376816106960177,
-0.14251862466335297,
-0.030591007322072983,
0.029780447483062744,
0.0014873158652335405,
-0.11689703911542892,
-0.027005087584257126,
0.09389875084161758,
-0.04272151365876198,
-0.06311851739883423,
-0.15389303863048553,
-0.0454421229660511,
-0.08688711374998093,
0.011851770803332329,
0.005009328946471214,
0.008037209510803223,
-0.11562680453062057,
0.08981089293956757,
0.009057710878551006,
-0.09574903547763824,
0.058846596628427505,
-0.08302060514688492,
0.004863778129220009,
-0.11868158727884293,
-0.01823366805911064,
-0.17185001075267792,
0.017361367121338844,
0.1743340939283371,
0.17856407165527344,
0.011556620709598064,
-0.08119673281908035,
0.05105486884713173,
0.027566175907850266,
0.10752616077661514,
0.03950304165482521,
-0.015383190475404263,
0.05597636103630066,
-0.033588800579309464,
-0.01045486144721508,
-0.043443288654088974,
-0.21071277558803558,
0.06327097117900848,
0.011061734519898891,
0.04313728213310242,
-0.0669732317328453,
0.0747966319322586,
-0.02011682465672493,
0.03054383210837841,
0.01818717271089554,
-0.02988259121775627,
0.049371398985385895,
-0.03925693407654762,
0.013712245039641857,
-0.0809786394238472,
0.032900117337703705,
0.10831229388713837,
0.026870984584093094,
0.09901712834835052,
-0.09215869009494781,
-0.021803077310323715,
-0.11723243445158005,
-0.058838676661252975,
0.01927344501018524,
-0.0007232280331663787,
0.04639449343085289,
-0.18217580020427704,
-0.24385316669940948,
-0.039855461567640305,
0.06950496137142181,
-0.03284268453717232,
-0.0660507082939148,
-0.08602586388587952,
0.010475946590304375,
0.05847384035587311,
-0.025249049067497253,
0.06053835526108742,
-0.006766340229660273,
0.02725645713508129,
-0.09177345037460327,
0.005915171932429075,
-0.06345934420824051,
0.0016364285256713629,
-0.10958781838417053,
-0.028317639604210854,
-0.023075606673955917,
0.019820749759674072,
-0.04484573379158974,
0.1346224695444107,
-0.015361327677965164,
0.05166352912783623,
-0.05846923962235451,
0.056585509330034256,
0.02016746811568737,
0.11968892812728882,
-0.16490231454372406,
-0.002552325837314129,
0.1652221381664276,
-0.10205310583114624,
-0.11537600308656693,
0.11744437366724014,
-0.10948594659566879,
0.23891519010066986,
0.09570688754320145,
0.15996620059013367,
0.029400693252682686,
-0.12259995192289352,
0.11311465501785278,
0.044385701417922974,
-0.08553649485111237,
-0.04975805804133415,
-0.01613697037100792,
-0.0187750943005085,
-0.15317568182945251,
0.013573155738413334,
0.14734122157096863,
0.07551421970129013,
-0.029119504615664482,
-0.08670662343502045,
-0.012989569455385208,
-0.05794382840394974,
0.04643617570400238,
0.02886943705379963,
0.13005796074867249,
-0.06525770574808121,
-0.0426858626306057,
0.0716388151049614,
0.03417434170842171,
0.04155395179986954,
-0.051185354590415955,
-0.08899204432964325,
-0.017478253692388535,
-0.04541110619902611,
-0.010380160994827747,
-0.08366479724645615,
-0.0700906440615654,
-0.022523561492562294,
0.11905723065137863,
0.04952830821275711,
0.1251334697008133,
0.049467846751213074,
0.027002273127436638,
-0.02090955153107643,
0.03143099695444107,
0.17509233951568604,
0.044941626489162445,
-0.13911008834838867,
-0.12228391319513321,
0.11367963999509811,
-0.08558206260204315,
0.12818413972854614,
-0.27459999918937683,
0.03262881562113762,
-0.08165117353200912,
0.09496741741895676,
0.0027740169316530228,
0.05194971710443497,
-0.0684652030467987,
0.01999986171722412,
-0.0958189070224762,
-0.01624615490436554,
0.07022757828235626,
0.06327712535858154,
-0.05662659928202629,
0.14026139676570892,
-0.17570924758911133,
0.19565783441066742,
0.11632779240608215,
-0.11043189465999603,
-0.10105086863040924,
-0.08642042428255081,
0.0036167094949632883,
-0.012462062761187553,
-0.09999484568834305,
0.0058722663670778275,
0.12042854726314545,
-0.03889302536845207,
0.17995381355285645,
-0.02769639901816845,
-0.03988126292824745,
-0.011288275942206383,
-0.0866771936416626,
-0.014757689088582993,
0.0010102991946041584,
0.11456076800823212,
-0.21932855248451233,
0.13577896356582642,
0.11419139057397842,
-0.051889847964048386,
0.22218789160251617,
0.025907613337039948,
0.024796508252620697,
-0.006247390992939472,
-0.028414150699973106,
0.009269235655665398,
0.05920398235321045,
-0.07477575540542603,
-0.027919800952076912,
0.003957283683121204,
-0.0092135826125741,
0.036593832075595856,
-0.14668212831020355,
-0.03666090592741966,
0.012492007575929165,
0.054741308093070984,
0.05988682061433792,
0.059844184666872025,
-0.09232781827449799,
0.07059172540903091,
-0.04286655783653259,
-0.13985447585582733,
0.1107911691069603,
0.0060933795757591724,
-0.12343225628137589,
0.1803586333990097,
-0.07787143439054489,
-0.19732743501663208,
-0.16621485352516174,
-0.11972853541374207,
0.014468242414295673,
0.07504851371049881,
0.04481320083141327,
-0.05905783176422119,
-0.05832948908209801,
-0.01938783936202526,
-0.13421949744224548,
0.0015642110956832767,
-0.025473810732364655,
-0.09767882525920868,
0.05334441736340523,
-0.009880103170871735,
-0.11362743377685547,
-0.033706214278936386,
-0.011477314867079258,
-0.06063736230134964,
0.04996487870812416,
-0.03063584864139557,
0.05468389019370079,
0.16709968447685242,
-0.014212493784725666,
0.026945235207676888,
-0.04314466938376427,
0.13374222815036774,
-0.09364467114210129,
0.027101639658212662,
0.07683544605970383,
-0.05926739051938057,
0.0322793610394001,
0.20565038919448853,
0.03931461274623871,
-0.06251461803913116,
0.05211615934967995,
-0.01300883013755083,
-0.07548793405294418,
-0.20642392337322235,
-0.08616714179515839,
-0.018872160464525223,
-0.004724911414086819,
0.0740182176232338,
0.06067976355552673,
0.27492231130599976,
0.13033071160316467,
0.08231183141469955,
0.0327739454805851,
0.031089577823877335,
0.07130683213472366,
0.10141957551240921,
-0.045351143926382065,
0.17327657341957092,
-0.07304312288761139,
-0.15891112387180328,
0.03544701635837555,
0.005132387857884169,
0.06854364275932312,
0.16671641170978546,
0.007023849990218878,
0.048709530383348465,
0.10315679013729095,
0.12708161771297455,
0.09641235321760178,
0.054253000766038895,
-0.07218553125858307,
-0.0012286589480936527,
-0.005305302795022726,
-0.026303669437766075,
0.1362561583518982,
-0.00046331988414749503,
-0.06845024228096008,
0.004173303488641977,
0.035755008459091187,
0.04544354975223541,
0.06030682846903801,
0.02706083655357361,
-0.2688038945198059,
0.03317579999566078,
0.03258064389228821,
-0.05240030959248543,
-0.10697153955698013,
0.08676817268133163,
0.03545473515987396,
-0.15415973961353302,
0.009957630187273026,
-0.05253329873085022,
0.07863115519285202,
0.011545667424798012,
0.04271426796913147,
-0.07402849197387695,
-0.04174455255270004,
-0.04944342002272606,
0.14203289151191711,
-0.36370033025741577,
0.21619655191898346,
-0.006830292288213968,
0.07295355945825577,
-0.11626013368368149,
0.008941524662077427,
0.08032336086034775,
0.13351061940193176,
0.1214267686009407,
-0.057370346039533615,
-0.15501785278320312,
-0.061875052750110626,
-0.10546572506427765,
-0.017368091270327568,
0.011643516831099987,
0.011438592337071896,
-0.015686411410570145,
-0.09938836097717285,
-0.0007191341137513518,
0.05575770139694214,
-0.031139280647039413,
-0.14712563157081604,
-0.17559047043323517,
-0.013708721846342087,
0.053798891603946686,
0.01039790641516447,
-0.02297559380531311,
-0.07223079353570938,
-0.07598548382520676,
0.18843905627727509,
0.017605016008019447,
0.010744013823568821,
-0.1267765909433365,
-0.0211129579693079,
-0.07204801589250565,
-0.023109255358576775,
0.0591631755232811,
0.010498205199837685,
0.1408766806125641,
-0.0984286293387413,
-0.06850062310695648,
0.11168986558914185,
-0.11995355039834976,
-0.0296772550791502,
-0.13311097025871277,
0.039311543107032776,
-0.013930300250649452,
0.0019760821014642715,
0.11339738965034485,
0.034697309136390686,
-0.065993532538414,
-0.06231782212853432,
-0.010306917130947113,
-0.01983947865664959,
0.004338997416198254,
-0.1453656256198883,
-0.10612037032842636,
-0.11072193831205368,
-0.02665124088525772,
-0.10663683712482452,
0.21942123770713806,
0.12710125744342804,
-0.09963835775852203,
0.1507042944431305,
0.19085004925727844,
-0.10560127347707748,
-0.3029433488845825,
-0.03758569061756134,
-0.03614523634314537,
0.01042028795927763,
0.052465375512838364,
-0.10016904771327972,
0.10020822286605835,
-0.004682690836489201,
-0.09071888029575348,
-0.012875484302639961,
-0.1332244724035263,
-0.16934457421302795,
0.2425684779882431,
0.027740225195884705,
0.18792714178562164,
-0.08958053588867188,
-0.05931283161044121,
-0.08887685835361481,
0.07167080044746399,
0.07230978459119797,
-0.10829314589500427,
0.052640654146671295,
0.06571503728628159,
0.06849011033773422,
0.03001396730542183,
-0.046969201415777206,
0.04856084659695625,
-0.0685959905385971,
0.06622105091810226,
-0.16036126017570496,
-0.04903446137905121,
0.05513772740960121,
-0.027114855125546455,
0.08837562054395676,
-0.045733582228422165,
0.023816362023353577,
-0.049519676715135574,
-0.06783362478017807,
0.016798026859760284,
0.06947769224643707,
-0.010557430796325207,
-0.11664488166570663,
-0.0023799410555511713,
-0.0001851402485044673,
0.003798362798988819,
-0.056741535663604736,
0.06440608948469162,
-0.024307509884238243,
0.16197754442691803,
0.18213209509849548,
0.22810977697372437,
-0.06883032619953156,
0.035292305052280426,
-0.028084218502044678,
-0.11230967938899994,
0.0835658609867096,
-0.05905301868915558,
0.007088550366461277,
0.06093867868185043,
-0.04436035454273224,
0.15304213762283325,
0.06302426010370255,
-0.023623578250408173,
-0.014216885901987553,
0.14470265805721283,
-0.16506865620613098,
-0.01060457993298769,
-0.06767161190509796,
0.1326562762260437,
0.04198072478175163,
-0.009442887268960476,
0.11170413345098495,
-0.0699271634221077,
-0.015712426975369453,
0.028324346989393234,
0.0006050282390788198,
-0.02406279183924198,
0.06398393213748932,
0.05348778888583183,
0.0234637763351202,
-0.05472220480442047,
0.025176841765642166,
0.0722203329205513,
-0.03072275035083294,
0.06242464855313301,
0.007681041024625301,
-0.07700609415769577,
-0.10173168778419495,
0.03668944537639618,
0.2752801775932312,
-0.15260876715183258,
-0.09022942930459976,
-0.01293264701962471,
-0.09389843791723251,
-0.0022608607541769743,
0.11169756948947906,
0.07335275411605835,
0.029061542823910713,
-0.060580506920814514,
-0.01626879908144474,
-0.12279229611158371,
0.1050315797328949,
-0.01852598413825035,
0.04680366814136505,
-0.15155616402626038,
0.0745868980884552,
-0.017912980169057846,
-0.0077625419944524765,
-0.09016294777393341,
-0.021869845688343048,
-0.13424256443977356,
0.02158970944583416,
-0.07701745629310608,
-0.03308233991265297,
-0.0459207147359848,
-0.022100694477558136,
0.06900330632925034,
-0.007899959571659565,
-0.02777872420847416,
-0.02411218360066414,
-0.08961070328950882,
0.042163655161857605,
0.014423605985939503,
0.030176332220435143,
-0.044656362384557724,
-0.02405896596610546,
0.01923391781747341,
-0.004822327755391598,
0.05716795101761818,
-0.0010958941420540214,
-0.010174169205129147,
0.030106110498309135,
-0.16514046490192413,
0.038273196667432785,
0.06191452965140343,
0.011508648283779621,
0.02424795925617218,
-0.021737953647971153,
-0.0018561079632490873,
0.09054802358150482,
0.04585824906826019,
0.03687870502471924,
0.011025887914001942,
-0.0873480960726738,
0.048339005559682846,
0.06997828185558319,
-0.1324043571949005,
-0.036405570805072784,
-0.017806943506002426,
-0.017597384750843048,
-0.030787678435444832,
0.2054802030324936,
-0.11842762678861618,
0.04016297683119774,
-0.05013446509838104,
0.04507654905319214,
-0.03293733298778534,
-0.09565191715955734,
-0.05252337083220482,
-0.09204892069101334,
-0.02712174877524376,
-0.020230986177921295,
0.25583967566490173,
0.15121719241142273,
-0.0226773489266634,
0.04129955545067787,
0.04341581091284752,
0.0822424590587616,
0.007453450001776218,
0.18559139966964722,
0.06772497296333313,
-0.0013120286166667938,
-0.12615074217319489,
0.07755409926176071,
0.03751662001013756,
-0.05538594350218773,
0.014171074144542217,
-0.010532640852034092,
-0.1126057505607605,
0.07215515524148941,
0.07383084297180176,
-0.028012176975607872,
-0.0910046175122261,
-0.11854562908411026,
-0.12325716763734818,
0.038516566157341,
-0.09675229340791702,
0.03040294535458088,
0.18707814812660217,
-0.05968274176120758,
-0.018261119723320007,
-0.06825742870569229,
-0.06702327728271484,
-0.21684440970420837,
-0.19894014298915863,
-0.10148875415325165,
-0.06482657790184021,
0.04089851677417755,
-0.026273420080542564,
0.0364372655749321,
0.01442588772624731,
0.06449200958013535,
-0.062291957437992096,
0.0987730547785759,
-0.09214674681425095,
0.025841906666755676,
0.0011953203938901424,
-0.02887633629143238,
0.00903320498764515,
-0.2084316611289978,
-0.0007441829657182097,
-0.14608801901340485,
-0.0058806356973946095,
-0.02894151583313942,
-0.04418741911649704,
0.026549741625785828,
-0.001695065526291728,
-0.011429454199969769,
-0.01772264763712883,
-0.010636563412845135,
0.027661345899105072,
0.028542719781398773,
0.056926626712083817,
0.021746328100562096,
0.004735887981951237,
0.02130277082324028,
0.19689784944057465,
-0.03654266148805618,
-0.14267215132713318,
-0.1396569460630417,
0.19610263407230377,
-0.0006993417046032846,
0.10599878430366516,
-0.07313507795333862,
-0.013131856918334961,
0.06016526371240616,
0.32045072317123413,
0.27119672298431396,
-0.05262213200330734,
0.010116464458405972,
-0.017002223059535027,
-0.008013651706278324,
-0.028321655467152596,
0.16524869203567505,
-0.0001161322943517007,
0.19725893437862396,
-0.06469258666038513,
0.013387450948357582,
-0.014107211492955685,
-0.08006207644939423,
-0.06046360358595848,
0.12547224760055542,
-0.00986608024686575,
-0.003953396342694759,
-0.01878383383154869,
0.07922805100679398,
-0.07593490183353424,
0.11825694143772125,
-0.1079479455947876,
-0.05408896505832672,
-0.06810387969017029,
0.048589129000902176,
0.1347869485616684,
-0.03979865461587906,
0.04452402517199516,
-0.03259386122226715,
-0.015653783455491066,
0.013312606140971184,
-0.04531089961528778,
-0.09555462747812271,
0.006992687471210957,
0.06398781388998032,
-0.022717608138918877,
0.24616771936416626,
-0.02360832318663597,
0.05345937982201576,
0.09784020483493805,
0.0065172514878213406,
-0.0765647366642952,
0.09085403382778168,
0.0050888159312307835,
-0.053313564509153366,
0.1124519407749176,
0.0035579963587224483,
0.006471545435488224,
-0.015531079843640327,
0.005561299156397581,
-0.15853364765644073,
0.1406017243862152,
-0.15508677065372467,
-0.09865288436412811,
-0.05270601063966751,
0.13324645161628723,
-0.02777857519686222,
0.1621675342321396,
0.05496421456336975,
-0.014418665319681168,
0.0035464121028780937,
-0.015237431973218918,
0.04721850901842117,
-0.0009800513507798314,
-0.0823616310954094,
-0.033644672483205795,
-0.18589724600315094,
-0.012747902423143387,
0.047270361334085464,
-0.026161834597587585,
-0.2605358064174652,
-0.07658558338880539,
-0.06751655787229538,
-0.04995943605899811,
-0.12565596401691437,
0.050980228930711746,
0.22033780813217163,
0.03622179850935936,
-0.022171910852193832,
-0.08444327861070633,
-0.016116393730044365,
0.01519850455224514,
-0.045565165579319,
-0.0974278599023819
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-300m-england-0211-ladderside_attempt-avatar
This model is a fine-tuned version of [vitouphy/wav2vec2-xls-r-300m-english](https://huggingface.co/vitouphy/wav2vec2-xls-r-300m-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3022
- Wer: 0.2729
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1227
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.1123 | 1.0 | 1227 | 0.3257 | 0.3140 |
| 0.3468 | 2.0 | 2454 | 0.2990 | 0.3002 |
| 0.3221 | 3.0 | 3681 | 0.2845 | 0.2909 |
| 0.3032 | 4.0 | 4908 | 0.2702 | 0.2823 |
| 0.287 | 5.0 | 6135 | 0.2667 | 0.2748 |
| 0.2712 | 6.0 | 7362 | 0.2601 | 0.2696 |
| 0.2558 | 7.0 | 8589 | 0.2583 | 0.2683 |
| 0.24 | 8.0 | 9816 | 0.2575 | 0.2624 |
| 0.2239 | 9.0 | 11043 | 0.2585 | 0.2674 |
| 0.2078 | 10.0 | 12270 | 0.2643 | 0.2630 |
| 0.1918 | 11.0 | 13497 | 0.2646 | 0.2635 |
| 0.177 | 12.0 | 14724 | 0.2784 | 0.2652 |
| 0.164 | 13.0 | 15951 | 0.2793 | 0.2666 |
| 0.1531 | 14.0 | 17178 | 0.2938 | 0.2709 |
| 0.1441 | 15.0 | 18405 | 0.3022 | 0.2729 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.14.7
- Tokenizers 0.15.0
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "vitouphy/wav2vec2-xls-r-300m-english", "model-index": [{"name": "wav2vec2-300m-england-0211-ladderside_attempt-avatar", "results": []}]} | automatic-speech-recognition | Lin25/wav2vec2-300m-england-0211-ladderside_attempt-avatar | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:vitouphy/wav2vec2-xls-r-300m-english",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-11T02:51:23+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-vitouphy/wav2vec2-xls-r-300m-english #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-300m-england-0211-ladderside\_attempt-avatar
=====================================================
This model is a fine-tuned version of vitouphy/wav2vec2-xls-r-300m-english on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3022
* Wer: 0.2729
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.001
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1227
* num\_epochs: 15
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.36.0.dev0
* Pytorch 1.12.1+cu113
* Datasets 2.14.7
* Tokenizers 0.15.0
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 1227\n* num\\_epochs: 15\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.36.0.dev0\n* Pytorch 1.12.1+cu113\n* Datasets 2.14.7\n* Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-vitouphy/wav2vec2-xls-r-300m-english #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 1227\n* num\\_epochs: 15\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.36.0.dev0\n* Pytorch 1.12.1+cu113\n* Datasets 2.14.7\n* Tokenizers 0.15.0"
] | [
80,
159,
4,
40
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-vitouphy/wav2vec2-xls-r-300m-english #license-apache-2.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 1227\n* num\\_epochs: 15\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.36.0.dev0\n* Pytorch 1.12.1+cu113\n* Datasets 2.14.7\n* Tokenizers 0.15.0"
] | [
-0.12465691566467285,
0.13422846794128418,
-0.0033921669237315655,
0.04942885786294937,
0.08694503456354141,
0.02121187187731266,
0.10567963868379593,
0.14321152865886688,
-0.05826539918780327,
0.12673917412757874,
0.11136090010404587,
0.0845835879445076,
0.07596516609191895,
0.1459297239780426,
-0.02841995656490326,
-0.29495757818222046,
0.0224810428917408,
-0.016161799430847168,
-0.1142239198088646,
0.10135062783956528,
0.08888418972492218,
-0.10815936326980591,
0.030373359099030495,
0.006174994166940451,
-0.08791209757328033,
-0.013285565190017223,
-0.03192336484789848,
-0.0618252195417881,
0.10925420373678207,
0.05721037834882736,
0.0789627730846405,
0.038640573620796204,
0.0832996517419815,
-0.27146294713020325,
0.013236995786428452,
0.05100950598716736,
0.02037181332707405,
0.07485561817884445,
0.09717301279306412,
-0.01830236427485943,
0.10736017674207687,
-0.10179122537374496,
0.07814016193151474,
0.03811271861195564,
-0.09145806729793549,
-0.3031558394432068,
-0.07879561185836792,
0.05247556045651436,
0.14443330466747284,
0.08126156777143478,
-0.03472461551427841,
0.07135944068431854,
-0.056889958679676056,
0.07816186547279358,
0.22543039917945862,
-0.2625831067562103,
-0.06478251516819,
-0.01270261686295271,
0.046449512243270874,
0.05287967249751091,
-0.1144741028547287,
-0.019110586494207382,
0.020056825131177902,
0.01791469193994999,
0.08630358427762985,
0.01640322245657444,
0.05626271665096283,
0.019265267997980118,
-0.1485597789287567,
-0.031407251954078674,
0.11930002272129059,
0.09399271011352539,
-0.01598619483411312,
-0.1202399805188179,
-0.033291932195425034,
-0.1576727032661438,
-0.05974581465125084,
-0.011626476421952248,
0.0199188981205225,
-0.035975679755210876,
-0.08254094421863556,
0.020756477490067482,
-0.06593198329210281,
-0.07009761035442352,
0.013556314632296562,
0.13418807089328766,
0.04965931922197342,
-0.03940175846219063,
0.029303492978215218,
0.08000955730676651,
0.039811696857213974,
-0.1509731411933899,
0.0010899495100602508,
0.030081072822213173,
-0.10689733177423477,
-0.012487096711993217,
-0.01752214878797531,
-0.0037971828132867813,
0.031802933663129807,
0.14865058660507202,
-0.02718919701874256,
0.09470890462398529,
0.02501765266060829,
0.010753295384347439,
-0.08100786060094833,
0.14188045263290405,
-0.06458915770053864,
-0.08041055500507355,
-0.04937044158577919,
0.11280500143766403,
0.023620815947651863,
-0.016562215983867645,
-0.07768469303846359,
0.02609618753194809,
0.0910460501909256,
0.04789042845368385,
-0.002183925360441208,
0.00941375084221363,
-0.07486971467733383,
-0.023043794557452202,
0.04457709193229675,
-0.10666938871145248,
0.05648881942033768,
0.040808551013469696,
-0.0424368754029274,
-0.005682796239852905,
-0.0050771646201610565,
0.03140757232904434,
-0.005957894492894411,
0.11618456989526749,
-0.06692945957183838,
-0.01908540353178978,
-0.052657317370176315,
-0.09988176077604294,
0.03331562876701355,
-0.03511057794094086,
-0.0008417097269557416,
-0.07353773713111877,
-0.08586865663528442,
-0.05412377789616585,
0.05573324114084244,
-0.057308558374643326,
-0.062025632709264755,
-0.07954680919647217,
-0.05664779990911484,
0.0692707896232605,
-0.009371276944875717,
0.1232767179608345,
-0.0534224733710289,
0.09213440120220184,
0.004930954892188311,
0.0687665119767189,
0.05363429710268974,
0.05418974533677101,
-0.03217229247093201,
0.04693179205060005,
-0.1655811071395874,
0.07958008348941803,
-0.10107725858688354,
0.0462600402534008,
-0.16477049887180328,
-0.08749037981033325,
-0.010742590762674809,
0.0037504418287426233,
0.0900646448135376,
0.11584417521953583,
-0.1839005947113037,
-0.09751975536346436,
0.1800609976053238,
-0.08436178416013718,
-0.10292261838912964,
0.14855927228927612,
-0.018097100779414177,
-0.04493969306349754,
0.03095185197889805,
0.18467818200588226,
0.09480796754360199,
-0.1019318625330925,
-0.014242682605981827,
-0.048202622681856155,
0.125900000333786,
0.030600544065237045,
0.11503001302480698,
-0.055704984813928604,
0.015985598787665367,
-0.006210555788129568,
-0.022121546790003777,
0.05842384323477745,
-0.07523756474256516,
-0.08422631770372391,
-0.013014234602451324,
-0.07502517849206924,
0.026611171662807465,
0.05130164325237274,
0.025490496307611465,
-0.08779723197221756,
-0.13890734314918518,
0.009012717753648758,
0.112187460064888,
-0.09905129671096802,
0.02573724091053009,
-0.07166428864002228,
0.06583460420370102,
-0.02471533976495266,
-0.005061803851276636,
-0.13695982098579407,
-0.011253075674176216,
0.02891036868095398,
-0.04860220104455948,
0.006382744759321213,
-0.023464569821953773,
0.07495082914829254,
0.05582648143172264,
-0.0624234601855278,
-0.06751437485218048,
-0.03387540578842163,
0.010957157239317894,
-0.07078094780445099,
-0.2536008656024933,
-0.04739753529429436,
-0.041560348123311996,
0.17449812591075897,
-0.23287859559059143,
0.007978971116244793,
0.009731430560350418,
0.14297343790531158,
0.0404483899474144,
-0.049616739153862,
-0.004274751991033554,
0.05847722664475441,
-0.029938064515590668,
-0.06424052268266678,
0.03185473382472992,
-0.012096774764358997,
-0.13092069327831268,
0.010333947837352753,
-0.1443648487329483,
0.09557273238897324,
0.10555122047662735,
0.043106622993946075,
-0.08215141296386719,
-0.08893183618783951,
-0.056019674986600876,
-0.04625513032078743,
-0.032676562666893005,
-0.005051587242633104,
0.1368291676044464,
0.022296762093901634,
0.09638182073831558,
-0.07204465568065643,
-0.03881654888391495,
0.03599295765161514,
0.014294483698904514,
-0.04407728835940361,
0.16101762652397156,
0.07079316675662994,
-0.07004653662443161,
0.10077449679374695,
0.13098689913749695,
-0.04669530689716339,
0.12386652827262878,
-0.06117767095565796,
-0.09604673832654953,
-0.03909028694033623,
0.028104135766625404,
0.038013212382793427,
0.10401234775781631,
-0.12499450147151947,
0.00011558888218132779,
0.020688150078058243,
0.02525905705988407,
0.0072943586856126785,
-0.17663924396038055,
-0.01109160203486681,
0.051894038915634155,
-0.05910249054431915,
-0.0072919102385640144,
-0.014158312231302261,
-0.018293175846338272,
0.08396372199058533,
0.013992696069180965,
-0.06050700694322586,
-0.02008850686252117,
-0.015141600742936134,
-0.10052376240491867,
0.18735739588737488,
-0.12100609391927719,
-0.13682174682617188,
-0.1107015609741211,
-0.024012308567762375,
-0.004433472640812397,
-0.013666593469679356,
0.054017987102270126,
-0.11229386925697327,
-0.042320843786001205,
-0.08469092100858688,
0.02971469797194004,
-0.059263020753860474,
0.0501706637442112,
0.024538688361644745,
0.006641092710196972,
0.04327184706926346,
-0.0882573127746582,
0.021516606211662292,
-0.019353307783603668,
0.006218044552952051,
0.01273646391928196,
0.013273934833705425,
0.09901361912488937,
0.16751913726329803,
0.051268115639686584,
0.025012869387865067,
-0.047743625938892365,
0.17528291046619415,
-0.1031772792339325,
0.005883621983230114,
0.09682352095842361,
0.0012472504749894142,
0.04982517287135124,
0.16714616119861603,
0.04836713522672653,
-0.08160148561000824,
0.02094469591975212,
0.02905653603374958,
-0.010264560580253601,
-0.23609279096126556,
-0.04486323148012161,
-0.05981893837451935,
-0.008341739885509014,
0.11863920092582703,
0.040315914899110794,
-0.02237948402762413,
0.03303240239620209,
-0.014322753064334393,
-0.004443172365427017,
0.014414799399673939,
0.06731575727462769,
0.08740384131669998,
0.04183557257056236,
0.12013236433267593,
-0.025197764858603477,
-0.028503015637397766,
0.039633914828300476,
-0.006057452410459518,
0.22490598261356354,
0.013164778240025043,
0.15907412767410278,
0.03730512037873268,
0.14815069735050201,
0.013581855222582817,
0.04572770744562149,
0.013271297328174114,
-0.025757092982530594,
0.0042893411591649055,
-0.06349009275436401,
-0.0153342979028821,
0.06815525889396667,
0.10480351746082306,
0.015667922794818878,
-0.11365535855293274,
0.016864264383912086,
0.028722455725073814,
0.2802526652812958,
0.10110834985971451,
-0.2881394326686859,
-0.08494052290916443,
0.024226831272244453,
-0.06429651379585266,
-0.023689718917012215,
0.030396588146686554,
0.10517676174640656,
-0.055776551365852356,
0.08272742480039597,
-0.05832483991980553,
0.07868875563144684,
-0.05875645577907562,
-0.0075154732912778854,
0.040583688765764236,
0.0838610976934433,
-0.011864845640957355,
0.05436096340417862,
-0.23350310325622559,
0.300857812166214,
0.002144297119230032,
0.06185218319296837,
-0.041023120284080505,
0.02903771586716175,
0.023582953959703445,
-0.02367059886455536,
0.09743359684944153,
-0.012309964746236801,
-0.14949147403240204,
-0.1586543619632721,
-0.10755860805511475,
0.023196902126073837,
0.11868114769458771,
-0.06869807839393616,
0.10237953066825867,
-0.022582538425922394,
-0.035772960633039474,
0.06107112765312195,
-0.0437554307281971,
-0.11314672976732254,
-0.13791383802890778,
0.01837385818362236,
0.02390027418732643,
0.04385851323604584,
-0.08861307799816132,
-0.11458326876163483,
-0.09115555882453918,
0.15207993984222412,
-0.09642759710550308,
-0.008278883993625641,
-0.13828150928020477,
0.07758791744709015,
0.1609092801809311,
-0.08590144664049149,
0.04970823600888252,
0.006224216427654028,
0.12112695723772049,
-0.004389591049402952,
-0.021128958091139793,
0.12441623210906982,
-0.08886036276817322,
-0.19982311129570007,
-0.07579217851161957,
0.16541942954063416,
0.039482783526182175,
0.06833011656999588,
-0.020997148007154465,
0.041578106582164764,
-0.009769851341843605,
-0.0781874731183052,
0.08743233233690262,
0.05540665239095688,
0.022205648943781853,
0.038115572184324265,
-0.023264657706022263,
-0.03284603729844093,
-0.06224752217531204,
-0.07518796622753143,
0.13796380162239075,
0.3099845349788666,
-0.09964250773191452,
0.054175637662410736,
0.07267068326473236,
-0.04165518283843994,
-0.14749953150749207,
-0.011213596910238266,
0.11096030473709106,
0.032545384019613266,
0.019626058638095856,
-0.1909829080104828,
0.04654333367943764,
0.08012045174837112,
-0.022109389305114746,
0.054848238825798035,
-0.299514502286911,
-0.13938665390014648,
0.11130546778440475,
0.0951491966843605,
-0.023050449788570404,
-0.1629284918308258,
-0.07291495054960251,
-0.01841890625655651,
-0.08837102353572845,
0.058659877628088,
-0.021678363904356956,
0.10548903048038483,
0.0014504729770123959,
0.0050860196352005005,
0.014934753999114037,
-0.056419748812913895,
0.15836037695407867,
-0.0077098277397453785,
0.03126494586467743,
-0.0105955321341753,
0.022249100729823112,
-0.03787294030189514,
-0.0649576187133789,
0.0032912935130298138,
-0.08965753763914108,
0.03260745853185654,
-0.11746523529291153,
-0.03461860492825508,
-0.06254439055919647,
0.013990161940455437,
-0.04498837888240814,
-0.03865162655711174,
-0.041557587683200836,
0.049785126000642776,
0.07602188736200333,
-0.00866411067545414,
0.13438765704631805,
-0.03367864340543747,
0.1528163105249405,
0.09713498502969742,
0.08908714354038239,
0.0037102289497852325,
-0.06963146477937698,
-0.010377682745456696,
-0.034309402108192444,
0.03859543427824974,
-0.1360805630683899,
0.026729537174105644,
0.14457173645496368,
0.035194989293813705,
0.1566532403230667,
0.04956107586622238,
-0.08772237598896027,
0.010831729508936405,
0.07128259539604187,
-0.08107803761959076,
-0.17113368213176727,
-0.016871606931090355,
0.044225748628377914,
-0.14615696668624878,
0.002111061243340373,
0.10808148235082626,
-0.034818731248378754,
-0.008472893387079239,
0.009534978307783604,
0.041008636355400085,
-0.017468124628067017,
0.21549323201179504,
0.035228949040174484,
0.07741193473339081,
-0.08696434646844864,
0.0661788135766983,
0.0627426728606224,
-0.18075448274612427,
0.048869747668504715,
0.08888214826583862,
-0.05956956371665001,
-0.0223891269415617,
0.034298304468393326,
0.08823622018098831,
0.013687703758478165,
-0.05001280456781387,
-0.10624095052480698,
-0.1416071206331253,
0.09546911716461182,
0.08980558812618256,
0.0286586731672287,
0.010445079766213894,
-0.018578147515654564,
0.028939250856637955,
-0.08818807452917099,
0.11803793907165527,
0.08050849288702011,
0.06904196739196777,
-0.13148103654384613,
0.0962539091706276,
0.005609280429780483,
-0.014090328477323055,
0.0027510446961969137,
0.016220945864915848,
-0.12626852095127106,
0.00307014980353415,
-0.10474570840597153,
-0.010948458686470985,
-0.08163022249937057,
-0.004538469947874546,
0.007960007525980473,
-0.06569186598062515,
-0.044137779623270035,
0.0034379728604108095,
-0.10066719353199005,
-0.04576309770345688,
-0.022153012454509735,
0.06914004683494568,
-0.11724007874727249,
-0.020933514460921288,
0.033753279596567154,
-0.1112338975071907,
0.09764771163463593,
0.03073752298951149,
0.036367110908031464,
0.019938191398978233,
-0.09965749830007553,
0.021258065477013588,
0.032896630465984344,
-0.006201489828526974,
0.02797832153737545,
-0.18904319405555725,
-0.016797177493572235,
-0.026024438440799713,
0.01231157872825861,
0.0006191044813022017,
0.042001478374004364,
-0.1148499995470047,
-0.0026931690517812967,
-0.06373682618141174,
-0.07059185951948166,
-0.054164156317710876,
0.05040789768099785,
0.0708576962351799,
0.01201667357236147,
0.14907217025756836,
-0.0870274007320404,
0.053721170872449875,
-0.2193002998828888,
0.0027807094156742096,
-0.031426187604665756,
-0.05132703110575676,
-0.05167054384946823,
-0.019764194265007973,
0.08048106729984283,
-0.054605633020401,
0.0773584246635437,
-0.06151328608393669,
0.0437510684132576,
0.04007377475500107,
-0.10574456304311752,
0.025782490149140358,
0.04471040144562721,
0.19997578859329224,
0.05083022639155388,
-0.02550613135099411,
0.04279240965843201,
0.0024539080914109945,
0.07178132981061935,
0.137655571103096,
0.13864757120609283,
0.16311699151992798,
0.04619503393769264,
0.08988433331251144,
0.056616492569446564,
-0.12446460127830505,
-0.14952975511550903,
0.13274778425693512,
-0.0505509190261364,
0.12263701856136322,
-0.0036637966986745596,
0.19783629477024078,
0.1195773184299469,
-0.19866126775741577,
0.0333433635532856,
-0.03165009990334511,
-0.0888478234410286,
-0.11334225535392761,
-0.0694054514169693,
-0.09658876061439514,
-0.18413053452968597,
0.0030663402285426855,
-0.10130501538515091,
0.043609704822301865,
0.02714058943092823,
0.04914320260286331,
0.05326608940958977,
0.09732173383235931,
0.05968717113137245,
0.016358498483896255,
0.09090957045555115,
0.02789892442524433,
-0.020201245322823524,
-0.025575658306479454,
-0.08776678144931793,
0.03609349951148033,
-0.04193320870399475,
0.04367658123373985,
-0.04059930145740509,
-0.0959504172205925,
0.07702730596065521,
0.020310360938310623,
-0.10311459749937057,
0.01788952387869358,
-0.006651570554822683,
0.05427092686295509,
0.10480048507452011,
0.040353260934352875,
-0.016790350899100304,
-0.015592037700116634,
0.21644027531147003,
-0.09369787573814392,
-0.04794204607605934,
-0.13067875802516937,
0.21886341273784637,
-0.002035768935456872,
0.00789148174226284,
0.018390290439128876,
-0.08484547585248947,
-0.001614079112187028,
0.1462174952030182,
0.14836829900741577,
-0.008537434972822666,
-0.0128974923864007,
0.03556783124804497,
-0.00969971064478159,
-0.03504331409931183,
0.060224808752536774,
0.12247539311647415,
0.08845093101263046,
-0.05734921619296074,
-0.047053441405296326,
-0.045989684760570526,
-0.054885007441043854,
-0.028954679146409035,
0.07112771272659302,
0.02638692781329155,
-0.013109331950545311,
-0.007614858448505402,
0.11813981086015701,
-0.036612775176763535,
-0.13547247648239136,
0.03129667788743973,
-0.19458259642124176,
-0.18193116784095764,
-0.030999675393104553,
0.0831923708319664,
0.03019033372402191,
0.04178052768111229,
0.004377693869173527,
-0.032944366335868835,
0.1087295338511467,
0.005747510585933924,
-0.061776306480169296,
-0.09095799177885056,
0.07698226720094681,
-0.06195938214659691,
0.17110060155391693,
-0.03269008919596672,
0.02339637652039528,
0.13258329033851624,
0.07403609901666641,
-0.08537306636571884,
0.04070720076560974,
0.0881977528333664,
-0.09510976076126099,
0.06531482934951782,
0.16427946090698242,
-0.043467238545417786,
0.1507003903388977,
0.06624232977628708,
-0.10473897308111191,
0.03149082884192467,
-0.09452635049819946,
-0.06903994083404541,
-0.05181585252285004,
0.028023090213537216,
-0.04808000475168228,
0.15068504214286804,
0.18012842535972595,
-0.06588926166296005,
-0.02063954994082451,
-0.028162136673927307,
0.01489912997931242,
0.0314309261739254,
0.14450062811374664,
-0.02213136851787567,
-0.2586686909198761,
0.026346303522586823,
0.005942780990153551,
0.03500347584486008,
-0.24705246090888977,
-0.09849528968334198,
0.018885361030697823,
-0.04813682660460472,
-0.07339941710233688,
0.11952648311853409,
0.08413115888834,
0.0388621985912323,
-0.06799168139696121,
-0.1152370497584343,
-0.0226230900734663,
0.16855163872241974,
-0.16250088810920715,
-0.05446529760956764
] |
null | null | diffusers |
# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test
These are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following.
| {"license": "creativeml-openrail-m", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "textual_inversion"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "inference": true} | text-to-image | Stelath/textual_inversion_comic_strip_fp16 | [
"diffusers",
"tensorboard",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"textual_inversion",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | 2024-02-11T02:51:37+00:00 | [] | [] | TAGS
#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us
|
# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test
These are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following.
!img_0
!img_1
!img_2
!img_3
| [
"# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test\nThese are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
"TAGS\n#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us \n",
"# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test\nThese are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
108,
86
] | [
"passage: TAGS\n#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us \n# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_test\nThese are textual inversion adaption weights for stabilityai/stable-diffusion-xl-base-1.0. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
-0.12564118206501007,
-0.10199816524982452,
-0.0036781728267669678,
0.0028595104813575745,
0.06154044345021248,
-0.0014107469469308853,
0.2095247060060501,
0.1278240978717804,
0.09875844419002533,
0.1198037788271904,
0.07856301218271255,
0.06516625732183456,
0.027537906542420387,
0.050159238278865814,
-0.07338200509548187,
-0.1671273410320282,
0.008385444059967995,
0.0038244593888521194,
-0.06113622710108757,
0.10609543323516846,
0.0929517149925232,
-0.06360045075416565,
0.07612685114145279,
0.023109959438443184,
-0.09398896992206573,
0.005586731713265181,
0.047696612775325775,
-0.08513443917036057,
0.09936098754405975,
0.015353298746049404,
0.06262470781803131,
0.1660502701997757,
0.01352710835635662,
-0.13697747886180878,
0.028618812561035156,
0.05832767114043236,
0.01671077497303486,
0.06055067107081413,
-0.008772443979978561,
-0.03503047302365303,
0.04309314489364624,
-0.044863469898700714,
-0.025332974269986153,
0.018390031531453133,
-0.0503503642976284,
-0.034838926047086716,
-0.10440833121538162,
-0.02097100205719471,
0.037916261702775955,
0.024298906326293945,
-0.00845368206501007,
0.12681466341018677,
-0.05924045294523239,
0.03455376625061035,
0.27143552899360657,
-0.27704790234565735,
-0.01093425415456295,
0.11925510317087173,
0.1510966718196869,
0.10017213225364685,
-0.02845107577741146,
0.11586924642324448,
0.07071718573570251,
-0.01138747576624155,
0.04414910078048706,
-0.053535327315330505,
0.1481436789035797,
-0.002269480610266328,
-0.12771297991275787,
0.06922383606433868,
0.13563664257526398,
-0.02117842808365822,
-0.08695950359106064,
-0.19250871241092682,
-0.0033962647430598736,
0.12224601209163666,
-0.030271083116531372,
-0.06323959678411484,
-0.008103403262794018,
-0.02394687943160534,
0.022984573617577553,
-0.05589151382446289,
-0.09875389188528061,
-0.08424098789691925,
-0.06994681060314178,
0.1273784637451172,
-0.017225464805960655,
-0.010252708569169044,
0.052999380975961685,
0.10626733303070068,
-0.14387072622776031,
-0.1424466073513031,
-0.012029961682856083,
-0.06175645813345909,
-0.009193508885800838,
-0.023951368406414986,
-0.04675566405057907,
-0.3035958707332611,
0.06745810061693192,
0.034383442252874374,
0.02824721671640873,
0.013044335879385471,
-0.048041656613349915,
0.11006122827529907,
-0.02448245882987976,
0.07940178364515305,
-0.05639581009745598,
0.007265028543770313,
0.0053871748968958855,
0.1126425564289093,
0.06450452655553818,
-0.01915786787867546,
-0.05156582593917847,
-0.0457562692463398,
-0.00146747927647084,
0.030937515199184418,
0.0016001502517610788,
0.018126115202903748,
-0.0812070444226265,
-0.006441445555537939,
0.10536347329616547,
-0.07507466524839401,
0.0374961718916893,
-0.02784017287194729,
0.016072284430265427,
0.12483829259872437,
0.12796998023986816,
0.021100511774420738,
-0.010383404791355133,
0.06922528892755508,
-0.03913325443863869,
0.06971525400876999,
-0.003572650020942092,
-0.11630163341760635,
0.02123606763780117,
-0.12912653386592865,
-0.06493370234966278,
-0.10557131469249725,
-0.09955236315727234,
0.013424856588244438,
0.026656925678253174,
-0.03931797295808792,
0.09169577807188034,
0.030131086707115173,
-0.027414673939347267,
0.03685504570603371,
0.01902691088616848,
-0.12009673565626144,
-0.03586846590042114,
0.049056630581617355,
0.05459943413734436,
0.09115369617938995,
0.033040281385183334,
-0.0033078042324632406,
-0.0643351674079895,
0.04207197204232216,
-0.3191680610179901,
0.10205597430467606,
-0.10886033624410629,
-0.021356696262955666,
-0.08630593866109848,
-0.03575318679213524,
-0.08092129975557327,
0.06962014734745026,
0.06255261600017548,
0.23541267216205597,
-0.26189109683036804,
-0.07578722387552261,
0.14119689166545868,
-0.16368550062179565,
-0.12524546682834625,
0.11043038219213486,
0.01847721077501774,
0.045055143535137177,
0.03427184745669365,
0.11121433973312378,
0.027894694358110428,
-0.26143544912338257,
0.034491244703531265,
-0.018740441650152206,
-0.05201306566596031,
0.01506356056779623,
0.05630865320563316,
-0.05444278195500374,
0.05229530110955238,
0.022690944373607635,
-0.13851727545261383,
0.054894447326660156,
-0.05515754967927933,
0.02508782595396042,
-0.0774858221411705,
-0.008952352218329906,
0.11916499584913254,
0.03854968398809433,
0.02939365617930889,
-0.05109553039073944,
-0.10047949105501175,
0.10386358946561813,
-0.00526534765958786,
-0.08400952070951462,
0.041442256420850754,
-0.05092431232333183,
0.17989544570446014,
-0.14778146147727966,
-0.017003536224365234,
-0.13976486027240753,
0.0050626457668840885,
0.03469390794634819,
0.15484029054641724,
0.030724354088306427,
0.05491974949836731,
0.13449953496456146,
0.006151129957288504,
-0.01913456805050373,
0.010013340041041374,
0.08400856703519821,
0.015127149410545826,
-0.07986223697662354,
-0.14858579635620117,
0.04383077844977379,
-0.08201710134744644,
0.07406065613031387,
-0.2182171493768692,
0.05465695261955261,
-0.003704144386574626,
0.14629466831684113,
0.07483798265457153,
-0.027882134541869164,
0.011930974200367928,
-0.02104494720697403,
-0.09064120799303055,
-0.03566204011440277,
0.002653865609318018,
-0.015464500524103642,
-0.05915283039212227,
0.21907003223896027,
-0.13768720626831055,
0.12202315777540207,
0.11257664114236832,
-0.012469414621591568,
-0.07696095108985901,
-0.14780081808567047,
-0.0034071330446749926,
0.023209918290376663,
-0.05526581034064293,
-0.03477306291460991,
0.0016820025630295277,
0.0380355566740036,
0.11480354517698288,
-0.061497271060943604,
0.0017813702579587698,
0.03410083055496216,
-0.07358913123607635,
-0.03090011142194271,
0.056439220905303955,
0.019106058403849602,
0.006052188575267792,
0.008906365372240543,
0.15139713883399963,
-0.04649997875094414,
0.02607208490371704,
-0.05547133460640907,
-0.10854717344045639,
-0.028815163299441338,
0.07751672714948654,
0.07755689322948456,
0.12808313965797424,
-0.02190699428319931,
-0.025096677243709564,
0.018756994977593422,
-0.02908826805651188,
0.015825901180505753,
-0.09872091561555862,
0.0006921314052306116,
0.08996112644672394,
-0.04925857484340668,
0.07998424768447876,
0.05599195882678032,
-0.01824713684618473,
0.10170295834541321,
-0.0829169750213623,
-0.03096717968583107,
-0.011887685395777225,
-0.012386859394609928,
-0.1308228224515915,
0.1516578495502472,
-0.05655466392636299,
-0.12972046434879303,
-0.1163933202624321,
-0.0004266265605110675,
0.04054959490895271,
0.010500254109501839,
0.036113232374191284,
-0.03631681203842163,
-0.06156960502266884,
-0.13281436264514923,
0.05400913953781128,
0.11720576137304306,
0.04345168173313141,
0.0015410681953653693,
-0.05431422218680382,
0.03185679391026497,
-0.07387755811214447,
-0.01592741161584854,
-0.020703088492155075,
0.08589937537908554,
0.0671115592122078,
0.02132374607026577,
0.09132371097803116,
0.12049812823534012,
-0.01858879253268242,
0.01751434989273548,
0.012040961533784866,
0.05586742237210274,
-0.049822982400655746,
0.11251500993967056,
0.18081925809383392,
-0.011173030361533165,
0.04690219461917877,
0.05511663481593132,
0.017376922070980072,
0.00854095071554184,
0.023922080174088478,
-0.007006458006799221,
-0.07334335148334503,
-0.1406083106994629,
-0.06096283718943596,
-0.06148253381252289,
-0.03784242272377014,
-0.019317353144288063,
0.014367402531206608,
0.10079478472471237,
0.09670202434062958,
0.06478424370288849,
-0.04946862906217575,
0.05179879814386368,
0.05718265101313591,
0.09940861910581589,
-0.030627455562353134,
0.08834604918956757,
-0.049290161579847336,
-0.06144953891634941,
0.08256402611732483,
-0.08860539644956589,
0.12014041095972061,
-0.05588580295443535,
0.07379473745822906,
0.056707289069890976,
0.043125249445438385,
0.07116168737411499,
0.09772602468729019,
-0.04203323274850845,
-0.07510940730571747,
0.025145750492811203,
-0.11780271679162979,
0.05097299814224243,
0.042937230318784714,
0.03699171543121338,
-0.04474220052361488,
-0.05728749558329582,
0.016259968280792236,
0.059659142047166824,
0.018616531044244766,
0.13663680851459503,
-0.26744258403778076,
-0.022757122293114662,
-0.007967695593833923,
0.024229880422353745,
-0.003116236301138997,
-0.028098253533244133,
0.14713911712169647,
-0.0299860630184412,
0.052058856934309006,
-0.12350057065486908,
0.05616217479109764,
0.042276106774806976,
-0.02080201357603073,
-0.024868695065379143,
0.13877274096012115,
-0.05313099920749664,
-0.020544499158859253,
-0.1944301724433899,
0.06718555837869644,
0.013774564489722252,
-0.006311691831797361,
-0.04622634872794151,
0.020305532962083817,
0.05555723235011101,
0.09608159959316254,
0.09877175092697144,
-0.022999383509159088,
0.043010611087083817,
-0.028236916288733482,
-0.12060347199440002,
-0.03332960978150368,
0.07574193924665451,
-0.01208128035068512,
0.0662904754281044,
0.01535098161548376,
-0.02576112188398838,
0.04852921888232231,
0.0035561511758714914,
-0.2368645966053009,
-0.10346512496471405,
0.056617897003889084,
-0.013691321946680546,
-0.10472510755062103,
-0.10390828549861908,
-0.10576220601797104,
-0.17824289202690125,
0.25023695826530457,
-0.039453618228435516,
-0.055667776614427567,
-0.12753939628601074,
-0.002764742588624358,
0.11551429331302643,
-0.024943286553025246,
0.0063726031221449375,
-0.019085343927145004,
0.09155609458684921,
-0.06408867239952087,
-0.12777240574359894,
0.08997886627912521,
-0.07171255350112915,
-0.08853618800640106,
-0.09021735191345215,
0.14073120057582855,
0.00845443457365036,
-0.008068809285759926,
0.034704823046922684,
0.007986281998455524,
0.05033088102936745,
-0.06655493378639221,
0.034083571285009384,
0.0324840173125267,
-0.018416740000247955,
0.06957428902387619,
-0.03670482337474823,
-0.02262977883219719,
-0.02050529420375824,
0.025511963292956352,
0.1171770691871643,
0.13075807690620422,
-0.08597050607204437,
0.07481484115123749,
0.05438745766878128,
-0.03398318588733673,
-0.1943272352218628,
0.05420960485935211,
-0.01869501918554306,
0.0581156425178051,
0.09857585281133652,
-0.02691272459924221,
0.1194821149110794,
0.05946630239486694,
0.004911620635539293,
0.2179946005344391,
-0.32178670167922974,
-0.13685278594493866,
0.0556764155626297,
0.0794372484087944,
0.023820964619517326,
-0.16505677998065948,
-0.12363046407699585,
0.05266806110739708,
-0.09807851910591125,
0.03536040708422661,
-0.05888998508453369,
0.043828338384628296,
-0.027966806665062904,
-0.07778690755367279,
0.02887800708413124,
-0.07469417154788971,
0.14631758630275726,
-0.08261852711439133,
0.0012123705819249153,
-0.08797495067119598,
0.052363160997629166,
0.07056284695863724,
-0.06908222287893295,
0.07826947420835495,
-0.21419855952262878,
0.033476561307907104,
-0.14812664687633514,
-0.01605599746108055,
-0.005798890721052885,
0.08032375574111938,
-0.005957591813057661,
-0.0018392031779512763,
-0.07827619463205338,
0.008267153054475784,
-0.03962291032075882,
-0.029664423316717148,
0.07446935772895813,
-0.05298617482185364,
0.08726436644792557,
0.18495021760463715,
0.10901948064565659,
-0.03031250834465027,
-0.07145699858665466,
-0.0037858576979488134,
-0.008113136515021324,
0.022220635786652565,
-0.11303441971540451,
0.0030105707701295614,
0.1335529237985611,
0.07328624278306961,
0.1211571916937828,
0.03556646406650543,
-0.09606431424617767,
0.0412420928478241,
0.11668356508016586,
-0.07540716975927353,
-0.02004457637667656,
-0.01660817489027977,
-0.014417415484786034,
-0.004738637711852789,
0.06091219559311867,
0.137492835521698,
-0.03924129530787468,
0.027888773009181023,
0.011546147055923939,
0.032756365835666656,
-0.053881190717220306,
0.1512591689825058,
0.05131500959396362,
0.026061831042170525,
-0.03415243700146675,
0.06676862388849258,
-0.06595607846975327,
-0.11316640675067902,
-0.02750347927212715,
0.07137840241193771,
-0.07602855563163757,
-0.047277484089136124,
0.08396997302770615,
0.1118602529168129,
-0.09081995487213135,
0.012592380866408348,
-0.11404763162136078,
-0.17107272148132324,
-0.016214922070503235,
0.1441413015127182,
0.0566832572221756,
-0.016225231811404228,
0.0025835006963461637,
-0.018933335319161415,
-0.05474196374416351,
0.08353567868471146,
0.13522027432918549,
0.10109595954418182,
-0.15662214159965515,
-0.03262864798307419,
-0.036055609583854675,
-0.020131733268499374,
-0.07948367297649384,
0.0013535041362047195,
-0.05591713637113571,
-0.04110788181424141,
-0.14951974153518677,
0.04479469358921051,
-0.12420831620693207,
-0.08224056661128998,
0.009794473648071289,
-0.07653512060642242,
0.012589615769684315,
-0.006893262732774019,
-0.030590586364269257,
-0.016958605498075485,
-0.030429275706410408,
0.018263651058077812,
-0.10153622925281525,
-0.027492975816130638,
0.003791968571022153,
-0.12001293897628784,
0.08003025501966476,
0.03333889693021774,
-0.05616924166679382,
-0.006876274012029171,
-0.21655696630477905,
-0.0026739947497844696,
0.11535897850990295,
-0.00922895222902298,
0.0017450039740651846,
-0.07074292004108429,
0.06295216828584671,
0.033232614398002625,
0.0106961689889431,
-0.002424232428893447,
0.01844359189271927,
-0.04487815871834755,
0.02595607005059719,
-0.1121954694390297,
0.018652252852916718,
-0.05374547094106674,
0.07449450343847275,
0.13873222470283508,
0.09165582805871964,
0.12244261056184769,
-0.13101382553577423,
0.06500118970870972,
-0.16963614523410797,
0.007625898811966181,
0.020062658935785294,
-0.019515840336680412,
0.10683517158031464,
0.017511136829853058,
0.017956744879484177,
-0.028101027011871338,
0.1283349245786667,
-0.034422360360622406,
-0.09989236295223236,
0.020488059148192406,
-0.03421805799007416,
0.1122482568025589,
0.03807383030653,
0.17758770287036896,
0.019658468663692474,
0.024478033185005188,
-0.1414409726858139,
0.04250868037343025,
0.10007727891206741,
-0.16674914956092834,
0.14968514442443848,
0.15762954950332642,
-0.1055903285741806,
0.1370546966791153,
0.04173482954502106,
-0.03905792906880379,
0.005963945761322975,
0.06825271248817444,
-0.09511949867010117,
0.11990801244974136,
0.008856697008013725,
0.09903861582279205,
0.15268146991729736,
-0.061139073222875595,
0.0006640661740675569,
0.01896868646144867,
-0.05988331139087677,
-0.0604131855070591,
-0.130680114030838,
-0.040348391979932785,
-0.1904054880142212,
-0.0022215330973267555,
-0.05429988354444504,
0.030782030895352364,
-0.00048324899398721755,
0.062182094901800156,
0.040324222296476364,
0.12767671048641205,
0.04242638498544693,
-0.06848081946372986,
0.13369503617286682,
-0.015769708901643753,
-0.05940743163228035,
0.09080296009778976,
-0.0026929122395813465,
0.04991995170712471,
0.03465227037668228,
0.010947166942059994,
0.06309013813734055,
0.04775916785001755,
0.03305749595165253,
-0.029191607609391212,
-0.0974745899438858,
0.017482493072748184,
0.006814707536250353,
0.010760549455881119,
0.11284587532281876,
0.06393406540155411,
-0.004596727434545755,
-0.04857334867119789,
0.12933722138404846,
-0.031918808817863464,
-0.04015793651342392,
-0.1260697990655899,
0.09337589889764786,
-0.06713804602622986,
0.046976104378700256,
-0.0721168965101242,
-0.1265585869550705,
0.01868458092212677,
0.20250897109508514,
0.1626291573047638,
-0.07407188415527344,
0.005370815750211477,
-0.023841828107833862,
-0.022477325052022934,
0.02147197537124157,
0.01837947964668274,
0.016147632151842117,
0.21596716344356537,
-0.01980837620794773,
-0.012651887722313404,
-0.06878896802663803,
-0.08038612455129623,
-0.07574649900197983,
-0.013098425231873989,
0.024511605501174927,
-0.013139933347702026,
-0.03228702023625374,
0.11294979602098465,
0.021156515926122665,
-0.13280236721038818,
0.05711142718791962,
-0.10290554910898209,
-0.03338725492358208,
-0.04857859015464783,
0.06401389837265015,
-0.05050712078809738,
-0.013388211838901043,
-0.03861464932560921,
-0.012652807869017124,
-0.005180776119232178,
-0.017789732664823532,
-0.03547700494527817,
0.06575293838977814,
-0.03267929330468178,
-0.1303638517856598,
0.037018656730651855,
-0.010361379012465477,
0.08649784326553345,
0.08076532930135727,
0.03505780175328255,
-0.07310494780540466,
0.03610201179981232,
-0.0048947809264063835,
-0.08112715929746628,
-0.00797212403267622,
0.10484974831342697,
0.029070662334561348,
-0.01449035108089447,
0.06484721601009369,
-0.11467526108026505,
0.057383451610803604,
-0.06165112927556038,
-0.12510569393634796,
-0.13818587362766266,
-0.013407143764197826,
-0.052342724055051804,
0.09877097606658936,
0.050481073558330536,
-0.010557989589869976,
0.06017391011118889,
-0.013616109266877174,
0.029907023534178734,
0.04201880842447281,
0.0656994879245758,
0.028917714953422546,
-0.14093433320522308,
0.03162089362740517,
0.026935547590255737,
0.012520218268036842,
-0.2627454102039337,
-0.07024431228637695,
-0.07196086645126343,
-0.02047756500542164,
0.010610807687044144,
0.08096987754106522,
0.2455509603023529,
0.06375695019960403,
-0.010469183325767517,
-0.16871148347854614,
0.06217831000685692,
0.14597536623477936,
-0.11018131673336029,
0.0029289722442626953
] |
null | null | transformers |
TinyTim
---
license: llama2
---
TinyTim is a version of TinyLlama that has been finetuned on text from James Joyce's Finnegan's Wake.
Hope other Joyce fans find it useful or entertaining! | {} | text-generation | caug37/TinyTim | [
"transformers",
"safetensors",
"gguf",
"llama",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T02:54:13+00:00 | [] | [] | TAGS
#transformers #safetensors #gguf #llama #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
TinyTim
---
license: llama2
---
TinyTim is a version of TinyLlama that has been finetuned on text from James Joyce's Finnegan's Wake.
Hope other Joyce fans find it useful or entertaining! | [] | [
"TAGS\n#transformers #safetensors #gguf #llama #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] | [
54
] | [
"passage: TAGS\n#transformers #safetensors #gguf #llama #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] | [
-0.0064122555777430534,
0.02255621738731861,
-0.006035775877535343,
-0.013292711228132248,
0.15196160972118378,
-0.018770087510347366,
0.14931869506835938,
0.09585024416446686,
-0.012765979394316673,
0.0029845228418707848,
0.14115726947784424,
0.16785666346549988,
-0.022869830951094627,
0.07486376166343689,
-0.12024322897195816,
-0.18477758765220642,
0.09942250698804855,
-0.014214659109711647,
0.008653846569359303,
0.07460074871778488,
0.08926931023597717,
-0.05679836496710777,
0.08219633251428604,
-0.0615135058760643,
-0.12755580246448517,
0.040972620248794556,
0.059874240309000015,
-0.12342879176139832,
0.10368393361568451,
0.08161503076553345,
0.09217216074466705,
0.029322516173124313,
-0.07760756462812424,
-0.22490820288658142,
0.03540550172328949,
0.012063191272318363,
-0.060419075191020966,
0.009583822451531887,
0.03438281640410423,
-0.09464818239212036,
0.04442509263753891,
0.07586072385311127,
-0.027260027825832367,
0.08508966118097305,
-0.16535517573356628,
0.029737912118434906,
-0.01177789643406868,
-0.052453093230724335,
0.09148285537958145,
0.09374777972698212,
-0.033292584121227264,
0.0848163291811943,
-0.0634668618440628,
0.11960022896528244,
0.09004785120487213,
-0.3165549635887146,
0.0003888290957547724,
0.12019508332014084,
0.05613104999065399,
0.07488253712654114,
-0.07805334776639938,
0.11205090582370758,
0.05892272666096687,
-0.02457508258521557,
-0.002258505206555128,
-0.0762566402554512,
-0.116920106112957,
0.046426109969615936,
-0.07048608362674713,
-0.01773506961762905,
0.21421562135219574,
-0.03796780854463577,
0.04434136673808098,
-0.07957123219966888,
-0.09656070172786713,
-0.02066459320485592,
-0.03636503964662552,
0.01291563268750906,
-0.05281560868024826,
0.09673572331666946,
0.025921383872628212,
-0.04712456092238426,
-0.12398675084114075,
-0.025393202900886536,
-0.16826966404914856,
0.20070143043994904,
0.0014878060901537538,
0.033579807728528976,
-0.19036224484443665,
0.03832735866308212,
0.005453171208500862,
-0.1039390042424202,
0.004882768262177706,
-0.07095742225646973,
0.00992018636316061,
0.0038854603189975023,
-0.043578583747148514,
-0.10826656222343445,
0.1682933270931244,
0.10337492823600769,
-0.03806925565004349,
0.04932180047035217,
-0.09790894389152527,
0.06015996262431145,
0.032113052904605865,
0.05797358229756355,
0.005222055595368147,
-0.04901714250445366,
0.061785049736499786,
-0.09074544906616211,
0.030172185972332954,
-0.07056016474962234,
-0.1456693410873413,
0.02341366559267044,
0.03083774633705616,
0.12588590383529663,
-0.012362396344542503,
0.1171063706278801,
-0.03315357863903046,
0.040776804089546204,
0.0018396475352346897,
-0.08124183863401413,
-0.013962103985249996,
0.017177043482661247,
0.04755860194563866,
0.034416355192661285,
-0.012968105264008045,
0.04351545125246048,
-0.06736895442008972,
0.006687674671411514,
-0.07269971817731857,
-0.03487936779856682,
-0.028937438502907753,
-0.059318237006664276,
0.015482049435377121,
-0.045913971960544586,
0.02332773618400097,
-0.18467682600021362,
-0.1792043000459671,
-0.005872097797691822,
-0.014400242827832699,
-0.032703619450330734,
0.008175062015652657,
-0.08558705449104309,
-0.03845641762018204,
0.041561685502529144,
-0.06252938508987427,
-0.0672096535563469,
-0.07745624333620071,
0.08435162901878357,
0.00830555334687233,
0.07078412175178528,
-0.11673863232135773,
0.04958626255393028,
-0.09676073491573334,
0.01965043507516384,
-0.0671469196677208,
0.09869120270013809,
-0.03825366869568825,
0.1615477055311203,
0.0023649909999221563,
0.05271100997924805,
-0.08939939737319946,
0.08635372668504715,
-0.035252850502729416,
0.2336420714855194,
-0.10392356663942337,
-0.0698002502322197,
0.2704465985298157,
-0.10174211859703064,
-0.1713515669107437,
0.11934170126914978,
-0.0023232894018292427,
0.046907611191272736,
0.12118498980998993,
0.23336271941661835,
-0.006812465377151966,
-0.01771281473338604,
0.054775673896074295,
0.09571181982755661,
-0.07974045723676682,
-0.018493348732590675,
-0.014395799487829208,
-0.02543666772544384,
-0.1417870968580246,
0.041065942496061325,
0.12024585157632828,
0.08630554378032684,
-0.029300808906555176,
-0.04684920981526375,
-0.035110458731651306,
-0.04280979931354523,
0.033263687044382095,
-0.035753779113292694,
0.0795048326253891,
-0.09073196351528168,
-0.0004851304111070931,
-0.04726708307862282,
-0.007968412712216377,
-0.04217963665723801,
0.0024970448575913906,
-0.08532778173685074,
0.09194739162921906,
-0.026421543210744858,
0.07833277434110641,
-0.11370819807052612,
-0.15080393850803375,
-0.016493842005729675,
0.13727760314941406,
-0.0047189281322062016,
0.0347147136926651,
0.06307534873485565,
-0.0028807835187762976,
-0.0054617710411548615,
0.0029191593639552593,
0.21277624368667603,
0.012537532486021519,
-0.06454005092382431,
-0.0680679902434349,
0.13587792217731476,
-0.08079370856285095,
0.04729216545820236,
-0.13122928142547607,
0.019889958202838898,
0.0694422498345375,
0.10270466655492783,
0.03432406112551689,
0.025636421516537666,
0.009112262167036533,
-0.008270658552646637,
-0.07678736001253128,
-0.008873254992067814,
0.0711982473731041,
-0.002735215937718749,
-0.10438745468854904,
0.19899244606494904,
-0.2478702813386917,
0.2668910622596741,
0.1780240386724472,
-0.2032952755689621,
0.009674794040620327,
-0.10217569768428802,
-0.0008750950801186264,
0.019084805622696877,
0.034916821867227554,
-0.06024169921875,
0.06591242551803589,
-0.030314942821860313,
0.1751050502061844,
-0.04856107011437416,
-0.024923181161284447,
-0.012714555487036705,
-0.06836135685443878,
-0.04133422672748566,
0.07116370648145676,
0.02700032852590084,
-0.17389759421348572,
0.20285940170288086,
0.17004798352718353,
0.044507578015327454,
0.21953421831130981,
-0.02180681936442852,
0.012444473803043365,
0.06849810481071472,
0.06017829477787018,
-0.018062306568026543,
-0.047489140182733536,
-0.18194817006587982,
-0.026853283867239952,
0.0446121022105217,
0.04232648015022278,
0.10394762456417084,
-0.10232608765363693,
-0.054801709949970245,
-0.005302773788571358,
-0.03873012959957123,
0.07376916706562042,
0.07946208119392395,
0.013070238754153252,
0.1277366280555725,
-0.030755646526813507,
-0.03035893104970455,
0.10000268369913101,
-0.016481420025229454,
-0.09921754896640778,
0.1999548375606537,
-0.1446828693151474,
-0.3408334255218506,
-0.15134970843791962,
-0.1756613552570343,
-0.07692691683769226,
0.07707907259464264,
0.11200769245624542,
-0.1290654093027115,
-0.06076591834425926,
-0.043178461492061615,
0.07547326385974884,
-0.030399302020668983,
0.020620374009013176,
-0.03116607293486595,
0.03758740797638893,
-0.06817552447319031,
-0.09744638949632645,
-0.045274440199136734,
0.0011376772308722138,
-0.06978212296962738,
0.1189270168542862,
-0.08336617797613144,
0.09099432826042175,
0.17316831648349762,
0.04388149455189705,
0.030709493905305862,
-0.03715059906244278,
0.18335658311843872,
-0.10256275534629822,
-0.028680292889475822,
0.16446097195148468,
-0.06578158587217331,
0.049319904297590256,
0.17159521579742432,
-0.010819005779922009,
-0.14060866832733154,
0.058820974081754684,
0.00040947733214125037,
-0.08834417909383774,
-0.2018880695104599,
-0.11393259465694427,
-0.09824506938457489,
0.09810734540224075,
-0.013564776629209518,
0.07932241261005402,
0.16647368669509888,
0.06868891417980194,
-0.022648371756076813,
-0.020905667915940285,
0.06311307847499847,
0.06499861925840378,
0.20603692531585693,
-0.044979847967624664,
0.1284654289484024,
-0.05620967224240303,
-0.15567509829998016,
0.0610278882086277,
0.06835366785526276,
0.07112512737512589,
0.10731135308742523,
0.07243316620588303,
0.01967942714691162,
0.01852688379585743,
0.12941311299800873,
0.0944417417049408,
0.014085667207837105,
-0.06767629086971283,
-0.01159314252436161,
-0.03816824033856392,
-0.045330069959163666,
0.04197065159678459,
-0.02701224572956562,
-0.13386274874210358,
-0.02969486080110073,
-0.05859650671482086,
0.12192949652671814,
0.0642537996172905,
0.056717898696660995,
-0.1978604644536972,
0.0020331433042883873,
0.13140973448753357,
-0.03907831013202667,
-0.12124495208263397,
0.11442483961582184,
0.08408965170383453,
-0.07106996327638626,
0.05792810767889023,
-0.025152331218123436,
0.09456096589565277,
-0.055007901042699814,
0.10081153362989426,
-0.12124689668416977,
-0.05068239942193031,
-0.014967262744903564,
0.09502708166837692,
-0.3165867328643799,
0.18792667984962463,
0.023835506290197372,
-0.01667754165828228,
-0.07833194732666016,
-0.00019496679306030273,
0.020260095596313477,
0.11520745605230331,
0.1405019760131836,
-0.02433370240032673,
-0.08351557701826096,
-0.07829058915376663,
-0.006585780065506697,
0.04118191823363304,
0.1469573676586151,
-0.022715376690030098,
0.015086766332387924,
-0.05659041553735733,
-0.0027779988013207912,
-0.0030070485081523657,
-0.07465211302042007,
-0.046615127474069595,
-0.20348624885082245,
0.048491500318050385,
0.12485988438129425,
0.13146598637104034,
-0.012949226424098015,
0.04601902514696121,
-0.13902881741523743,
0.22023843228816986,
-0.08888110518455505,
-0.05189617723226547,
-0.12222462147474289,
-0.07572261244058609,
0.010748032480478287,
-0.03508413955569267,
0.051319532096385956,
-0.07298320531845093,
0.04856692627072334,
-0.08088040351867676,
-0.17926400899887085,
0.127342090010643,
-0.10727261751890182,
-0.02190185897052288,
-0.041094955056905746,
0.16336745023727417,
-0.056110791862010956,
-0.04122284799814224,
0.04872875660657883,
0.02241211012005806,
-0.04712372273206711,
-0.10239262133836746,
0.024341098964214325,
0.014475788921117783,
0.004214381333440542,
0.06350582093000412,
-0.08773907274007797,
-0.08229130506515503,
-0.02927359752357006,
-0.05322088301181793,
0.30448117852211,
0.21080628037452698,
-0.028443122282624245,
0.14237384498119354,
0.17250533401966095,
-0.07142242044210434,
-0.3598255217075348,
-0.09370695054531097,
-0.17143946886062622,
-0.030207600444555283,
-0.046452391892671585,
-0.12831799685955048,
0.09097141772508621,
0.009746654890477657,
-0.02919047512114048,
0.15186570584774017,
-0.21425707638263702,
-0.08897055685520172,
0.1840442270040512,
0.031634725630283356,
0.4016166925430298,
-0.19345684349536896,
-0.1204269751906395,
-0.09574853628873825,
-0.07717424631118774,
0.141804039478302,
-0.10306784510612488,
0.10636639595031738,
0.035977158695459366,
0.07054314017295837,
0.05816822871565819,
-0.028728798031806946,
0.12070699036121368,
-0.025677476078271866,
0.04332452639937401,
-0.11838431656360626,
-0.018270744010806084,
0.005112144630402327,
-0.0006264290423132479,
0.031493768095970154,
-0.11705027520656586,
0.018160438165068626,
-0.045803193002939224,
-0.046560123562812805,
-0.021634027361869812,
0.07018405199050903,
0.04506758227944374,
-0.05934763699769974,
-0.020308934152126312,
-0.0702853873372078,
0.006790720392018557,
0.019632425159215927,
0.23547868430614471,
-0.10477851331233978,
0.19964048266410828,
0.15494070947170258,
0.14168670773506165,
-0.12713417410850525,
0.10281948745250702,
-0.025391308590769768,
-0.06805253773927689,
0.08485617488622665,
-0.0965808779001236,
0.08080621063709259,
0.06955590099096298,
-0.05082010105252266,
0.1038525328040123,
0.08997766673564911,
0.015741901472210884,
0.002785647753626108,
0.14783529937267303,
-0.2359418421983719,
-0.09610868245363235,
-0.05897171422839165,
0.006634729914367199,
0.08554843068122864,
0.10510457307100296,
0.1987825334072113,
0.026874976232647896,
0.019238604232668877,
-0.01865314692258835,
0.041306015104055405,
-0.036092448979616165,
0.07117629051208496,
0.009257538244128227,
0.025359956547617912,
-0.14028950035572052,
0.09961745887994766,
-0.006536869797855616,
-0.12987220287322998,
0.04637378826737404,
0.13611488044261932,
-0.11994970589876175,
-0.1294506937265396,
-0.08555220812559128,
0.1651948243379593,
-0.09554202109575272,
-0.05095971003174782,
-0.041743651032447815,
-0.16569942235946655,
0.03395910933613777,
0.22565476596355438,
0.032188642770051956,
0.10878890007734299,
-0.011046799831092358,
-0.016021326184272766,
-0.03591214492917061,
0.027068309485912323,
-0.0170756708830595,
0.014081410132348537,
-0.11134353280067444,
-0.006585543975234032,
-0.05323811247944832,
0.08872248232364655,
-0.10251479595899582,
-0.0581267848610878,
-0.19674529135227203,
0.01710330694913864,
-0.14543737471103668,
-0.048138078302145004,
-0.0845903605222702,
-0.029338959604501724,
0.01869603618979454,
-0.021246274933218956,
-0.037393294274806976,
-0.06397685408592224,
-0.09487886726856232,
0.0262262262403965,
-0.027880150824785233,
0.03298196941614151,
-0.08833476901054382,
-0.018045734614133835,
0.07080962508916855,
-0.03766363486647606,
0.14235979318618774,
0.114722341299057,
-0.09216561913490295,
0.11470203101634979,
-0.2696073353290558,
-0.062212854623794556,
0.1333799958229065,
-0.023693764582276344,
0.025221146643161774,
0.08953963965177536,
0.0010872165439650416,
0.08044464141130447,
0.03209681436419487,
0.05831942707300186,
0.027520332485437393,
-0.10420626401901245,
0.043743863701820374,
-0.05653729289770126,
-0.11085058003664017,
-0.03458234667778015,
-0.08087914437055588,
0.05687427520751953,
-0.02919401414692402,
0.10941071063280106,
-0.09325217455625534,
0.0686236172914505,
-0.017112551257014275,
0.03694496303796768,
0.025337710976600647,
-0.19413428008556366,
-0.06339018046855927,
-0.06295423209667206,
0.030603352934122086,
-0.007110594771802425,
0.2635350525379181,
0.010703319683670998,
-0.024873577058315277,
0.046206410974264145,
0.023204149678349495,
0.08094096183776855,
0.04443121701478958,
0.229760080575943,
0.12193021923303604,
-0.0565921925008297,
-0.14343884587287903,
0.04630715027451515,
0.049080170691013336,
-0.05755060166120529,
0.07928819209337234,
0.0435376837849617,
-0.1159333884716034,
0.11293893307447433,
-0.0053017837926745415,
-0.02041512541472912,
-0.0017680644523352385,
-0.07305105775594711,
-0.08920130878686905,
0.023712484166026115,
-0.04213550314307213,
0.05847100913524628,
0.2118225246667862,
-0.012522878125309944,
0.016160983592271805,
-0.03541681170463562,
-0.05198964849114418,
-0.18089793622493744,
-0.12537625432014465,
-0.10228627175092697,
-0.12392809242010117,
0.02640601620078087,
-0.11371736973524094,
0.04974353685975075,
0.04922192171216011,
0.06071336194872856,
-0.030203109607100487,
0.17784209549427032,
0.029716940596699715,
-0.05968450382351875,
0.06179005652666092,
-0.040415987372398376,
0.05994859337806702,
0.00971936248242855,
-0.04561319574713707,
-0.07168417423963547,
-0.012485451065003872,
-0.02273562364280224,
0.06862522661685944,
-0.008164340630173683,
0.053249042481184006,
-0.15499582886695862,
-0.07652662694454193,
-0.04093101620674133,
0.08413659781217575,
-0.062022384256124496,
0.1111806258559227,
0.027511363849043846,
-0.05024390295147896,
0.06162859499454498,
0.2377467006444931,
-0.0672212615609169,
-0.05962219834327698,
-0.055367399007081985,
0.15891720354557037,
0.005958155263215303,
0.16705746948719025,
-0.0779593288898468,
-0.02856500819325447,
-0.05531277507543564,
0.3682738244533539,
0.2638523578643799,
-0.1010449156165123,
0.03593987971544266,
-0.047655098140239716,
0.04292294755578041,
0.08470012247562408,
0.10314859449863434,
0.08396229892969131,
0.28573063015937805,
-0.03532048687338829,
-0.03549329563975334,
0.015925772488117218,
-0.03788706660270691,
-0.12580038607120514,
0.11546952277421951,
0.024566777050495148,
-0.017076395452022552,
-0.04760707542300224,
0.0961565226316452,
-0.22358401119709015,
0.0895320400595665,
-0.10420793294906616,
-0.1340782195329666,
-0.026194486767053604,
-0.019145308062434196,
0.1035999283194542,
-0.013616432435810566,
0.06688374280929565,
-0.006798774003982544,
-0.1115930825471878,
-0.010254524648189545,
0.016459131613373756,
-0.18585218489170074,
0.009289185516536236,
0.005061356350779533,
-0.02055923081934452,
0.03317747265100479,
-0.01837657392024994,
-0.0011654326226562262,
0.08236202597618103,
0.016130810603499413,
-0.02005852945148945,
0.12716998159885406,
0.003195993835106492,
-0.07791660726070404,
0.028966890648007393,
0.049787018448114395,
0.0093741025775671,
-0.016040386632084846,
0.06420200318098068,
-0.14582988619804382,
0.05987554043531418,
0.00045093995868228376,
-0.0905534103512764,
-0.006854205392301083,
0.009705781005322933,
-0.07150541245937347,
0.06591706722974777,
0.04881131276488304,
-0.007475336082279682,
0.0354364812374115,
-0.022544680163264275,
0.021288080140948296,
-0.031625743955373764,
-0.09909699112176895,
-0.05918072164058685,
-0.16694974899291992,
-0.08447092771530151,
0.14703980088233948,
-0.006823449861258268,
-0.25925320386886597,
0.022965731099247932,
-0.10128752142190933,
0.10355594754219055,
-0.15858475863933563,
0.0787435919046402,
0.19651469588279724,
0.019067848101258278,
-0.027433710172772408,
-0.15616004168987274,
0.0723186656832695,
0.09999869018793106,
-0.04390270262956619,
-0.10244302451610565
] |
null | null | null |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
``` | {"license": "other", "tags": ["autotrain", "text-generation"], "widget": [{"text": "I love AutoTrain because "}]} | text-generation | InnerI/NousResearch-Llama2-7bhf | [
"tensorboard",
"safetensors",
"autotrain",
"text-generation",
"conversational",
"doi:10.57967/hf/1761",
"license:other",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:15:17+00:00 | [] | [] | TAGS
#tensorboard #safetensors #autotrain #text-generation #conversational #doi-10.57967/hf/1761 #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
| [
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
"TAGS\n#tensorboard #safetensors #autotrain #text-generation #conversational #doi-10.57967/hf/1761 #license-other #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
53,
29,
3
] | [
"passage: TAGS\n#tensorboard #safetensors #autotrain #text-generation #conversational #doi-10.57967/hf/1761 #license-other #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.# Usage"
] | [
-0.07200268656015396,
0.06151486933231354,
-0.00019187346333637834,
0.056454502046108246,
0.09307248145341873,
-0.03851618990302086,
0.24693240225315094,
0.06572914868593216,
-0.010653158649802208,
-0.06143573671579361,
0.1941394954919815,
0.182493656873703,
-0.014000632800161839,
0.1304558515548706,
-0.046271827071905136,
-0.2409805804491043,
0.017790885642170906,
0.020063988864421844,
0.08458098769187927,
0.09482920914888382,
0.1270197331905365,
-0.09208691865205765,
0.05757985636591911,
0.05009295418858528,
-0.1985396444797516,
0.04587429389357567,
0.061237502843141556,
-0.09299329668283463,
0.1872793436050415,
0.05162853002548218,
0.12784135341644287,
0.06352408975362778,
0.12474394589662552,
-0.07806628197431564,
0.029711760580539703,
0.007401132024824619,
-0.03022698126733303,
0.0820406824350357,
0.08523869514465332,
-0.008778875693678856,
0.08623214066028595,
0.15818670392036438,
0.08422189950942993,
0.04430593177676201,
-0.08590973913669586,
0.015086873434484005,
-0.03687319904565811,
0.021576665341854095,
0.12198556214570999,
0.11526740342378616,
-0.01318405568599701,
0.2176397144794464,
-0.10317154228687286,
0.09380967170000076,
-0.05676925182342529,
-0.3058379590511322,
-0.027100494131445885,
0.2255392223596573,
0.07145660370588303,
0.002634069649502635,
-0.12310361117124557,
0.04695477709174156,
0.1268136352300644,
-0.01464108843356371,
0.025873906910419464,
-0.029828473925590515,
-0.030836064368486404,
-0.015943529084324837,
-0.08397406339645386,
0.05579210817813873,
0.2173439860343933,
-0.04159821942448616,
-0.008618870750069618,
-0.07877423614263535,
-0.038608476519584656,
-0.00036704575177282095,
0.004913388751447201,
-0.13356828689575195,
-0.022797778248786926,
0.07358396053314209,
-0.013477236032485962,
-0.05307236313819885,
-0.16961900889873505,
-0.04584851488471031,
-0.10677693039178848,
0.02872711606323719,
0.007048825267702341,
0.012049111537635326,
-0.12218761444091797,
0.08580364286899567,
-0.0034815415274351835,
-0.10639423131942749,
0.04651525989174843,
-0.06534195691347122,
0.018112724646925926,
-0.11229834705591202,
0.00028103188378736377,
-0.186044842004776,
0.013798368163406849,
0.13875669240951538,
0.12757383286952972,
0.03812374174594879,
-0.08497771620750427,
0.05009888485074043,
0.004093836061656475,
0.10771927982568741,
0.017230505123734474,
-0.012921730056405067,
0.056273043155670166,
-0.023249447345733643,
0.003578831674531102,
-0.02906768210232258,
-0.21081557869911194,
0.045144226402044296,
0.0016102780355140567,
0.032084379345178604,
-0.07531020790338516,
0.07106325775384903,
-0.01672401838004589,
0.042794689536094666,
0.050901129841804504,
-0.03167028725147247,
0.028848985210061073,
-0.04273981973528862,
0.01096630934625864,
-0.07638188451528549,
0.031611017882823944,
0.10465843975543976,
0.013845493085682392,
0.11569458246231079,
-0.09744250029325485,
-0.01478477381169796,
-0.09486214816570282,
-0.04418811947107315,
0.030118348076939583,
-0.006818965543061495,
0.04488350450992584,
-0.18951895833015442,
-0.233808696269989,
-0.023970630019903183,
0.04844121262431145,
-0.040092166513204575,
-0.0563400574028492,
-0.08564867824316025,
-0.0002588954521343112,
0.0533611960709095,
-0.02279270812869072,
0.0678909569978714,
-0.017724502831697464,
0.024248339235782623,
-0.057108182460069656,
0.02504887804389,
-0.09879398345947266,
-0.003628665814176202,
-0.09782899171113968,
-0.021902523934841156,
0.0025630476884543896,
-0.01819303259253502,
-0.04461083933711052,
0.11892654001712799,
-0.012090294621884823,
0.04571046680212021,
-0.0657089501619339,
0.0397673062980175,
0.04170868918299675,
0.14521008729934692,
-0.1659889966249466,
0.012757276184856892,
0.1598724126815796,
-0.09718447923660278,
-0.11586218327283859,
0.1257198601961136,
-0.08782097697257996,
0.21342606842517853,
0.07363511621952057,
0.14462900161743164,
0.018372345715761185,
-0.1416671723127365,
0.08859534561634064,
0.05159018933773041,
-0.08929961174726486,
-0.07466066628694534,
-0.010613448917865753,
-0.017988402396440506,
-0.15274874866008759,
0.02006419375538826,
0.14102846384048462,
0.05122627317905426,
-0.026147911325097084,
-0.07326267659664154,
-0.009965073317289352,
-0.06595703959465027,
0.040224939584732056,
0.03741243854165077,
0.14040246605873108,
-0.07105563580989838,
-0.03309699892997742,
0.014320820569992065,
0.05519358068704605,
0.05906160920858383,
-0.05746321380138397,
-0.0834333747625351,
0.0015125726349651814,
-0.06578938663005829,
-0.015734132379293442,
-0.08086539059877396,
-0.04120856523513794,
-0.03019673191010952,
0.12143655121326447,
0.05185496434569359,
0.1413179636001587,
0.058841995894908905,
0.026361612603068352,
-0.026903972029685974,
0.02081781066954136,
0.171645849943161,
0.04438233748078346,
-0.13321064412593842,
-0.11841321736574173,
0.12137404084205627,
-0.08477051556110382,
0.13023895025253296,
-0.25639331340789795,
0.016905542463064194,
-0.06710688024759293,
0.11134073883295059,
-0.0034539559856057167,
0.06871825456619263,
-0.0645887702703476,
0.0063400897197425365,
-0.09100620448589325,
-0.008857669308781624,
0.06078328937292099,
0.058605633676052094,
-0.04376203566789627,
0.1313907653093338,
-0.166944682598114,
0.2126878947019577,
0.12079871445894241,
-0.10643208026885986,
-0.09434041380882263,
-0.07323731482028961,
0.0032558836974203587,
-0.0199467521160841,
-0.09002003818750381,
0.0044005317613482475,
0.11369776725769043,
-0.04946203902363777,
0.18875180184841156,
-0.03953992575407028,
-0.03165055438876152,
0.009054862894117832,
-0.0862501859664917,
-0.03230591490864754,
0.02386441081762314,
0.12134016305208206,
-0.24559955298900604,
0.13282370567321777,
0.13824589550495148,
-0.053999412804841995,
0.23353126645088196,
0.03340083733201027,
0.010989743284881115,
-0.018970949575304985,
-0.011613010428845882,
0.0019703912548720837,
0.08381447941064835,
-0.07983014732599258,
-0.01808004640042782,
-0.0008139710989780724,
-0.0005917492089793086,
0.0443863607943058,
-0.16049405932426453,
-0.03856142610311508,
0.002831571502611041,
0.049519989639520645,
0.05618793144822121,
0.06464935839176178,
-0.08752365410327911,
0.09258616715669632,
-0.023632286116480827,
-0.14796702563762665,
0.11069366335868835,
0.00776861235499382,
-0.12194931507110596,
0.1831529438495636,
-0.08095056563615799,
-0.2009115070104599,
-0.16130110621452332,
-0.12287130206823349,
0.00015713743050582707,
0.06939813494682312,
0.03964395448565483,
-0.08482472598552704,
-0.06424300372600555,
-0.01747114583849907,
-0.15499842166900635,
-0.016505185514688492,
-0.01805180311203003,
-0.06971524655818939,
0.051604919135570526,
-0.0003782103885896504,
-0.10074298083782196,
-0.03578859567642212,
-0.0241559911519289,
-0.04354160651564598,
0.050239358097314835,
-0.036484841257333755,
0.06089456379413605,
0.13980333507061005,
-0.015019179321825504,
0.033189818263053894,
-0.02435607649385929,
0.10772142559289932,
-0.08967302739620209,
0.029024440795183182,
0.07740902900695801,
-0.0569666251540184,
0.03598644584417343,
0.2117600440979004,
0.03457852825522423,
-0.07164793461561203,
0.04224367439746857,
-0.023609748110175133,
-0.05936465784907341,
-0.2137010544538498,
-0.07729406654834747,
-0.02163137122988701,
0.028528695926070213,
0.06270811706781387,
0.06381415575742722,
0.24527238309383392,
0.1338462382555008,
0.07912464439868927,
0.04023955017328262,
-0.016902385279536247,
0.07439881563186646,
0.09657208621501923,
-0.056679148226976395,
0.1527068316936493,
-0.08159865438938141,
-0.150199294090271,
0.04046914726495743,
0.006288777571171522,
0.047623295336961746,
0.1583193689584732,
-0.001496748998761177,
0.03619501367211342,
0.145220085978508,
0.1169774979352951,
0.09498190134763718,
0.07099669426679611,
-0.08522821217775345,
0.002867822302505374,
-0.009145278483629227,
-0.017112143337726593,
0.1371397078037262,
-0.007901779375970364,
-0.05656183883547783,
-0.0007670017657801509,
0.05343552306294441,
0.026342041790485382,
0.051191821694374084,
0.03954864293336868,
-0.27541565895080566,
0.0185262281447649,
0.01780465990304947,
-0.036878038197755814,
-0.10850854963064194,
0.08400027453899384,
0.0260940995067358,
-0.12626035511493683,
0.012376384809613228,
-0.04924111068248749,
0.05967443063855171,
0.005249256268143654,
0.04562819376587868,
-0.08843182027339935,
-0.025998203083872795,
-0.05583435297012329,
0.13834495842456818,
-0.3600170612335205,
0.26040008664131165,
-0.000022700663976138458,
0.06587625294923782,
-0.12224632501602173,
0.002246105344966054,
0.08274855464696884,
0.13010938465595245,
0.12779052555561066,
-0.05191386118531227,
-0.1444813758134842,
-0.07205689698457718,
-0.09552361816167831,
-0.007834672927856445,
0.02153768204152584,
0.0456734336912632,
-0.023456361144781113,
-0.08703865110874176,
-0.011982312425971031,
0.044270068407058716,
-0.017516551539301872,
-0.1363978385925293,
-0.15577438473701477,
0.012741745449602604,
0.06248754262924194,
-0.011522234417498112,
-0.017015589401125908,
-0.07286912202835083,
-0.09421920776367188,
0.18945208191871643,
0.004732809495180845,
0.01193985529243946,
-0.12148130685091019,
-0.004729830659925938,
-0.07338810712099075,
-0.04266355186700821,
0.03898380696773529,
0.004444791469722986,
0.12070436030626297,
-0.08444810658693314,
-0.059143003076314926,
0.10509265959262848,
-0.13303564488887787,
-0.04094045236706734,
-0.13013601303100586,
0.05084354802966118,
-0.020328335464000702,
-0.004924735985696316,
0.09814667701721191,
0.021107641980051994,
-0.06883134692907333,
-0.05756642296910286,
0.010862552560865879,
-0.05416817590594292,
0.038255706429481506,
-0.1477060616016388,
-0.08108897507190704,
-0.12056472152471542,
-0.027877135202288628,
-0.12260852009057999,
0.19771777093410492,
0.17197556793689728,
-0.09318511188030243,
0.11248040944337845,
0.21033883094787598,
-0.08159518241882324,
-0.2902262806892395,
-0.03818628564476967,
-0.04419507458806038,
0.01704658754169941,
0.03052203357219696,
-0.07924969494342804,
0.09973757714033127,
0.016055839136242867,
-0.09789984673261642,
0.00605743657797575,
-0.10054471343755722,
-0.1613672375679016,
0.2528480291366577,
0.039509065449237823,
0.2383219450712204,
-0.07758960127830505,
-0.05903482809662819,
-0.08414599299430847,
0.03273557126522064,
0.047869130969047546,
-0.10212311148643494,
0.050999902188777924,
0.0406201034784317,
0.06875627487897873,
0.03231428563594818,
-0.056439511477947235,
0.05155615508556366,
-0.08880463242530823,
0.06684846431016922,
-0.16963133215904236,
-0.07892405986785889,
0.027336115017533302,
-0.027256881818175316,
0.09019047766923904,
-0.038445718586444855,
0.03097144141793251,
-0.024782443419098854,
-0.052348293364048004,
0.007024538703262806,
0.0645567774772644,
-0.020410560071468353,
-0.11063851416110992,
-0.013966493308544159,
0.010271941311657429,
-0.015003953129053116,
-0.06490669399499893,
0.07522289454936981,
-0.01895030401647091,
0.1376449018716812,
0.19198310375213623,
0.22740647196769714,
-0.09738238155841827,
0.068732351064682,
-0.0285617895424366,
-0.11367049068212509,
0.074271060526371,
-0.07009707391262054,
0.009106100536882877,
0.07626090198755264,
-0.03492501750588417,
0.1462828516960144,
0.058249618858098984,
-0.03539976105093956,
-0.010931950993835926,
0.147688090801239,
-0.17271241545677185,
0.004686843138188124,
-0.07462607324123383,
0.1312674582004547,
0.05680963024497032,
0.0213736891746521,
0.11829672753810883,
-0.07200094312429428,
-0.004917308688163757,
0.019879059866070747,
0.0022899301256984472,
-0.01564379222691059,
0.06868625432252884,
0.05866681784391403,
0.02085835486650467,
-0.05521449074149132,
0.04617379605770111,
0.06694073975086212,
-0.04600315913558006,
0.05513501912355423,
0.03265174478292465,
-0.08576890081167221,
-0.10019994527101517,
0.003276348812505603,
0.2560063600540161,
-0.15276430547237396,
-0.10921184718608856,
-0.050704196095466614,
-0.0743345320224762,
0.00011753533908631653,
0.11307647824287415,
0.060114335268735886,
0.000024251974537037313,
-0.050822991877794266,
-0.02160741575062275,
-0.1374223381280899,
0.09490606933832169,
-0.01914227567613125,
0.06003689020872116,
-0.1630580723285675,
0.06329949200153351,
-0.022711602970957756,
0.017220085486769676,
-0.0765426903963089,
-0.010577940382063389,
-0.11930352449417114,
0.012834321707487106,
-0.09175057709217072,
-0.0235856082290411,
-0.05436743423342705,
-0.03817076236009598,
0.058535054326057434,
-0.029555561020970345,
-0.04157591983675957,
-0.01052695419639349,
-0.09855549782514572,
0.054660990834236145,
0.02106870897114277,
0.01594611071050167,
-0.023704780265688896,
-0.02508939802646637,
0.017977913841605186,
0.009489675983786583,
0.057059913873672485,
0.007692527025938034,
-0.00974211748689413,
0.041969358921051025,
-0.15137402713298798,
0.04303952306509018,
0.056047167629003525,
0.019596736878156662,
0.04421105235815048,
-0.009533604606986046,
-0.01584053784608841,
0.09797906130552292,
0.04955950751900673,
0.02543424814939499,
0.021444566547870636,
-0.0839877724647522,
0.04508158937096596,
0.05721259489655495,
-0.12650129199028015,
-0.04976508766412735,
-0.009998863562941551,
-0.008126506581902504,
-0.038749780505895615,
0.18494883179664612,
-0.1189211830496788,
0.030839359387755394,
-0.04607737436890602,
0.04368091747164726,
-0.015657303854823112,
-0.10536237061023712,
-0.05363396182656288,
-0.09350632131099701,
-0.014552731066942215,
-0.03089636005461216,
0.2177693247795105,
0.10460267215967178,
-0.02945924550294876,
0.03803861141204834,
0.026844341307878494,
0.06018923595547676,
-0.009421774186193943,
0.17116615176200867,
0.05261774733662605,
-0.006128533277660608,
-0.1325739026069641,
0.09289664030075073,
0.032735444605350494,
-0.01960758864879608,
0.040921516716480255,
-0.020977674052119255,
-0.09790980815887451,
0.07758200168609619,
0.07441599667072296,
-0.0537366159260273,
-0.0847327932715416,
-0.12109634280204773,
-0.14972023665905,
0.03036399930715561,
-0.07191108167171478,
0.028292978182435036,
0.2079843431711197,
-0.04653321951627731,
-0.034897331148386,
-0.08220692723989487,
-0.06537872552871704,
-0.19831858575344086,
-0.1721850335597992,
-0.11176055669784546,
-0.06466633826494217,
0.04321037605404854,
-0.02899966575205326,
0.04438579082489014,
0.010759555734694004,
0.07690072804689407,
-0.07754645496606827,
0.12241923063993454,
-0.07448666542768478,
-0.0006168945110403001,
0.0074021643958985806,
-0.020649952813982964,
0.0033588744699954987,
-0.19253329932689667,
-0.005892377346754074,
-0.13778504729270935,
-0.03301194682717323,
-0.0375804677605629,
-0.05069832503795624,
0.025740642100572586,
-0.012504867278039455,
0.010108202695846558,
-0.018768690526485443,
-0.007298655807971954,
0.032772764563560486,
0.05483312904834747,
0.06832057237625122,
0.017989587038755417,
0.028563424944877625,
0.027966333553195,
0.1717444807291031,
-0.03308287262916565,
-0.11287611722946167,
-0.12992307543754578,
0.1947023868560791,
-0.0012075984850525856,
0.09393364191055298,
-0.06079135462641716,
-0.02031395584344864,
0.0773930475115776,
0.3268296420574188,
0.24347425997257233,
-0.04222024977207184,
0.01827836036682129,
-0.0145439887419343,
-0.004948418587446213,
-0.04969358816742897,
0.14132650196552277,
0.020422393456101418,
0.19043639302253723,
-0.0625886470079422,
-0.0008500951807945967,
-0.010473744012415409,
-0.0718192607164383,
-0.0480710044503212,
0.12212307751178741,
-0.0018291549058631063,
-0.009160690940916538,
-0.02355135977268219,
0.06088241934776306,
-0.043335266411304474,
0.08928023278713226,
-0.09073040634393692,
-0.06329714506864548,
-0.07575984299182892,
0.054974380880594254,
0.11504256725311279,
-0.03514653444290161,
0.04196176677942276,
-0.0413830503821373,
-0.003931134007871151,
0.009939196519553661,
-0.0440228097140789,
-0.10033778846263885,
0.0034244831185787916,
0.053569816052913666,
-0.04839128255844116,
0.25034284591674805,
-0.016881244257092476,
0.06932172924280167,
0.10466786473989487,
0.0036538029089570045,
-0.08687717467546463,
0.108554907143116,
0.008976157754659653,
-0.07189258933067322,
0.10005486011505127,
0.009575976058840752,
0.007994178682565689,
-0.030659111216664314,
0.009230555966496468,
-0.17196905612945557,
0.12800736725330353,
-0.10763759911060333,
-0.09696101397275925,
-0.0580328144133091,
0.14822734892368317,
-0.03117481805384159,
0.16964606940746307,
0.07177041471004486,
-0.007433717139065266,
-0.0071690999902784824,
-0.019084876403212547,
0.05815822258591652,
0.005835024639964104,
-0.09021792560815811,
-0.029506724327802658,
-0.18642152845859528,
0.0058512017130851746,
0.056606292724609375,
-0.020497988909482956,
-0.24899691343307495,
-0.066353440284729,
-0.06758653372526169,
-0.06317158788442612,
-0.11013493686914444,
0.031660839915275574,
0.2001754641532898,
0.042346399277448654,
-0.01715772971510887,
-0.07425438612699509,
-0.025843149051070213,
0.02184676006436348,
-0.056563034653663635,
-0.10569658875465393
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | null | Damodaran/donut-demo-niel | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:16:54+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #vision-encoder-decoder #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #vision-encoder-decoder #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
39,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #vision-encoder-decoder #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.05306316912174225,
0.20225799083709717,
-0.004532716237008572,
0.02486577071249485,
0.10745619982481003,
0.005829503294080496,
0.06235508993268013,
0.11292294412851334,
-0.0020419019274413586,
0.12131396681070328,
0.02719549834728241,
0.07967612892389297,
0.12327883392572403,
0.1561002880334854,
0.003298027440905571,
-0.2451947182416916,
0.056976594030857086,
-0.09095743298530579,
0.005862638354301453,
0.11416777968406677,
0.1328127682209015,
-0.10651655495166779,
0.09236611425876617,
-0.006378492806106806,
-0.018223589286208153,
-0.01560811698436737,
-0.07464081048965454,
-0.06576249748468399,
0.05573050677776337,
0.07688132673501968,
0.0721992626786232,
0.009551521390676498,
0.07658318430185318,
-0.2803225517272949,
0.014262731187045574,
0.08472383767366409,
0.001679662149399519,
0.06746198982000351,
0.08127366751432419,
-0.06743600219488144,
0.1253480762243271,
-0.072596974670887,
0.1388878971338272,
0.07806979864835739,
-0.09000035375356674,
-0.19567735493183136,
-0.06588542461395264,
0.06967565417289734,
0.13176710903644562,
0.05219413340091705,
-0.02802334912121296,
0.13226838409900665,
-0.09170275926589966,
0.009603562764823437,
0.11835573613643646,
-0.0669531598687172,
-0.05480296164751053,
0.036625828593969345,
0.09896823018789291,
0.08901896327733994,
-0.11835762113332748,
-0.005250310990959406,
0.02971211075782776,
0.02317153476178646,
0.08707734197378159,
0.01639537699520588,
0.14948242902755737,
0.03726613521575928,
-0.14019928872585297,
-0.05744593217968941,
0.0939771831035614,
0.03824683278799057,
-0.04958764836192131,
-0.2343815118074417,
-0.031156767159700394,
-0.016557393595576286,
-0.0305255725979805,
-0.04024772346019745,
0.05501044541597366,
-0.03525097668170929,
0.0778101459145546,
-0.00980226881802082,
-0.08041384816169739,
-0.028304021805524826,
0.04802321270108223,
0.06495635211467743,
0.0185654629021883,
-0.0052207582630217075,
0.02111206203699112,
0.11669638752937317,
0.0788947269320488,
-0.13250376284122467,
-0.07449234277009964,
-0.07420225441455841,
-0.098720021545887,
-0.04206917807459831,
0.035802435129880905,
0.07063398510217667,
0.03907659277319908,
0.1947319507598877,
-0.017316637560725212,
0.0492829903960228,
0.04488114267587662,
0.006694390904158354,
0.06837808340787888,
0.11208193004131317,
-0.06981375813484192,
-0.1344674974679947,
-0.058068543672561646,
0.0876275971531868,
-0.004179352894425392,
-0.03578972443938255,
-0.050102028995752335,
0.04014993831515312,
0.030947856605052948,
0.11303774267435074,
0.08247632533311844,
0.00018158231978304684,
-0.06263403594493866,
-0.042954958975315094,
0.22251743078231812,
-0.14639760553836823,
0.04202887415885925,
0.005975429899990559,
-0.04316512867808342,
-0.004425262566655874,
0.010939684696495533,
0.012188587337732315,
-0.037748441100120544,
0.10074765980243683,
-0.07618969678878784,
-0.034445326775312424,
-0.11386469751596451,
-0.0645400807261467,
0.02648116648197174,
0.004736251663416624,
-0.021350713446736336,
-0.043291062116622925,
-0.11405764520168304,
-0.04943132400512695,
0.07177776843309402,
-0.07382809370756149,
-0.05491260066628456,
0.011223746463656425,
-0.053137388080358505,
0.004582186229526997,
0.00267049134708941,
0.1107012927532196,
-0.032886769622564316,
0.02474004216492176,
-0.046873610466718674,
0.06870805472135544,
0.10572899132966995,
0.037948183715343475,
-0.08262749016284943,
0.07297130674123764,
-0.23081135749816895,
0.10601279884576797,
-0.0860590934753418,
0.020004073157906532,
-0.14292661845684052,
-0.04098188504576683,
0.028510602191090584,
0.027961768209934235,
-0.010129709728062153,
0.1261758655309677,
-0.2058180272579193,
-0.030243845656514168,
0.14840680360794067,
-0.11589378863573074,
-0.09422067552804947,
0.06595603376626968,
-0.05322439596056938,
0.10703813284635544,
0.04694817587733269,
-0.023595338687300682,
0.07076855003833771,
-0.1317324936389923,
-0.04631568118929863,
-0.021216953173279762,
-0.014257868751883507,
0.1454293578863144,
0.06817390769720078,
-0.05359628424048424,
0.07706184685230255,
0.021635930985212326,
-0.037367887794971466,
-0.03435307368636131,
-0.03299751877784729,
-0.0921449214220047,
0.006188652943819761,
-0.06746368855237961,
0.029415255412459373,
-0.021083641797304153,
-0.09160202741622925,
-0.0303809754550457,
-0.1750536859035492,
0.03627307340502739,
0.08193549513816833,
0.006318137980997562,
-0.0197709072381258,
-0.09286735206842422,
0.01832297258079052,
-0.012543086893856525,
-0.01892191916704178,
-0.16171851754188538,
-0.04700363799929619,
0.04258821904659271,
-0.20086339116096497,
0.01967989094555378,
-0.03661181032657623,
0.04892909526824951,
0.03480081260204315,
-0.04064054414629936,
-0.008631768636405468,
0.003335281042382121,
0.015725387260317802,
-0.024876078590750694,
-0.20007483661174774,
-0.030333993956446648,
-0.02597803995013237,
0.13431528210639954,
-0.22246739268302917,
0.02835940755903721,
0.08417746424674988,
0.1434013694524765,
0.0016660679830238223,
-0.04368278756737709,
0.014076939783990383,
-0.054847393184900284,
-0.05226233974099159,
-0.06906641274690628,
-0.006392029579728842,
-0.03333830088376999,
-0.03956965357065201,
0.07096927613019943,
-0.20027990639209747,
-0.04262993112206459,
0.10826600342988968,
0.09837738424539566,
-0.14323553442955017,
-0.02474437840282917,
-0.04144697263836861,
-0.061835117638111115,
-0.09049158543348312,
-0.06381296366453171,
0.1425853669643402,
0.04930912330746651,
0.05233171954751015,
-0.08628004789352417,
-0.06071622669696808,
0.010883725248277187,
-0.00011982241994701326,
-0.04022165387868881,
0.08589175343513489,
0.08529563993215561,
-0.1104804202914238,
0.09131632000207901,
0.08476598560810089,
0.06810380518436432,
0.10764316469430923,
0.0015695258043706417,
-0.10674308240413666,
-0.02863943576812744,
0.007197246421128511,
0.014064288698136806,
0.14327655732631683,
-0.04052828997373581,
0.048501238226890564,
0.05552942305803299,
-0.026791011914610863,
0.01846246048808098,
-0.1073673665523529,
0.03181065618991852,
0.047323208302259445,
-0.009707847610116005,
0.022087840363383293,
-0.03469701483845711,
0.029233038425445557,
0.08711127936840057,
0.035028502345085144,
0.029371140524744987,
0.006271174643188715,
-0.035827167332172394,
-0.10475867241621017,
0.17433254420757294,
-0.0890800803899765,
-0.2983497679233551,
-0.1401464194059372,
-0.0031294787768274546,
0.04853705316781998,
-0.02189650572836399,
0.011501757428050041,
-0.04715869575738907,
-0.11619791388511658,
-0.10501103848218918,
0.008872180245816708,
0.04236939176917076,
-0.07721052318811417,
-0.0677536204457283,
0.049645159393548965,
0.03511786088347435,
-0.1394437551498413,
0.02193400263786316,
0.04976930096745491,
-0.03652774170041084,
-0.014805521816015244,
0.07396114617586136,
0.1029050275683403,
0.17309242486953735,
-0.006633569020777941,
-0.017617538571357727,
0.023926623165607452,
0.24285922944545746,
-0.14599764347076416,
0.10973547399044037,
0.15899382531642914,
-0.06477009505033493,
0.10309092700481415,
0.19795724749565125,
0.023503681644797325,
-0.07609159499406815,
0.03380175679922104,
0.03942976891994476,
-0.05477331578731537,
-0.22650650143623352,
-0.06247439235448837,
-0.0018889455823227763,
-0.07084330171346664,
0.0898994579911232,
0.09043484926223755,
0.10881193727254868,
0.04595636948943138,
-0.08826620131731033,
-0.06884618103504181,
0.018320003524422646,
0.10980518162250519,
-0.021245790645480156,
0.0068580652587115765,
0.08790436387062073,
-0.04739201068878174,
-0.004643888212740421,
0.10682045668363571,
0.012494737282395363,
0.19045358896255493,
0.026300430297851562,
0.1511247158050537,
0.0705496221780777,
0.02818082831799984,
0.028634218499064445,
0.01902483031153679,
0.02658020332455635,
0.008844421245157719,
-0.017161816358566284,
-0.08914987742900848,
0.024366190657019615,
0.1353050321340561,
0.07279488444328308,
0.03349636495113373,
0.02151625230908394,
-0.03378571942448616,
0.06302186101675034,
0.16916872560977936,
0.010774882510304451,
-0.22069227695465088,
-0.038822758942842484,
0.08901690691709518,
-0.07502853125333786,
-0.12661625444889069,
-0.02531552128493786,
0.041314706206321716,
-0.17944134771823883,
0.04614526778459549,
-0.01675923727452755,
0.11310327053070068,
-0.12792818248271942,
-0.027826640754938126,
0.0399215929210186,
0.08714547008275986,
-0.030904775485396385,
0.07850778102874756,
-0.16933031380176544,
0.11483496427536011,
0.012726574204862118,
0.06142592057585716,
-0.11495199054479599,
0.09937658905982971,
0.012870636768639088,
-0.004057616461068392,
0.166650652885437,
-0.0004076457116752863,
-0.07127676159143448,
-0.06420327723026276,
-0.0747542679309845,
-0.021446911618113518,
0.09447984397411346,
-0.11176029592752457,
0.08143189549446106,
-0.014278407208621502,
-0.038768354803323746,
0.002094640163704753,
-0.1095178872346878,
-0.12445959448814392,
-0.19356580078601837,
0.06069660931825638,
-0.10815826058387756,
0.003831093432381749,
-0.09925412386655807,
-0.05358343943953514,
-0.04677683115005493,
0.20124182105064392,
-0.14483362436294556,
-0.09758627414703369,
-0.15289589762687683,
-0.09554614871740341,
0.1664566993713379,
-0.04663718119263649,
0.08821606636047363,
-0.0038687095511704683,
0.22914768755435944,
0.006724040023982525,
-0.012434800155460835,
0.07520399242639542,
-0.08637748658657074,
-0.17783690989017487,
-0.07604682445526123,
0.12165174633264542,
0.12136691808700562,
0.04747939854860306,
-0.012795967981219292,
0.021366307511925697,
-0.03262670710682869,
-0.1143370196223259,
0.008061125874519348,
0.12403146922588348,
0.05908475071191788,
0.04311663657426834,
0.00427021412178874,
-0.11007828265428543,
-0.07147429138422012,
-0.03523124009370804,
0.021944832056760788,
0.18807166814804077,
-0.08221416175365448,
0.15053938329219818,
0.12907743453979492,
-0.05370299890637398,
-0.21416690945625305,
0.03436880186200142,
0.04090806469321251,
0.00472818361595273,
0.053175248205661774,
-0.1770489513874054,
0.07840683311223984,
0.024572648108005524,
-0.05139078199863434,
0.15225622057914734,
-0.1677834391593933,
-0.1536329686641693,
0.0777980238199234,
0.05417194589972496,
-0.21989625692367554,
-0.12022100389003754,
-0.08520790934562683,
-0.06769770383834839,
-0.14243635535240173,
0.08412115275859833,
0.020698823034763336,
0.00019321028958074749,
0.04856256768107414,
0.034081753343343735,
0.019389502704143524,
-0.04823823645710945,
0.21962693333625793,
-0.009151222184300423,
0.036160267889499664,
-0.07677234709262848,
-0.09645134955644608,
0.07220485061407089,
-0.054490040987730026,
0.08667207509279251,
-0.024035243317484856,
0.007558862213045359,
-0.07708337903022766,
-0.05522387474775314,
-0.051626816391944885,
0.029731709510087967,
-0.07851403951644897,
-0.1059325784444809,
-0.0698300376534462,
0.09317977726459503,
0.09290435165166855,
-0.03390717878937721,
-0.03715480491518974,
-0.09010928869247437,
0.027843475341796875,
0.20326566696166992,
0.1706404834985733,
0.05219545215368271,
-0.10166811943054199,
0.0006855534156784415,
-0.017444688826799393,
0.04213650897145271,
-0.21454355120658875,
0.04805922508239746,
0.046434495598077774,
0.023125024512410164,
0.11990387737751007,
-0.016930051147937775,
-0.16412340104579926,
-0.04671873524785042,
0.056455835700035095,
-0.036497533321380615,
-0.20693081617355347,
-0.012548294849693775,
0.052488550543785095,
-0.18057814240455627,
-0.0640311911702156,
0.01719793491065502,
-0.01455759722739458,
-0.024732910096645355,
0.013886804692447186,
0.06330747157335281,
0.027956031262874603,
0.09375539422035217,
0.05616210401058197,
0.10073219239711761,
-0.11451173573732376,
0.08603792637586594,
0.08968610316514969,
-0.09007474035024643,
0.0125290397554636,
0.0736992210149765,
-0.055889032781124115,
-0.02316245622932911,
0.020047122612595558,
0.06119868531823158,
-0.00162112049292773,
-0.061508238315582275,
-0.01975059136748314,
-0.11018196493387222,
0.06758071482181549,
0.13242226839065552,
0.04006093740463257,
-0.005321177653968334,
0.048064373433589935,
0.021657899022102356,
-0.0826604813337326,
0.11298491060733795,
0.025856876745820045,
0.038508445024490356,
-0.06642783433198929,
-0.023183433338999748,
0.045513976365327835,
0.008002778515219688,
-0.020539432764053345,
-0.02922571264207363,
-0.05385620519518852,
-0.011762911453843117,
-0.18990042805671692,
0.01677597686648369,
-0.0765504315495491,
0.004350012633949518,
0.014810539782047272,
-0.03814086318016052,
-0.020958559587597847,
0.016691848635673523,
-0.07982292026281357,
-0.05134430527687073,
-0.002734045498073101,
0.0985812395811081,
-0.13863937556743622,
0.007181720342487097,
0.08835478872060776,
-0.11878933757543564,
0.06740869581699371,
-0.024482958018779755,
-0.017330501228570938,
-0.0019446499645709991,
-0.12968114018440247,
0.04302144795656204,
0.002646980108693242,
0.01983785443007946,
0.042118169367313385,
-0.16895927488803864,
0.006406146101653576,
-0.04021742194890976,
-0.04932057484984398,
-0.01649690791964531,
-0.07501037418842316,
-0.11416008323431015,
0.11071296036243439,
0.0018048452911898494,
-0.07790763676166534,
-0.0117954695597291,
0.05156298726797104,
0.10936092585325241,
-0.037753306329250336,
0.1212289109826088,
0.0044145528227090836,
0.06474429368972778,
-0.18044467270374298,
-0.024778762832283974,
-0.015598369762301445,
0.006858370266854763,
0.02694357931613922,
-0.0140616400167346,
0.042949724942445755,
-0.013948258012533188,
0.2575705349445343,
-0.02087925560772419,
0.07440228760242462,
0.06519795209169388,
0.046770140528678894,
0.011650492437183857,
0.0869150459766388,
0.06678774207830429,
0.012648052535951138,
0.003416551509872079,
0.032283470034599304,
-0.031422972679138184,
-0.014915283769369125,
-0.1482047736644745,
0.07101717591285706,
0.1439564973115921,
0.08283385634422302,
0.012806775979697704,
0.06352550536394119,
-0.10048910230398178,
-0.10461166501045227,
0.08237126469612122,
-0.041638992726802826,
-0.0008007619762793183,
-0.058745238929986954,
0.1454916000366211,
0.15373669564723969,
-0.17184817790985107,
0.0812029168009758,
-0.0365472249686718,
-0.04692631587386131,
-0.110826775431633,
-0.16450464725494385,
-0.06572620570659637,
-0.02580863982439041,
-0.003703176509588957,
-0.05508402734994888,
0.06688077747821808,
0.11885157972574234,
-0.0016993435565382242,
-0.0014807049883529544,
0.10038914531469345,
-0.022431546822190285,
-0.02085503377020359,
0.03484790027141571,
0.04871930554509163,
0.036450520157814026,
-0.04567375034093857,
0.02037064917385578,
0.010481024160981178,
0.03885771334171295,
0.0584954097867012,
0.024686437100172043,
-0.03216709941625595,
0.015852995216846466,
-0.012883862480521202,
-0.10344603657722473,
0.023220296949148178,
-0.02661588042974472,
-0.07547900825738907,
0.12944786250591278,
0.03020857274532318,
0.016596315428614616,
-0.03272676467895508,
0.20282141864299774,
-0.07233016192913055,
-0.07228796184062958,
-0.14049077033996582,
0.11066530644893646,
-0.03675038740038872,
0.06309209764003754,
0.05746688321232796,
-0.11500853300094604,
-0.005017681512981653,
0.12902788817882538,
0.12829062342643738,
-0.03323068469762802,
0.0049867476336658,
0.026197774335741997,
0.00827173050493002,
-0.049032241106033325,
0.04763645678758621,
0.032188743352890015,
0.15468738973140717,
-0.07100655138492584,
0.07814180850982666,
-0.0005074164946563542,
-0.08921105414628983,
-0.03626048564910889,
0.1392250955104828,
0.0028979976195842028,
0.032514654099941254,
-0.06501611322164536,
0.1007646918296814,
-0.07232671231031418,
-0.22924686968326569,
0.04944430664181709,
-0.0780143067240715,
-0.1530541479587555,
-0.012732122093439102,
0.02754151076078415,
-0.013794543221592903,
0.02254127338528633,
0.061679136008024216,
-0.06457692384719849,
0.16001729667186737,
0.03501654788851738,
-0.08832933753728867,
-0.05492360517382622,
0.07016300410032272,
-0.1023297980427742,
0.29636111855506897,
0.011759842745959759,
0.032544128596782684,
0.10384590178728104,
-0.01977287232875824,
-0.1365358531475067,
0.029908113181591034,
0.09750298410654068,
-0.0958370491862297,
0.0666261613368988,
0.18576137721538544,
-0.01007252186536789,
0.10188479721546173,
0.07690271735191345,
-0.06373509019613266,
0.05595288425683975,
-0.08074036985635757,
-0.06501531600952148,
-0.0913926437497139,
0.0567726232111454,
-0.06534478068351746,
0.14360256493091583,
0.11906343698501587,
-0.03889768570661545,
-0.0050442758947610855,
-0.029765458777546883,
0.041717544198036194,
0.013438636437058449,
0.12334854900836945,
0.013119494542479515,
-0.1562117338180542,
0.029238002374768257,
0.003133314661681652,
0.10249229520559311,
-0.2173282951116562,
-0.08784149587154388,
0.04678759351372719,
-0.03227124735713005,
-0.05141454562544823,
0.1055324450135231,
0.06109399348497391,
0.05229108780622482,
-0.0470384918153286,
-0.05454113334417343,
-0.007119470275938511,
0.1505606472492218,
-0.11762657761573792,
-0.009603551588952541
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# emotion_classifier
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2783
- Accuracy: 0.5521
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 35 | 2.0697 | 0.2014 |
| No log | 2.0 | 70 | 2.0539 | 0.1875 |
| No log | 3.0 | 105 | 2.0278 | 0.2014 |
| No log | 4.0 | 140 | 1.9869 | 0.2639 |
| No log | 5.0 | 175 | 1.9248 | 0.2986 |
| No log | 6.0 | 210 | 1.8172 | 0.3403 |
| No log | 7.0 | 245 | 1.7661 | 0.375 |
| No log | 8.0 | 280 | 1.6933 | 0.4306 |
| No log | 9.0 | 315 | 1.6493 | 0.4514 |
| No log | 10.0 | 350 | 1.6028 | 0.4514 |
| No log | 11.0 | 385 | 1.5580 | 0.4444 |
| No log | 12.0 | 420 | 1.5267 | 0.5 |
| No log | 13.0 | 455 | 1.4934 | 0.4861 |
| No log | 14.0 | 490 | 1.4605 | 0.5208 |
| 1.6139 | 15.0 | 525 | 1.4499 | 0.5278 |
| 1.6139 | 16.0 | 560 | 1.4228 | 0.5347 |
| 1.6139 | 17.0 | 595 | 1.4109 | 0.5208 |
| 1.6139 | 18.0 | 630 | 1.3872 | 0.5139 |
| 1.6139 | 19.0 | 665 | 1.3640 | 0.5556 |
| 1.6139 | 20.0 | 700 | 1.3787 | 0.5208 |
| 1.6139 | 21.0 | 735 | 1.3820 | 0.5278 |
| 1.6139 | 22.0 | 770 | 1.3649 | 0.5069 |
| 1.6139 | 23.0 | 805 | 1.3508 | 0.5347 |
| 1.6139 | 24.0 | 840 | 1.3322 | 0.5417 |
| 1.6139 | 25.0 | 875 | 1.3577 | 0.5347 |
| 1.6139 | 26.0 | 910 | 1.3337 | 0.5625 |
| 1.6139 | 27.0 | 945 | 1.3578 | 0.5139 |
| 1.6139 | 28.0 | 980 | 1.3256 | 0.5556 |
| 0.8303 | 29.0 | 1015 | 1.3139 | 0.5833 |
| 0.8303 | 30.0 | 1050 | 1.3575 | 0.5139 |
| 0.8303 | 31.0 | 1085 | 1.3214 | 0.5625 |
| 0.8303 | 32.0 | 1120 | 1.3185 | 0.5486 |
| 0.8303 | 33.0 | 1155 | 1.3285 | 0.5417 |
| 0.8303 | 34.0 | 1190 | 1.3259 | 0.5903 |
| 0.8303 | 35.0 | 1225 | 1.3492 | 0.5556 |
| 0.8303 | 36.0 | 1260 | 1.3164 | 0.5764 |
| 0.8303 | 37.0 | 1295 | 1.3645 | 0.5417 |
| 0.8303 | 38.0 | 1330 | 1.3431 | 0.5347 |
| 0.8303 | 39.0 | 1365 | 1.3272 | 0.5278 |
| 0.8303 | 40.0 | 1400 | 1.3326 | 0.5972 |
| 0.8303 | 41.0 | 1435 | 1.3375 | 0.5486 |
| 0.8303 | 42.0 | 1470 | 1.3641 | 0.5556 |
| 0.3516 | 43.0 | 1505 | 1.3633 | 0.5278 |
| 0.3516 | 44.0 | 1540 | 1.3532 | 0.5278 |
| 0.3516 | 45.0 | 1575 | 1.3473 | 0.5903 |
| 0.3516 | 46.0 | 1610 | 1.3413 | 0.5833 |
| 0.3516 | 47.0 | 1645 | 1.4158 | 0.5556 |
| 0.3516 | 48.0 | 1680 | 1.3747 | 0.5903 |
| 0.3516 | 49.0 | 1715 | 1.4364 | 0.5347 |
| 0.3516 | 50.0 | 1750 | 1.4659 | 0.5417 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "emotion_classifier", "results": [{"task": {"type": "emotion-classifier", "name": "Emotion Classifier"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5520833333333334, "name": "Accuracy"}]}]}]} | image-classification | Hendrico/emotion_classifier | [
"transformers",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:17:14+00:00 | [] | [] | TAGS
#transformers #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| emotion\_classifier
===================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2783
* Accuracy: 0.5521
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant\_with\_warmup
* num\_epochs: 50
### Training results
### Framework versions
* Transformers 4.37.2
* Pytorch 2.2.0+cu121
* Datasets 2.16.1
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\\_with\\_warmup\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.2.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\\_with\\_warmup\n* num\\_epochs: 50",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.2.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
82,
105,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\\_with\\_warmup\n* num\\_epochs: 50### Training results### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.2.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
-0.11918340623378754,
0.13898758590221405,
-0.002430528402328491,
0.10803069174289703,
0.11799941211938858,
-0.008938218466937542,
0.166351318359375,
0.13371482491493225,
-0.11189015209674835,
0.06606516242027283,
0.15516597032546997,
0.12898296117782593,
0.03455652296543121,
0.21339905261993408,
-0.07260216772556305,
-0.21630851924419403,
0.0689384937286377,
0.030713018029928207,
0.005935944616794586,
0.1224670261144638,
0.08176631480455399,
-0.1385040432214737,
0.11960683763027191,
0.03078838437795639,
-0.19102983176708221,
-0.025400293990969658,
0.027282705530524254,
-0.07318565994501114,
0.10447494685649872,
0.020103702321648598,
0.07325737923383713,
0.052667926996946335,
0.04558437317609787,
-0.1467462033033371,
0.01213096920400858,
0.06695666909217834,
-0.02082274667918682,
0.08770357817411423,
0.03945191949605942,
-0.017818031832575798,
0.03401966765522957,
-0.08118253946304321,
0.04740682244300842,
0.018389053642749786,
-0.13019070029258728,
-0.2612886428833008,
-0.10820800811052322,
0.056935060769319534,
0.08693245053291321,
0.05981643497943878,
-0.006979899015277624,
0.21510455012321472,
-0.013684659264981747,
0.1036042720079422,
0.22527331113815308,
-0.31216955184936523,
-0.06658966094255447,
0.017867840826511383,
0.02395336888730526,
0.07803139090538025,
-0.08752264082431793,
0.008137905970215797,
0.040129076689481735,
0.02141733653843403,
0.1450384557247162,
-0.000040984061342896894,
0.003875565016642213,
-0.034353386610746384,
-0.11802303045988083,
-0.07908909022808075,
0.1888829916715622,
0.08579331636428833,
-0.06609931588172913,
-0.0713808536529541,
-0.08118858188390732,
-0.1481200009584427,
-0.06181367114186287,
-0.00231060734950006,
0.05854811891913414,
-0.03033125028014183,
-0.09890580177307129,
-0.008067168295383453,
-0.08154904842376709,
-0.054898060858249664,
-0.02419969253242016,
0.1488935947418213,
0.04802241548895836,
0.02571961097419262,
-0.036622025072574615,
0.07190520316362381,
-0.0731268972158432,
-0.16524215042591095,
-0.026340723037719727,
0.004005151335150003,
0.030355393886566162,
-0.04393313080072403,
-0.026979655027389526,
-0.12909823656082153,
0.01612909510731697,
0.14807330071926117,
-0.1091950312256813,
0.062346503138542175,
-0.03574476018548012,
0.038721129298210144,
-0.08724885433912277,
0.1757337898015976,
-0.03564421832561493,
0.02964347042143345,
0.04588368535041809,
0.10238170623779297,
0.0889081358909607,
-0.008741900324821472,
-0.10918093472719193,
0.04449424892663956,
0.14433543384075165,
0.00898429099470377,
-0.04004472494125366,
0.08007252961397171,
-0.06867445260286331,
-0.011419686488807201,
0.11887573450803757,
-0.07185249775648117,
0.025326702743768692,
-0.016925020143389702,
-0.043861910700798035,
-0.09471862763166428,
0.031092781573534012,
0.009384595789015293,
-0.002559200394898653,
0.054649244993925095,
-0.09537309408187866,
0.014563607051968575,
-0.05502748861908913,
-0.1195743978023529,
0.01218344271183014,
-0.10650181025266647,
0.01954835094511509,
-0.12666277587413788,
-0.1402391642332077,
0.005101343616843224,
0.06714947521686554,
-0.03932786360383034,
-0.03723478317260742,
-0.03338678926229477,
-0.10216478258371353,
0.03389814496040344,
0.004862294998019934,
0.010826611891388893,
-0.08343512564897537,
0.0858551636338234,
0.05761299654841423,
0.08737824112176895,
-0.03850496932864189,
0.028115253895521164,
-0.1070188656449318,
0.0699625238776207,
-0.25388115644454956,
0.044103484600782394,
-0.05047662556171417,
0.10859324783086777,
-0.10844085365533829,
-0.08996497839689255,
0.01932545006275177,
-0.04165941849350929,
0.08024799078702927,
0.12119803577661514,
-0.1531553566455841,
-0.04611220583319664,
0.18974485993385315,
-0.12142500281333923,
-0.1772433966398239,
0.12786227464675903,
-0.035312868654727936,
0.01261673029512167,
0.058074951171875,
0.21096637845039368,
0.04974545165896416,
-0.10938753187656403,
-0.02614939585328102,
-0.06305552273988724,
0.023414364084601402,
-0.03936091810464859,
0.07743173837661743,
0.02913302183151245,
0.020596357062458992,
0.007375041954219341,
-0.036635782569646835,
0.04852786660194397,
-0.07924854010343552,
-0.0864093229174614,
-0.06881237775087357,
-0.08393421024084091,
0.034919023513793945,
0.042152099311351776,
0.05253768339753151,
-0.13781006634235382,
-0.10214921832084656,
0.020457828417420387,
0.07648877054452896,
-0.07314535230398178,
0.024531029164791107,
-0.11967213451862335,
0.13760654628276825,
-0.10662052780389786,
0.00040233906474895775,
-0.1356949806213379,
-0.02390514872968197,
0.05167316645383835,
-0.01798427291214466,
-0.016134895384311676,
-0.09977147728204727,
0.07868190854787827,
0.08703051507472992,
-0.06654271483421326,
-0.08088642358779907,
-0.03104931302368641,
0.0189273152500391,
-0.09661216288805008,
-0.1995968222618103,
-0.027481254190206528,
-0.04248052090406418,
0.12125508487224579,
-0.1844436526298523,
0.04120772331953049,
0.08521497249603271,
0.11802763491868973,
0.0729672759771347,
-0.03155564144253731,
0.01471728552132845,
0.018870916217565536,
-0.041963983327150345,
-0.09500617533922195,
0.048132747411727905,
0.03316975757479668,
-0.06649793684482574,
0.0186137892305851,
-0.135397270321846,
0.19330815970897675,
0.14508172869682312,
0.014748256653547287,
-0.06866873800754547,
-0.010864179581403732,
-0.03720967471599579,
-0.02768290415406227,
-0.02812596596777439,
0.032664258033037186,
0.08090318739414215,
0.012414312921464443,
0.1468237340450287,
-0.11257216334342957,
-0.015501354821026325,
0.07184437662363052,
-0.043218642473220825,
-0.0413258895277977,
0.07196895033121109,
0.014149132184684277,
-0.20270144939422607,
0.14667712152004242,
0.17228740453720093,
-0.04756160080432892,
0.10480573773384094,
-0.05499058961868286,
-0.043904952704906464,
-0.0375685915350914,
0.031006744131445885,
0.044250234961509705,
0.14176033437252045,
-0.0903296172618866,
-0.013691245578229427,
0.020567160099744797,
0.0052332887426018715,
-0.027528338134288788,
-0.19060258567333221,
-0.002621218329295516,
0.04289142042398453,
-0.05056487396359444,
-0.03087337501347065,
-0.008897568099200726,
-0.0168210007250309,
0.08208931982517242,
0.016362927854061127,
-0.06587257981300354,
0.04894944280385971,
0.02545526809990406,
-0.05453494191169739,
0.18458351492881775,
-0.09553525596857071,
-0.17318634688854218,
-0.10983197391033173,
-0.049012307077646255,
-0.093790702521801,
0.022525859996676445,
0.08459150046110153,
-0.08381743729114532,
-0.0697316899895668,
-0.12098575383424759,
-0.06770379096269608,
0.05827878788113594,
0.030683664605021477,
0.03345037251710892,
-0.014492295682430267,
0.11491510272026062,
-0.08461105078458786,
-0.02895386889576912,
0.0025413178373128176,
0.021001549437642097,
0.08653156459331512,
0.00670322310179472,
0.12208829820156097,
0.06141749769449234,
-0.04553372040390968,
0.034923356026411057,
-0.015381153672933578,
0.27389973402023315,
-0.07745841890573502,
-0.009506977163255215,
0.14003436267375946,
0.01931028626859188,
0.08149728178977966,
0.14301127195358276,
0.03224891796708107,
-0.11892492324113846,
0.005616631358861923,
-0.004472719505429268,
-0.03462870419025421,
-0.15995648503303528,
-0.015013673342764378,
-0.028419464826583862,
-0.02252218872308731,
0.13101933896541595,
0.049123615026474,
0.031949423253536224,
0.08290650695562363,
-0.010683502070605755,
0.054438166320323944,
0.014087074436247349,
0.11729558557271957,
0.0847461149096489,
0.0674334242939949,
0.12447237968444824,
-0.04599685221910477,
-0.01613476686179638,
0.034166332334280014,
0.018703162670135498,
0.20227761566638947,
0.00445842370390892,
0.1673479825258255,
0.040381886065006256,
0.1819036602973938,
0.03461304306983948,
0.05403422191739082,
-0.01700502820312977,
-0.028895383700728416,
-0.013326368294656277,
-0.05384586378931999,
-0.04192719981074333,
0.04089638963341713,
-0.0648067370057106,
0.04851802811026573,
-0.09105521440505981,
0.06120006740093231,
0.0812547579407692,
0.29019078612327576,
0.0472259558737278,
-0.41555142402648926,
-0.112602598965168,
0.0044452352449297905,
-0.01404530182480812,
-0.06339254975318909,
-0.005918038543313742,
0.11641401797533035,
-0.04496088996529579,
0.08397365361452103,
-0.097105473279953,
0.0875098779797554,
-0.04226396605372429,
0.027723442763090134,
0.047109201550483704,
0.07745608687400818,
-0.010124145075678825,
0.037937603890895844,
-0.22683143615722656,
0.2668801546096802,
0.036970704793930054,
0.07655448466539383,
-0.04524841532111168,
0.0027670173440128565,
0.028938336297869682,
0.13953165709972382,
0.08638348430395126,
0.004195950925350189,
-0.05811239033937454,
-0.16328656673431396,
-0.10058776289224625,
0.005021321587264538,
0.06931894272565842,
0.006020928733050823,
0.09375107288360596,
-0.012286433950066566,
-0.020549746230244637,
0.0398351214826107,
-0.0031302575953304768,
-0.07869558781385422,
-0.07766751199960709,
-0.006316943094134331,
0.04971522092819214,
0.049625981599092484,
-0.09681212902069092,
-0.08927467465400696,
-0.07966997474431992,
0.152483731508255,
0.06019480526447296,
-0.05457010120153427,
-0.11350494623184204,
0.039221830666065216,
0.04177214950323105,
-0.08026020228862762,
0.06212160736322403,
-0.03322695940732956,
0.1420477032661438,
0.011380727402865887,
-0.05100376531481743,
0.12981413304805756,
-0.05835210904479027,
-0.17668549716472626,
-0.03953821584582329,
0.08429954200983047,
-0.015797661617398262,
0.024761220440268517,
0.012783958576619625,
0.05014549195766449,
-0.016220638528466225,
-0.05296463519334793,
0.05896713584661484,
-0.027064181864261627,
0.10296245664358139,
-0.0414549894630909,
0.019680801779031754,
0.01098086591809988,
-0.07052607089281082,
-0.016815781593322754,
0.1306440830230713,
0.3046446144580841,
-0.09031853824853897,
0.020431170240044594,
0.04487651586532593,
-0.014007813297212124,
-0.17125514149665833,
0.026590421795845032,
0.03420292213559151,
-0.014134528115391731,
0.011583227664232254,
-0.1382870227098465,
0.031209973618388176,
0.084258072078228,
-0.03676347807049751,
0.07107554376125336,
-0.24219158291816711,
-0.1248558759689331,
0.08935429900884628,
0.17970594763755798,
0.10284853726625443,
-0.1475001573562622,
-0.04529022425413132,
-0.040178172290325165,
-0.11983667314052582,
0.10161497443914413,
-0.10549814254045486,
0.09684501588344574,
-0.022133124992251396,
0.030443474650382996,
0.007008402608335018,
-0.062319569289684296,
0.14138029515743256,
-0.0450681671500206,
0.12481768429279327,
-0.07295413315296173,
0.02465103007853031,
0.11434753984212875,
-0.09872777760028839,
0.06875287741422653,
-0.11586230993270874,
0.07166816294193268,
-0.05583254247903824,
-0.0018525365740060806,
-0.05647074431180954,
0.003082028590142727,
-0.014286200515925884,
-0.02233201079070568,
-0.04542999342083931,
0.021216334775090218,
0.06454186886548996,
-0.016992615535855293,
0.231647789478302,
0.054040104150772095,
0.10407083481550217,
0.16819331049919128,
0.0700376108288765,
-0.15144415199756622,
-0.04528481513261795,
-0.0093470998108387,
-0.037771616131067276,
0.08213327080011368,
-0.1644715964794159,
0.06158711388707161,
0.08431640267372131,
-0.002997793024405837,
0.13366563618183136,
0.04410089552402496,
-0.040330566465854645,
0.027650712057948112,
0.07367287576198578,
-0.1775464415550232,
-0.14927290380001068,
-0.007376229390501976,
0.06101023033261299,
-0.10113690048456192,
0.07779177278280258,
0.11748906970024109,
-0.08086726814508438,
-0.008487269282341003,
-0.0026953837368637323,
0.028963269665837288,
0.0009327311418019235,
0.15280938148498535,
0.04534979164600372,
0.05608215555548668,
-0.1021900624036789,
0.09958308935165405,
0.04747791215777397,
-0.11238522827625275,
0.033440880477428436,
0.027173565700650215,
-0.12923453748226166,
-0.03998103737831116,
0.06329074501991272,
0.14494358003139496,
-0.012520917691290379,
-0.05933014675974846,
-0.1502426415681839,
-0.09684255719184875,
0.05668150633573532,
0.1582132875919342,
0.08046607673168182,
0.006731824949383736,
0.0049346936866641045,
-0.01625990867614746,
-0.10442238301038742,
0.10632692277431488,
0.03318312391638756,
0.10719530284404755,
-0.20014448463916779,
0.05051886662840843,
-0.0012657821644097567,
0.027866648510098457,
-0.018299361690878868,
0.021709203720092773,
-0.11073487251996994,
-0.0040163565427064896,
-0.11320909112691879,
0.046380117535591125,
-0.05772106721997261,
0.016476325690746307,
-0.015555900521576405,
-0.051455918699502945,
-0.06299235671758652,
0.029384836554527283,
-0.10827998071908951,
-0.03640374541282654,
0.04606233909726143,
0.04386119917035103,
-0.11702754348516464,
-0.02915371209383011,
0.018957605585455894,
-0.08868807554244995,
0.08637823909521103,
0.04017501696944237,
-0.012717329896986485,
0.0062254262156784534,
-0.041663262993097305,
-0.00754020269960165,
0.08960632234811783,
-0.007295546121895313,
0.04448869079351425,
-0.12361045181751251,
-0.006004753522574902,
0.017313484102487564,
-0.020089730620384216,
0.011235259473323822,
0.1620393991470337,
-0.11548664420843124,
-0.016568688675761223,
-0.010003750212490559,
-0.040731996297836304,
-0.05988997966051102,
0.06037838011980057,
0.10984550416469574,
-0.014685152098536491,
0.22342796623706818,
-0.08517474681138992,
-0.032120466232299805,
-0.1920565515756607,
-0.003222042229026556,
-0.0015859935665503144,
-0.16949208080768585,
-0.11688685417175293,
-0.016522318124771118,
0.05188059061765671,
-0.07807952165603638,
0.09679742157459259,
0.012439921498298645,
0.006774635054171085,
0.04598945006728172,
0.0032083538826555014,
-0.025033991783857346,
0.022989097982645035,
0.1645607203245163,
0.003816331271082163,
-0.027375254780054092,
0.07314598560333252,
0.018724873661994934,
0.10823003202676773,
0.06991096585988998,
0.11141049861907959,
0.1481664925813675,
-0.00015765598800498992,
0.1086304560303688,
0.03590940684080124,
-0.012483412399888039,
-0.17981386184692383,
0.070631243288517,
-0.07922472059726715,
0.14832304418087006,
-0.004792478866875172,
0.1459457129240036,
0.15094684064388275,
-0.14083808660507202,
0.021438919007778168,
-0.042780403047800064,
-0.07001886516809464,
-0.07154534757137299,
-0.12977929413318634,
-0.11947818100452423,
-0.1910979151725769,
0.01172989048063755,
-0.09302995353937149,
0.013453197665512562,
0.05925963073968887,
-0.010362079367041588,
-0.013835103251039982,
0.17468033730983734,
0.01956087164580822,
0.014287619851529598,
0.05149344727396965,
-0.011092407628893852,
-0.08557935804128647,
-0.011027054861187935,
-0.09903430938720703,
0.05299263820052147,
-0.01608862727880478,
0.03745884448289871,
-0.007343181874603033,
0.011183671653270721,
0.05147120729088783,
-0.005590931978076696,
-0.1280762106180191,
0.019904926419258118,
0.025300122797489166,
0.01245809905230999,
-0.0038659842684865,
0.00986564252525568,
0.020865026861429214,
0.002437965013086796,
0.18477436900138855,
-0.059536274522542953,
-0.03104178048670292,
-0.13058120012283325,
0.1860179752111435,
0.013321254402399063,
-0.02176935039460659,
0.02809121087193489,
-0.08974695950746536,
0.025786608457565308,
0.150010883808136,
0.15000849962234497,
-0.02091199718415737,
0.0037487114313989878,
-0.04949820786714554,
-0.01980818621814251,
-0.042831845581531525,
0.0809365063905716,
0.09744124859571457,
-0.08845418691635132,
-0.06033331900835037,
-0.01436494942754507,
-0.07695501297712326,
-0.0212696585804224,
-0.03558911010622978,
0.04136050119996071,
0.0026861734222620726,
0.011950134299695492,
-0.07180683314800262,
0.05242552235722542,
0.010415452532470226,
-0.03924702852964401,
0.07186682522296906,
-0.18778860569000244,
-0.13837359845638275,
-0.013839775696396828,
0.08374640345573425,
-0.00952850840985775,
0.036970462650060654,
-0.009470258839428425,
0.013351843692362309,
0.04378703981637955,
-0.021584276109933853,
-0.06382200866937637,
-0.10893499851226807,
0.06991489976644516,
-0.14393536746501923,
0.2405831217765808,
-0.025261450558900833,
-0.0017243375768885016,
0.12881942093372345,
0.01805088296532631,
-0.13134443759918213,
0.08094286918640137,
0.030773084610700607,
-0.05173252895474434,
0.008918628096580505,
0.11518943309783936,
-0.03112408146262169,
0.10791691392660141,
0.037232376635074615,
-0.0972011387348175,
-0.031242990866303444,
-0.08324100077152252,
-0.026714198291301727,
-0.03477660194039345,
-0.028910983353853226,
-0.047916002571582794,
0.11358756572008133,
0.1560327410697937,
-0.040682096034288406,
-0.005754303652793169,
-0.05695154145359993,
0.0413379892706871,
0.10399515181779861,
-0.049117084592580795,
-0.030005568638443947,
-0.25713637471199036,
0.02101816236972809,
0.07334823161363602,
0.006617045495659113,
-0.22124136984348297,
-0.09575066715478897,
-0.011301725171506405,
-0.03271509334445,
-0.08381639420986176,
0.08822277188301086,
0.125045508146286,
0.04551704227924347,
-0.07913587242364883,
-0.026011783629655838,
-0.0746893435716629,
0.1662844717502594,
-0.10913276672363281,
-0.08198157697916031
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | null | devlocalhost/blip2-opt-2.7b-xray-captions-adapters | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:20:17+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
31,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06646376848220825,
0.2168014943599701,
-0.00225935154594481,
0.023818302899599075,
0.1271018385887146,
-0.001635765191167593,
0.04218708351254463,
0.13324736058712006,
-0.020175931975245476,
0.11144465953111649,
0.046588581055402756,
0.09377603232860565,
0.09928803145885468,
0.18404334783554077,
0.04859916493296623,
-0.2059975117444992,
0.007056170143187046,
-0.09090408682823181,
0.014076028019189835,
0.1116579994559288,
0.13719257712364197,
-0.10291384905576706,
0.08272874355316162,
-0.04045208916068077,
-0.02019004337489605,
0.00012576708104461432,
-0.09259183704853058,
-0.07032395154237747,
0.06885425746440887,
0.06264153122901917,
0.051234472543001175,
0.001456156256608665,
0.09140396863222122,
-0.2864592671394348,
0.017265573143959045,
0.08406311273574829,
0.0027674848679453135,
0.06290827691555023,
0.07236549258232117,
-0.07389893382787704,
0.11328595131635666,
-0.08021481335163116,
0.13019037246704102,
0.08625296503305435,
-0.062064990401268005,
-0.23071379959583282,
-0.07525765895843506,
0.0963398814201355,
0.12251301854848862,
0.06215599179267883,
-0.022921854630112648,
0.15455181896686554,
-0.06248689442873001,
0.012971068732440472,
0.1294165402650833,
-0.11526761949062347,
-0.05572471022605896,
0.061741601675748825,
0.11775490641593933,
0.10740239918231964,
-0.14110268652439117,
-0.0017287094378843904,
0.04900608956813812,
0.029121357947587967,
0.08589313924312592,
0.022661056369543076,
0.12003941088914871,
0.04652795568108559,
-0.13695219159126282,
-0.04037507623434067,
0.12011898308992386,
0.038862764835357666,
-0.06446044892072678,
-0.2168138176202774,
-0.006778308190405369,
-0.0601806715130806,
-0.014732478186488152,
-0.07019448280334473,
0.039128515869379044,
-0.02470310963690281,
0.07317749410867691,
-0.04465159401297569,
-0.1063927412033081,
-0.0421026237308979,
0.0892222449183464,
0.07748593389987946,
0.011527054943144321,
-0.02519804798066616,
0.04627908393740654,
0.13455867767333984,
0.05402068421244621,
-0.10399353504180908,
-0.07017925381660461,
-0.06942764669656754,
-0.09420394152402878,
-0.04035796597599983,
0.056760527193546295,
0.031942449510097504,
0.02665667235851288,
0.22703726589679718,
0.016653569415211678,
0.04155244305729866,
0.0224777739495039,
0.01032855175435543,
0.043662428855895996,
0.0955500528216362,
-0.05303520709276199,
-0.15660029649734497,
-0.04072032496333122,
0.09077946096658707,
-0.0027527001220732927,
-0.036689214408397675,
-0.03966725245118141,
0.03849169611930847,
0.06843466311693192,
0.13122352957725525,
0.07552056759595871,
-0.017929591238498688,
-0.04813180863857269,
-0.030096933245658875,
0.23523783683776855,
-0.1493375599384308,
0.04426715523004532,
-0.02271856553852558,
-0.01804111897945404,
-0.03908449783921242,
0.03597262129187584,
0.022118929773569107,
-0.000004518366949923802,
0.09706240892410278,
-0.058981191366910934,
-0.05378659814596176,
-0.10168042778968811,
-0.03272576630115509,
0.04088849574327469,
-0.013975566253066063,
-0.010589460842311382,
-0.09025166928768158,
-0.09490354359149933,
-0.04766594246029854,
0.05537205561995506,
-0.05123869329690933,
-0.03770573064684868,
0.009465423412621021,
-0.08151785284280777,
-0.005444355774670839,
-0.005417742300778627,
0.10699385404586792,
-0.03222226724028587,
0.04445803165435791,
-0.027600755915045738,
0.05225523188710213,
0.09919606149196625,
0.031576547771692276,
-0.0773419588804245,
0.0561848059296608,
-0.22559374570846558,
0.07503069192171097,
-0.11481974273920059,
0.04335082694888115,
-0.1704932004213333,
-0.042439818382263184,
0.005444696638733149,
0.0139949731528759,
0.013206101022660732,
0.12720820307731628,
-0.19255615770816803,
-0.01654396951198578,
0.13260798156261444,
-0.09212633967399597,
-0.118110790848732,
0.07884611934423447,
-0.029701577499508858,
0.1624738723039627,
0.04682036489248276,
-0.027025915682315826,
0.09224298596382141,
-0.16434773802757263,
-0.07092688232660294,
-0.00949116237461567,
-0.01727987825870514,
0.12109188735485077,
0.07512219995260239,
-0.05991523340344429,
0.046571120619773865,
0.02832140028476715,
-0.038078423589468,
-0.04424772411584854,
-0.050857074558734894,
-0.10884185880422592,
-0.01070026308298111,
-0.08987759798765182,
0.04065500199794769,
-0.01250192429870367,
-0.07916021347045898,
-0.029885273426771164,
-0.18612512946128845,
-0.0030564051121473312,
0.10038342326879501,
0.0035033065360039473,
-0.005652366206049919,
-0.08666291832923889,
0.026358824223279953,
-0.03112892620265484,
-0.008404186926782131,
-0.16764774918556213,
-0.04399421438574791,
0.046902090311050415,
-0.16094985604286194,
0.020117372274398804,
-0.06413903087377548,
0.06334125250577927,
0.03641495108604431,
-0.05590536445379257,
-0.0248766727745533,
-0.01730942726135254,
0.011945613659918308,
-0.05083848536014557,
-0.18994836509227753,
-0.056277405470609665,
-0.037882111966609955,
0.149809330701828,
-0.25956398248672485,
0.032966937869787216,
0.051140617579221725,
0.14649195969104767,
0.00406361510977149,
-0.05115427449345589,
0.01429014839231968,
-0.05360214412212372,
-0.054652128368616104,
-0.06746816635131836,
-0.006135428790003061,
-0.027576493099331856,
-0.05147203803062439,
0.019243421033024788,
-0.1755700707435608,
-0.021410830318927765,
0.09424154460430145,
0.12876708805561066,
-0.1486445665359497,
-0.018640631809830666,
-0.048725154250860214,
-0.06339836865663528,
-0.0715010017156601,
-0.07038594037294388,
0.10712739825248718,
0.0513901449739933,
0.04796046018600464,
-0.07435787469148636,
-0.07092321664094925,
0.02726263552904129,
0.006906150374561548,
-0.03382374346256256,
0.08727246522903442,
0.05199531093239784,
-0.09209315478801727,
0.0756213590502739,
0.1092359870672226,
0.07177663594484329,
0.09363535046577454,
0.01574566215276718,
-0.11756632477045059,
-0.028492970392107964,
0.036266472190618515,
0.02740776725113392,
0.1465986967086792,
-0.05952361226081848,
0.04016614332795143,
0.04494241625070572,
-0.04170418903231621,
0.022319864481687546,
-0.08787637203931808,
0.024075502529740334,
0.025203049182891846,
-0.0034381982404738665,
0.06284574419260025,
-0.02525499276816845,
-0.0050758360885083675,
0.07016654312610626,
0.047779910266399384,
0.04621000960469246,
0.009655474685132504,
-0.01720241829752922,
-0.1047825813293457,
0.16950392723083496,
-0.0951867327094078,
-0.269941508769989,
-0.17632324993610382,
0.026197833940386772,
0.04035249724984169,
-0.022378476336598396,
0.031619444489479065,
-0.07056326419115067,
-0.10630585998296738,
-0.1060405746102333,
-0.002429972169920802,
0.01714223250746727,
-0.06364088505506516,
-0.0741225928068161,
0.07348573952913284,
0.04382912442088127,
-0.14902326464653015,
0.038552410900592804,
0.055694397538900375,
-0.057955220341682434,
-0.0233661737293005,
0.09118817001581192,
0.12397737801074982,
0.14583967626094818,
-0.021366750821471214,
-0.028626007959246635,
0.029004426673054695,
0.19620531797409058,
-0.13469526171684265,
0.10371150821447372,
0.13814030587673187,
-0.04545360431075096,
0.08360563963651657,
0.1560150384902954,
0.029186224564909935,
-0.08317049592733383,
0.05044832453131676,
0.04082648828625679,
-0.043159641325473785,
-0.2666129767894745,
-0.0534592866897583,
0.012832709588110447,
-0.06255637854337692,
0.09786593168973923,
0.10183793306350708,
0.11542957276105881,
0.034910861402750015,
-0.07166364789009094,
-0.043925940990448,
-0.0058974819257855415,
0.11737963557243347,
-0.05490213260054588,
-0.012639665976166725,
0.07686592638492584,
-0.05086168646812439,
0.005355054512619972,
0.10266812145709991,
0.02973790094256401,
0.17442677915096283,
0.020399179309606552,
0.11231429129838943,
0.06195578724145889,
0.08633565157651901,
0.0007386076031252742,
0.02951662428677082,
0.05147615820169449,
0.017203815281391144,
-0.002300140680745244,
-0.10421168059110641,
-0.006156572140753269,
0.1449710875749588,
0.028103826567530632,
0.029669636860489845,
-0.0018948549404740334,
-0.005003341939300299,
0.05121048167347908,
0.1746254414319992,
-0.011592294089496136,
-0.22072425484657288,
-0.0845772922039032,
0.06936841458082199,
-0.06218599155545235,
-0.12968985736370087,
-0.026130788028240204,
0.045467354357242584,
-0.17519839107990265,
0.026703642681241035,
-0.027433741837739944,
0.0919293761253357,
-0.09345759451389313,
-0.02221956104040146,
0.03687324374914169,
0.084866963326931,
-0.014529162086546421,
0.08703910559415817,
-0.14498743414878845,
0.11886418610811234,
0.02978132851421833,
0.09024628251791,
-0.11081171780824661,
0.07909037172794342,
-0.007550720125436783,
0.009180475026369095,
0.19379350543022156,
-0.011335089802742004,
-0.03514958545565605,
-0.08774717897176743,
-0.11210042238235474,
-0.013537433929741383,
0.12687496840953827,
-0.1243172138929367,
0.08773399889469147,
-0.015198243781924248,
-0.044079482555389404,
0.00937260314822197,
-0.12100647389888763,
-0.17273177206516266,
-0.19628387689590454,
0.05585884302854538,
-0.09575839340686798,
0.025643249973654747,
-0.11914430558681488,
-0.07089093327522278,
-0.02952558360993862,
0.241120383143425,
-0.1745356321334839,
-0.06510113179683685,
-0.1468164622783661,
-0.046294767409563065,
0.1662203073501587,
-0.04437198117375374,
0.0718095526099205,
-0.0208172257989645,
0.20345525443553925,
0.005988610442727804,
-0.004939318168908358,
0.06724198162555695,
-0.08892562240362167,
-0.16873881220817566,
-0.06771010160446167,
0.1510489284992218,
0.11680185794830322,
0.04907919466495514,
-0.002248800592496991,
0.0011772146681323647,
-0.016943959519267082,
-0.1137804463505745,
-0.0033210667315870523,
0.16037839651107788,
0.03878779336810112,
0.025986969470977783,
-0.05243593826889992,
-0.08797456324100494,
-0.06899320334196091,
-0.06853509694337845,
0.06221301481127739,
0.19590823352336884,
-0.10376439243555069,
0.1700313836336136,
0.147536963224411,
-0.07305635511875153,
-0.23175598680973053,
0.035342130810022354,
0.04983805492520332,
0.0014306638622656465,
0.04886869341135025,
-0.18252557516098022,
0.10521943867206573,
0.019543392583727837,
-0.05505957826972008,
0.13485197722911835,
-0.1557481735944748,
-0.1552847921848297,
0.0722852572798729,
0.03904085233807564,
-0.22423844039440155,
-0.1354004591703415,
-0.09622503817081451,
-0.05825018882751465,
-0.14065024256706238,
0.06054598465561867,
-0.002136280992999673,
0.015948504209518433,
0.03500790148973465,
-0.0015643214574083686,
0.027123261243104935,
-0.058935679495334625,
0.18609118461608887,
-0.004065449349582195,
0.020676052197813988,
-0.060264769941568375,
-0.0478842556476593,
0.09839435666799545,
-0.06130504235625267,
0.12208222597837448,
0.004057085141539574,
0.01594383642077446,
-0.10362856835126877,
-0.048314861953258514,
-0.04328322783112526,
0.05154227837920189,
-0.07548051327466965,
-0.10070807486772537,
-0.043625857681035995,
0.08841723203659058,
0.07005169242620468,
-0.03383097052574158,
0.00549331633374095,
-0.07189501076936722,
0.10019614547491074,
0.17795267701148987,
0.17573626339435577,
0.009926567785441875,
-0.07241068035364151,
0.01677953451871872,
-0.04142116755247116,
0.044231921434402466,
-0.2513144314289093,
0.03756171092391014,
0.06098250672221184,
0.029438555240631104,
0.09217222779989243,
-0.020435843616724014,
-0.1820858269929886,
-0.04050002992153168,
0.08094815909862518,
-0.05452597141265869,
-0.22617179155349731,
-0.019085140898823738,
0.0954197570681572,
-0.2020406424999237,
-0.007372708059847355,
0.03995226323604584,
-0.048725228756666183,
-0.023169852793216705,
0.00010950004070764408,
0.06317184865474701,
0.002471912419423461,
0.09773622453212738,
0.0735151618719101,
0.09715340286493301,
-0.08337292820215225,
0.10562895983457565,
0.10150538384914398,
-0.09572599828243256,
0.03605884686112404,
0.06754924356937408,
-0.05300498008728027,
-0.043293699622154236,
0.03665391728281975,
0.033023297786712646,
0.005234600510448217,
-0.060321882367134094,
0.013913018628954887,
-0.036497246474027634,
0.044923391193151474,
0.08326134830713272,
0.03754979372024536,
-0.013354414142668247,
0.06462216377258301,
0.03401726484298706,
-0.10898099094629288,
0.10366570204496384,
0.01731540448963642,
0.04105307161808014,
-0.08384523540735245,
-0.019968897104263306,
0.035425446927547455,
0.030576206743717194,
-0.01765924133360386,
-0.02306121215224266,
-0.02860277332365513,
-0.01614218018949032,
-0.14299540221691132,
-0.023106401786208153,
-0.07243485748767853,
0.006181265693157911,
0.014656842686235905,
-0.031884219497442245,
-0.011233693920075893,
0.02475680410861969,
-0.06979699432849884,
-0.07426341623067856,
-0.006949664559215307,
0.09833318740129471,
-0.15115703642368317,
0.008848577737808228,
0.06907843053340912,
-0.11088496446609497,
0.08190931379795074,
-0.008411259390413761,
0.016245156526565552,
0.022527478635311127,
-0.15448406338691711,
0.05601610988378525,
0.0008648968650959432,
0.01916889287531376,
0.025886621326208115,
-0.16471809148788452,
0.004104440100491047,
-0.04661374166607857,
-0.02149827405810356,
-0.00004464812809601426,
-0.02647159807384014,
-0.12325995415449142,
0.06858719140291214,
-0.015622655861079693,
-0.035931166261434555,
-0.02701525390148163,
0.0539589487016201,
0.07888586074113846,
-0.027474910020828247,
0.10445091128349304,
-0.008690856397151947,
0.04941811040043831,
-0.16801609098911285,
-0.02470702864229679,
-0.04982255399227142,
0.019377702847123146,
0.009884213097393513,
-0.007693959400057793,
0.04183054715394974,
-0.00976533442735672,
0.21883612871170044,
-0.05075952783226967,
0.1607085019350052,
0.05847611650824547,
-0.017352959141135216,
-0.0007513365126214921,
0.06180921941995621,
0.05997028574347496,
0.04658793285489082,
0.009480604901909828,
0.023740366101264954,
-0.022450892254710197,
-0.006695089396089315,
-0.15932634472846985,
0.01890849508345127,
0.14999441802501678,
0.06301083415746689,
0.024745315313339233,
0.05866100639104843,
-0.12775006890296936,
-0.12135478109121323,
0.09311001747846603,
-0.026755332946777344,
0.00928465835750103,
-0.08245618641376495,
0.1358020007610321,
0.14980104565620422,
-0.14000412821769714,
0.05256148427724838,
-0.06134212389588356,
-0.05217423290014267,
-0.10388828068971634,
-0.12032219022512436,
-0.05887215584516525,
-0.053666237741708755,
0.002330566756427288,
-0.03760887682437897,
0.054546963423490524,
0.03344334661960602,
-0.009351172484457493,
-0.00022941511997487396,
0.13597318530082703,
-0.019751882180571556,
-0.0028988157864660025,
0.048313532024621964,
0.03693558648228645,
0.02373051457107067,
-0.05275435373187065,
0.02940409444272518,
0.02539868652820587,
0.032232340425252914,
0.06546790152788162,
0.033412106335163116,
-0.047448933124542236,
0.03804153576493263,
-0.0025254099164158106,
-0.11207924783229828,
0.019641218706965446,
-0.00460948096588254,
-0.0742158442735672,
0.1268945336341858,
0.0407399944961071,
0.010224059224128723,
-0.03741471841931343,
0.24361543357372284,
-0.06653323769569397,
-0.06378097087144852,
-0.13251738250255585,
0.10491154342889786,
-0.0027236645109951496,
0.06476365029811859,
0.023412218317389488,
-0.1284150779247284,
0.005243356805294752,
0.13858191668987274,
0.12181595712900162,
0.0045748427510261536,
0.009228081442415714,
0.0518609918653965,
0.0025186820421367884,
-0.06998204439878464,
0.054019294679164886,
0.06992026418447495,
0.12919506430625916,
-0.07847554981708527,
0.07680778950452805,
0.0006860480643808842,
-0.08370215445756912,
-0.02947772853076458,
0.11312682181596756,
-0.0409729965031147,
0.03491825982928276,
-0.047444481402635574,
0.10916327685117722,
-0.05787910893559456,
-0.29412412643432617,
0.02350960113108158,
-0.09588567912578583,
-0.15202060341835022,
-0.018367812037467957,
0.05944539234042168,
-0.02624768204987049,
0.018029648810625076,
0.06971040368080139,
-0.06011629104614258,
0.20098382234573364,
0.0335683599114418,
-0.07864278554916382,
-0.0664360448718071,
0.04837050288915634,
-0.06564252078533173,
0.2949807047843933,
0.008418165147304535,
0.02863333560526371,
0.10770907253026962,
-0.03253700211644173,
-0.18271861970424652,
0.010723991319537163,
0.1133992001414299,
-0.08056149631738663,
0.08200647681951523,
0.19000613689422607,
-0.012578671798110008,
0.1209007054567337,
0.05294662341475487,
-0.047376248985528946,
0.04217283055186272,
-0.03389401361346245,
-0.051268599927425385,
-0.10752558708190918,
0.058453381061553955,
-0.05909625440835953,
0.15447644889354706,
0.10152646154165268,
-0.05671518296003342,
-0.004550917539745569,
-0.05555408447980881,
0.04875178262591362,
0.01804669201374054,
0.12263146042823792,
0.02951994352042675,
-0.1865430772304535,
0.032826557755470276,
-0.01144319772720337,
0.10186848044395447,
-0.25588861107826233,
-0.08421015739440918,
0.08833149075508118,
-0.011924264021217823,
-0.05105875805020332,
0.10560628771781921,
0.057650718837976456,
0.04243382066488266,
-0.043439045548439026,
-0.10480839014053345,
-0.02186836116015911,
0.14663739502429962,
-0.1469624787569046,
-0.025013303384184837
] |
null | null | null |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
``` | {"license": "other", "tags": ["autotrain", "text-generation"], "widget": [{"text": "I love AutoTrain because "}]} | text-generation | InnerI/I-NousResearch-Yarn-Mistral-7b-128k | [
"tensorboard",
"safetensors",
"autotrain",
"text-generation",
"conversational",
"license:other",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:23:06+00:00 | [] | [] | TAGS
#tensorboard #safetensors #autotrain #text-generation #conversational #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
| [
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
"TAGS\n#tensorboard #safetensors #autotrain #text-generation #conversational #license-other #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.",
"# Usage"
] | [
41,
29,
3
] | [
"passage: TAGS\n#tensorboard #safetensors #autotrain #text-generation #conversational #license-other #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\nThis model was trained using AutoTrain. For more information, please visit AutoTrain.# Usage"
] | [
-0.027139926329255104,
0.05549413338303566,
-0.001086072763428092,
0.0458357073366642,
0.11233107000589371,
-0.03919310122728348,
0.25330719351768494,
0.05724795535206795,
-0.03235183656215668,
-0.07674083113670349,
0.18840105831623077,
0.18488869071006775,
-0.03171338140964508,
0.14625823497772217,
-0.03068830817937851,
-0.2556142807006836,
0.014358164742588997,
0.0045296261087059975,
0.09734679758548737,
0.10690443962812424,
0.13996313512325287,
-0.08409817516803741,
0.04779442772269249,
0.05504542589187622,
-0.21212154626846313,
0.03396059572696686,
0.07364731281995773,
-0.10847485810518265,
0.1812181919813156,
0.05314876511693001,
0.13394244015216827,
0.03942825272679329,
0.11810304969549179,
-0.10978661477565765,
0.027138201519846916,
0.02522261068224907,
-0.028195848688483238,
0.07583968341350555,
0.07542945444583893,
-0.032452408224344254,
0.0983496606349945,
0.17407329380512238,
0.1203153133392334,
0.04488663002848625,
-0.09238871932029724,
0.02062407322227955,
-0.012019496411085129,
0.01698697917163372,
0.1256086677312851,
0.10495282709598541,
-0.0233027134090662,
0.21972255408763885,
-0.12350398302078247,
0.09147249907255173,
-0.10042452067136765,
-0.2998514175415039,
-0.02898949384689331,
0.23076921701431274,
0.0885743498802185,
0.000009943089935404714,
-0.13909539580345154,
0.0714062973856926,
0.10903196036815643,
-0.008379057981073856,
0.06390078365802765,
-0.023791620507836342,
-0.04102479666471481,
-0.003995601553469896,
-0.09138286113739014,
0.03857232257723808,
0.16629371047019958,
-0.06115882471203804,
-0.0014376816106960177,
-0.14251862466335297,
-0.030591007322072983,
0.029780447483062744,
0.0014873158652335405,
-0.11689703911542892,
-0.027005087584257126,
0.09389875084161758,
-0.04272151365876198,
-0.06311851739883423,
-0.15389303863048553,
-0.0454421229660511,
-0.08688711374998093,
0.011851770803332329,
0.005009328946471214,
0.008037209510803223,
-0.11562680453062057,
0.08981089293956757,
0.009057710878551006,
-0.09574903547763824,
0.058846596628427505,
-0.08302060514688492,
0.004863778129220009,
-0.11868158727884293,
-0.01823366805911064,
-0.17185001075267792,
0.017361367121338844,
0.1743340939283371,
0.17856407165527344,
0.011556620709598064,
-0.08119673281908035,
0.05105486884713173,
0.027566175907850266,
0.10752616077661514,
0.03950304165482521,
-0.015383190475404263,
0.05597636103630066,
-0.033588800579309464,
-0.01045486144721508,
-0.043443288654088974,
-0.21071277558803558,
0.06327097117900848,
0.011061734519898891,
0.04313728213310242,
-0.0669732317328453,
0.0747966319322586,
-0.02011682465672493,
0.03054383210837841,
0.01818717271089554,
-0.02988259121775627,
0.049371398985385895,
-0.03925693407654762,
0.013712245039641857,
-0.0809786394238472,
0.032900117337703705,
0.10831229388713837,
0.026870984584093094,
0.09901712834835052,
-0.09215869009494781,
-0.021803077310323715,
-0.11723243445158005,
-0.058838676661252975,
0.01927344501018524,
-0.0007232280331663787,
0.04639449343085289,
-0.18217580020427704,
-0.24385316669940948,
-0.039855461567640305,
0.06950496137142181,
-0.03284268453717232,
-0.0660507082939148,
-0.08602586388587952,
0.010475946590304375,
0.05847384035587311,
-0.025249049067497253,
0.06053835526108742,
-0.006766340229660273,
0.02725645713508129,
-0.09177345037460327,
0.005915171932429075,
-0.06345934420824051,
0.0016364285256713629,
-0.10958781838417053,
-0.028317639604210854,
-0.023075606673955917,
0.019820749759674072,
-0.04484573379158974,
0.1346224695444107,
-0.015361327677965164,
0.05166352912783623,
-0.05846923962235451,
0.056585509330034256,
0.02016746811568737,
0.11968892812728882,
-0.16490231454372406,
-0.002552325837314129,
0.1652221381664276,
-0.10205310583114624,
-0.11537600308656693,
0.11744437366724014,
-0.10948594659566879,
0.23891519010066986,
0.09570688754320145,
0.15996620059013367,
0.029400693252682686,
-0.12259995192289352,
0.11311465501785278,
0.044385701417922974,
-0.08553649485111237,
-0.04975805804133415,
-0.01613697037100792,
-0.0187750943005085,
-0.15317568182945251,
0.013573155738413334,
0.14734122157096863,
0.07551421970129013,
-0.029119504615664482,
-0.08670662343502045,
-0.012989569455385208,
-0.05794382840394974,
0.04643617570400238,
0.02886943705379963,
0.13005796074867249,
-0.06525770574808121,
-0.0426858626306057,
0.0716388151049614,
0.03417434170842171,
0.04155395179986954,
-0.051185354590415955,
-0.08899204432964325,
-0.017478253692388535,
-0.04541110619902611,
-0.010380160994827747,
-0.08366479724645615,
-0.0700906440615654,
-0.022523561492562294,
0.11905723065137863,
0.04952830821275711,
0.1251334697008133,
0.049467846751213074,
0.027002273127436638,
-0.02090955153107643,
0.03143099695444107,
0.17509233951568604,
0.044941626489162445,
-0.13911008834838867,
-0.12228391319513321,
0.11367963999509811,
-0.08558206260204315,
0.12818413972854614,
-0.27459999918937683,
0.03262881562113762,
-0.08165117353200912,
0.09496741741895676,
0.0027740169316530228,
0.05194971710443497,
-0.0684652030467987,
0.01999986171722412,
-0.0958189070224762,
-0.01624615490436554,
0.07022757828235626,
0.06327712535858154,
-0.05662659928202629,
0.14026139676570892,
-0.17570924758911133,
0.19565783441066742,
0.11632779240608215,
-0.11043189465999603,
-0.10105086863040924,
-0.08642042428255081,
0.0036167094949632883,
-0.012462062761187553,
-0.09999484568834305,
0.0058722663670778275,
0.12042854726314545,
-0.03889302536845207,
0.17995381355285645,
-0.02769639901816845,
-0.03988126292824745,
-0.011288275942206383,
-0.0866771936416626,
-0.014757689088582993,
0.0010102991946041584,
0.11456076800823212,
-0.21932855248451233,
0.13577896356582642,
0.11419139057397842,
-0.051889847964048386,
0.22218789160251617,
0.025907613337039948,
0.024796508252620697,
-0.006247390992939472,
-0.028414150699973106,
0.009269235655665398,
0.05920398235321045,
-0.07477575540542603,
-0.027919800952076912,
0.003957283683121204,
-0.0092135826125741,
0.036593832075595856,
-0.14668212831020355,
-0.03666090592741966,
0.012492007575929165,
0.054741308093070984,
0.05988682061433792,
0.059844184666872025,
-0.09232781827449799,
0.07059172540903091,
-0.04286655783653259,
-0.13985447585582733,
0.1107911691069603,
0.0060933795757591724,
-0.12343225628137589,
0.1803586333990097,
-0.07787143439054489,
-0.19732743501663208,
-0.16621485352516174,
-0.11972853541374207,
0.014468242414295673,
0.07504851371049881,
0.04481320083141327,
-0.05905783176422119,
-0.05832948908209801,
-0.01938783936202526,
-0.13421949744224548,
0.0015642110956832767,
-0.025473810732364655,
-0.09767882525920868,
0.05334441736340523,
-0.009880103170871735,
-0.11362743377685547,
-0.033706214278936386,
-0.011477314867079258,
-0.06063736230134964,
0.04996487870812416,
-0.03063584864139557,
0.05468389019370079,
0.16709968447685242,
-0.014212493784725666,
0.026945235207676888,
-0.04314466938376427,
0.13374222815036774,
-0.09364467114210129,
0.027101639658212662,
0.07683544605970383,
-0.05926739051938057,
0.0322793610394001,
0.20565038919448853,
0.03931461274623871,
-0.06251461803913116,
0.05211615934967995,
-0.01300883013755083,
-0.07548793405294418,
-0.20642392337322235,
-0.08616714179515839,
-0.018872160464525223,
-0.004724911414086819,
0.0740182176232338,
0.06067976355552673,
0.27492231130599976,
0.13033071160316467,
0.08231183141469955,
0.0327739454805851,
0.031089577823877335,
0.07130683213472366,
0.10141957551240921,
-0.045351143926382065,
0.17327657341957092,
-0.07304312288761139,
-0.15891112387180328,
0.03544701635837555,
0.005132387857884169,
0.06854364275932312,
0.16671641170978546,
0.007023849990218878,
0.048709530383348465,
0.10315679013729095,
0.12708161771297455,
0.09641235321760178,
0.054253000766038895,
-0.07218553125858307,
-0.0012286589480936527,
-0.005305302795022726,
-0.026303669437766075,
0.1362561583518982,
-0.00046331988414749503,
-0.06845024228096008,
0.004173303488641977,
0.035755008459091187,
0.04544354975223541,
0.06030682846903801,
0.02706083655357361,
-0.2688038945198059,
0.03317579999566078,
0.03258064389228821,
-0.05240030959248543,
-0.10697153955698013,
0.08676817268133163,
0.03545473515987396,
-0.15415973961353302,
0.009957630187273026,
-0.05253329873085022,
0.07863115519285202,
0.011545667424798012,
0.04271426796913147,
-0.07402849197387695,
-0.04174455255270004,
-0.04944342002272606,
0.14203289151191711,
-0.36370033025741577,
0.21619655191898346,
-0.006830292288213968,
0.07295355945825577,
-0.11626013368368149,
0.008941524662077427,
0.08032336086034775,
0.13351061940193176,
0.1214267686009407,
-0.057370346039533615,
-0.15501785278320312,
-0.061875052750110626,
-0.10546572506427765,
-0.017368091270327568,
0.011643516831099987,
0.011438592337071896,
-0.015686411410570145,
-0.09938836097717285,
-0.0007191341137513518,
0.05575770139694214,
-0.031139280647039413,
-0.14712563157081604,
-0.17559047043323517,
-0.013708721846342087,
0.053798891603946686,
0.01039790641516447,
-0.02297559380531311,
-0.07223079353570938,
-0.07598548382520676,
0.18843905627727509,
0.017605016008019447,
0.010744013823568821,
-0.1267765909433365,
-0.0211129579693079,
-0.07204801589250565,
-0.023109255358576775,
0.0591631755232811,
0.010498205199837685,
0.1408766806125641,
-0.0984286293387413,
-0.06850062310695648,
0.11168986558914185,
-0.11995355039834976,
-0.0296772550791502,
-0.13311097025871277,
0.039311543107032776,
-0.013930300250649452,
0.0019760821014642715,
0.11339738965034485,
0.034697309136390686,
-0.065993532538414,
-0.06231782212853432,
-0.010306917130947113,
-0.01983947865664959,
0.004338997416198254,
-0.1453656256198883,
-0.10612037032842636,
-0.11072193831205368,
-0.02665124088525772,
-0.10663683712482452,
0.21942123770713806,
0.12710125744342804,
-0.09963835775852203,
0.1507042944431305,
0.19085004925727844,
-0.10560127347707748,
-0.3029433488845825,
-0.03758569061756134,
-0.03614523634314537,
0.01042028795927763,
0.052465375512838364,
-0.10016904771327972,
0.10020822286605835,
-0.004682690836489201,
-0.09071888029575348,
-0.012875484302639961,
-0.1332244724035263,
-0.16934457421302795,
0.2425684779882431,
0.027740225195884705,
0.18792714178562164,
-0.08958053588867188,
-0.05931283161044121,
-0.08887685835361481,
0.07167080044746399,
0.07230978459119797,
-0.10829314589500427,
0.052640654146671295,
0.06571503728628159,
0.06849011033773422,
0.03001396730542183,
-0.046969201415777206,
0.04856084659695625,
-0.0685959905385971,
0.06622105091810226,
-0.16036126017570496,
-0.04903446137905121,
0.05513772740960121,
-0.027114855125546455,
0.08837562054395676,
-0.045733582228422165,
0.023816362023353577,
-0.049519676715135574,
-0.06783362478017807,
0.016798026859760284,
0.06947769224643707,
-0.010557430796325207,
-0.11664488166570663,
-0.0023799410555511713,
-0.0001851402485044673,
0.003798362798988819,
-0.056741535663604736,
0.06440608948469162,
-0.024307509884238243,
0.16197754442691803,
0.18213209509849548,
0.22810977697372437,
-0.06883032619953156,
0.035292305052280426,
-0.028084218502044678,
-0.11230967938899994,
0.0835658609867096,
-0.05905301868915558,
0.007088550366461277,
0.06093867868185043,
-0.04436035454273224,
0.15304213762283325,
0.06302426010370255,
-0.023623578250408173,
-0.014216885901987553,
0.14470265805721283,
-0.16506865620613098,
-0.01060457993298769,
-0.06767161190509796,
0.1326562762260437,
0.04198072478175163,
-0.009442887268960476,
0.11170413345098495,
-0.0699271634221077,
-0.015712426975369453,
0.028324346989393234,
0.0006050282390788198,
-0.02406279183924198,
0.06398393213748932,
0.05348778888583183,
0.0234637763351202,
-0.05472220480442047,
0.025176841765642166,
0.0722203329205513,
-0.03072275035083294,
0.06242464855313301,
0.007681041024625301,
-0.07700609415769577,
-0.10173168778419495,
0.03668944537639618,
0.2752801775932312,
-0.15260876715183258,
-0.09022942930459976,
-0.01293264701962471,
-0.09389843791723251,
-0.0022608607541769743,
0.11169756948947906,
0.07335275411605835,
0.029061542823910713,
-0.060580506920814514,
-0.01626879908144474,
-0.12279229611158371,
0.1050315797328949,
-0.01852598413825035,
0.04680366814136505,
-0.15155616402626038,
0.0745868980884552,
-0.017912980169057846,
-0.0077625419944524765,
-0.09016294777393341,
-0.021869845688343048,
-0.13424256443977356,
0.02158970944583416,
-0.07701745629310608,
-0.03308233991265297,
-0.0459207147359848,
-0.022100694477558136,
0.06900330632925034,
-0.007899959571659565,
-0.02777872420847416,
-0.02411218360066414,
-0.08961070328950882,
0.042163655161857605,
0.014423605985939503,
0.030176332220435143,
-0.044656362384557724,
-0.02405896596610546,
0.01923391781747341,
-0.004822327755391598,
0.05716795101761818,
-0.0010958941420540214,
-0.010174169205129147,
0.030106110498309135,
-0.16514046490192413,
0.038273196667432785,
0.06191452965140343,
0.011508648283779621,
0.02424795925617218,
-0.021737953647971153,
-0.0018561079632490873,
0.09054802358150482,
0.04585824906826019,
0.03687870502471924,
0.011025887914001942,
-0.0873480960726738,
0.048339005559682846,
0.06997828185558319,
-0.1324043571949005,
-0.036405570805072784,
-0.017806943506002426,
-0.017597384750843048,
-0.030787678435444832,
0.2054802030324936,
-0.11842762678861618,
0.04016297683119774,
-0.05013446509838104,
0.04507654905319214,
-0.03293733298778534,
-0.09565191715955734,
-0.05252337083220482,
-0.09204892069101334,
-0.02712174877524376,
-0.020230986177921295,
0.25583967566490173,
0.15121719241142273,
-0.0226773489266634,
0.04129955545067787,
0.04341581091284752,
0.0822424590587616,
0.007453450001776218,
0.18559139966964722,
0.06772497296333313,
-0.0013120286166667938,
-0.12615074217319489,
0.07755409926176071,
0.03751662001013756,
-0.05538594350218773,
0.014171074144542217,
-0.010532640852034092,
-0.1126057505607605,
0.07215515524148941,
0.07383084297180176,
-0.028012176975607872,
-0.0910046175122261,
-0.11854562908411026,
-0.12325716763734818,
0.038516566157341,
-0.09675229340791702,
0.03040294535458088,
0.18707814812660217,
-0.05968274176120758,
-0.018261119723320007,
-0.06825742870569229,
-0.06702327728271484,
-0.21684440970420837,
-0.19894014298915863,
-0.10148875415325165,
-0.06482657790184021,
0.04089851677417755,
-0.026273420080542564,
0.0364372655749321,
0.01442588772624731,
0.06449200958013535,
-0.062291957437992096,
0.0987730547785759,
-0.09214674681425095,
0.025841906666755676,
0.0011953203938901424,
-0.02887633629143238,
0.00903320498764515,
-0.2084316611289978,
-0.0007441829657182097,
-0.14608801901340485,
-0.0058806356973946095,
-0.02894151583313942,
-0.04418741911649704,
0.026549741625785828,
-0.001695065526291728,
-0.011429454199969769,
-0.01772264763712883,
-0.010636563412845135,
0.027661345899105072,
0.028542719781398773,
0.056926626712083817,
0.021746328100562096,
0.004735887981951237,
0.02130277082324028,
0.19689784944057465,
-0.03654266148805618,
-0.14267215132713318,
-0.1396569460630417,
0.19610263407230377,
-0.0006993417046032846,
0.10599878430366516,
-0.07313507795333862,
-0.013131856918334961,
0.06016526371240616,
0.32045072317123413,
0.27119672298431396,
-0.05262213200330734,
0.010116464458405972,
-0.017002223059535027,
-0.008013651706278324,
-0.028321655467152596,
0.16524869203567505,
-0.0001161322943517007,
0.19725893437862396,
-0.06469258666038513,
0.013387450948357582,
-0.014107211492955685,
-0.08006207644939423,
-0.06046360358595848,
0.12547224760055542,
-0.00986608024686575,
-0.003953396342694759,
-0.01878383383154869,
0.07922805100679398,
-0.07593490183353424,
0.11825694143772125,
-0.1079479455947876,
-0.05408896505832672,
-0.06810387969017029,
0.048589129000902176,
0.1347869485616684,
-0.03979865461587906,
0.04452402517199516,
-0.03259386122226715,
-0.015653783455491066,
0.013312606140971184,
-0.04531089961528778,
-0.09555462747812271,
0.006992687471210957,
0.06398781388998032,
-0.022717608138918877,
0.24616771936416626,
-0.02360832318663597,
0.05345937982201576,
0.09784020483493805,
0.0065172514878213406,
-0.0765647366642952,
0.09085403382778168,
0.0050888159312307835,
-0.053313564509153366,
0.1124519407749176,
0.0035579963587224483,
0.006471545435488224,
-0.015531079843640327,
0.005561299156397581,
-0.15853364765644073,
0.1406017243862152,
-0.15508677065372467,
-0.09865288436412811,
-0.05270601063966751,
0.13324645161628723,
-0.02777857519686222,
0.1621675342321396,
0.05496421456336975,
-0.014418665319681168,
0.0035464121028780937,
-0.015237431973218918,
0.04721850901842117,
-0.0009800513507798314,
-0.0823616310954094,
-0.033644672483205795,
-0.18589724600315094,
-0.012747902423143387,
0.047270361334085464,
-0.026161834597587585,
-0.2605358064174652,
-0.07658558338880539,
-0.06751655787229538,
-0.04995943605899811,
-0.12565596401691437,
0.050980228930711746,
0.22033780813217163,
0.03622179850935936,
-0.022171910852193832,
-0.08444327861070633,
-0.016116393730044365,
0.01519850455224514,
-0.045565165579319,
-0.0974278599023819
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper large-v3 Bisyllabic Jyutping
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the AlienKevin/cantone dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2668
- eval_wer: 31.7361
- eval_runtime: 1403.0426
- eval_samples_per_second: 0.513
- eval_steps_per_second: 0.032
- epoch: 0.04
- step: 400
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- training_steps: 2400
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0
- Datasets 2.14.5
- Tokenizers 0.15.1
| {"language": ["yue"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "openai/whisper-large-v3", "model-index": [{"name": "Whisper large-v3 Bisyllabic Jyutping", "results": []}]} | automatic-speech-recognition | AlienKevin/whisper-large-v3-bisyllabic-jyutping | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"yue",
"base_model:openai/whisper-large-v3",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:36:50+00:00 | [] | [
"yue"
] | TAGS
#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #yue #base_model-openai/whisper-large-v3 #license-apache-2.0 #endpoints_compatible #region-us
|
# Whisper large-v3 Bisyllabic Jyutping
This model is a fine-tuned version of openai/whisper-large-v3 on the AlienKevin/cantone dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2668
- eval_wer: 31.7361
- eval_runtime: 1403.0426
- eval_samples_per_second: 0.513
- eval_steps_per_second: 0.032
- epoch: 0.04
- step: 400
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- training_steps: 2400
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0
- Datasets 2.14.5
- Tokenizers 0.15.1
| [
"# Whisper large-v3 Bisyllabic Jyutping\n\nThis model is a fine-tuned version of openai/whisper-large-v3 on the AlienKevin/cantone dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.2668\n- eval_wer: 31.7361\n- eval_runtime: 1403.0426\n- eval_samples_per_second: 0.513\n- eval_steps_per_second: 0.032\n- epoch: 0.04\n- step: 400",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1e-05\n- train_batch_size: 16\n- eval_batch_size: 16\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- lr_scheduler_warmup_steps: 400\n- training_steps: 2400",
"### Framework versions\n\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0\n- Datasets 2.14.5\n- Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #yue #base_model-openai/whisper-large-v3 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Whisper large-v3 Bisyllabic Jyutping\n\nThis model is a fine-tuned version of openai/whisper-large-v3 on the AlienKevin/cantone dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.2668\n- eval_wer: 31.7361\n- eval_runtime: 1403.0426\n- eval_samples_per_second: 0.513\n- eval_steps_per_second: 0.032\n- epoch: 0.04\n- step: 400",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1e-05\n- train_batch_size: 16\n- eval_batch_size: 16\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- lr_scheduler_warmup_steps: 400\n- training_steps: 2400",
"### Framework versions\n\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0\n- Datasets 2.14.5\n- Tokenizers 0.15.1"
] | [
75,
125,
6,
12,
8,
3,
104,
35
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #yue #base_model-openai/whisper-large-v3 #license-apache-2.0 #endpoints_compatible #region-us \n# Whisper large-v3 Bisyllabic Jyutping\n\nThis model is a fine-tuned version of openai/whisper-large-v3 on the AlienKevin/cantone dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.2668\n- eval_wer: 31.7361\n- eval_runtime: 1403.0426\n- eval_samples_per_second: 0.513\n- eval_steps_per_second: 0.032\n- epoch: 0.04\n- step: 400## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 1e-05\n- train_batch_size: 16\n- eval_batch_size: 16\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- lr_scheduler_warmup_steps: 400\n- training_steps: 2400### Framework versions\n\n- Transformers 4.38.0.dev0\n- Pytorch 2.1.0\n- Datasets 2.14.5\n- Tokenizers 0.15.1"
] | [
-0.10106740891933441,
0.1742624044418335,
-0.004311452154070139,
0.07639868557453156,
0.11127658933401108,
-0.001657908782362938,
0.06751599162817001,
0.17554278671741486,
-0.04543784260749817,
0.10281194746494293,
0.05065314099192619,
0.02711804211139679,
0.0875554233789444,
0.1510293334722519,
-0.007143808528780937,
-0.18013305962085724,
-0.00022446623188443482,
-0.05070285499095917,
-0.02177705056965351,
0.08242331445217133,
0.10467924922704697,
-0.08311185985803604,
0.0471787229180336,
-0.009458359330892563,
-0.045703236013650894,
0.02551175095140934,
-0.062034107744693756,
-0.08205977827310562,
0.07665839046239853,
0.0028125797398388386,
0.02867302857339382,
0.008104357868432999,
0.0797768384218216,
-0.28701651096343994,
-0.016692133620381355,
0.07420413941144943,
0.04167779162526131,
0.06574823707342148,
0.08115831762552261,
-0.005223041400313377,
0.046323928982019424,
-0.19609428942203522,
0.0978170782327652,
0.05540101230144501,
-0.08015558123588562,
-0.23326261341571808,
-0.08944721519947052,
0.0782710462808609,
0.09056976437568665,
0.0925978422164917,
-0.014672189019620419,
0.15342190861701965,
-0.03605318069458008,
0.06342204660177231,
0.22515012323856354,
-0.2682432234287262,
-0.03857940435409546,
0.014735091477632523,
0.05415518581867218,
0.038776904344558716,
-0.10847537219524384,
-0.0007316473056562245,
0.04642859846353531,
0.017306789755821228,
0.08941318094730377,
0.006982604041695595,
-0.028412196785211563,
-0.00937612447887659,
-0.09209254384040833,
-0.061721526086330414,
0.17193427681922913,
0.05938732996582985,
-0.05475577712059021,
-0.1561027318239212,
-0.026762349531054497,
-0.08871600031852722,
-0.005497809499502182,
-0.036763522773981094,
0.03741264343261719,
-0.05131873860955238,
-0.04289056733250618,
-0.016688155010342598,
-0.08005738258361816,
-0.026084715500473976,
0.0527181513607502,
0.10117127746343613,
0.03610632196068764,
-0.005111115984618664,
0.0008596347761340439,
0.08914872258901596,
0.003983787260949612,
-0.16102266311645508,
-0.07551851868629456,
-0.00535723939538002,
-0.11112968623638153,
-0.05891582742333412,
-0.01208016462624073,
-0.012766707688570023,
0.013017823919653893,
0.19780239462852478,
-0.06525441259145737,
0.07977245002985,
0.03637580946087837,
-0.014515154995024204,
-0.010787335224449635,
0.1610681116580963,
-0.022123897448182106,
-0.1031019315123558,
-0.02837654948234558,
0.10111548751592636,
0.009622669778764248,
-0.016118498519062996,
-0.03412298858165741,
-0.035141196101903915,
0.08301188796758652,
0.09381299465894699,
0.0060538905672729015,
0.0036881135310977697,
-0.07476530969142914,
-0.017480328679084778,
0.013461089693009853,
-0.1546064019203186,
0.04724555462598801,
0.006020810920745134,
-0.08875507861375809,
-0.07182527333498001,
0.043065525591373444,
-0.010713722556829453,
-0.05134228989481926,
0.04483329504728317,
-0.03563398867845535,
-0.021455714479088783,
-0.047627393156290054,
-0.04783748835325241,
0.03978513926267624,
-0.055331308394670486,
0.005904615856707096,
-0.08013789355754852,
-0.1811102330684662,
-0.03929484635591507,
0.02732839435338974,
-0.07952369004487991,
-0.040454257279634476,
-0.02495424821972847,
-0.06850140541791916,
0.0039021323900669813,
-0.03006148152053356,
0.1024843230843544,
-0.04980058595538139,
0.054657258093357086,
0.008875492960214615,
0.04054577276110649,
0.1245686337351799,
0.04089595749974251,
-0.07901445031166077,
0.048102568835020065,
-0.07367789000272751,
0.12019804120063782,
-0.10987759381532669,
0.03537590801715851,
-0.16198518872261047,
-0.08269549906253815,
0.009399307891726494,
-0.029732925817370415,
0.0812268778681755,
0.14182350039482117,
-0.15576454997062683,
-0.026204649358987808,
0.14146338403224945,
-0.045572418719530106,
-0.11290242522954941,
0.10030710697174072,
-0.02106340229511261,
0.044726427644491196,
0.06799190491437912,
0.13092322647571564,
0.11845636367797852,
-0.1432548314332962,
-0.05684811621904373,
0.027297932654619217,
0.056666526943445206,
0.07255487143993378,
0.07941198348999023,
-0.031837016344070435,
0.10003714263439178,
0.016766652464866638,
-0.05027910694479942,
-0.00788146536797285,
-0.05635162442922592,
-0.09216912090778351,
-0.031773801892995834,
-0.07838644087314606,
0.03205659240484238,
0.018115781247615814,
0.01254603173583746,
-0.0892290398478508,
-0.13162127137184143,
0.03989506512880325,
0.12410392612218857,
-0.0324731282889843,
0.00637234328314662,
-0.10083601623773575,
0.00967557355761528,
-0.006590042728930712,
-0.004901244770735502,
-0.1672380417585373,
-0.062449611723423004,
0.05341459438204765,
-0.11348387598991394,
-0.009543446823954582,
0.01403708104044199,
0.08603771030902863,
0.0374494269490242,
-0.027100730687379837,
-0.03334955498576164,
-0.08118592947721481,
-0.013571355491876602,
-0.06781085580587387,
-0.15394625067710876,
-0.06870011985301971,
-0.03239860013127327,
0.20145012438297272,
-0.19482536613941193,
0.017374327406287193,
0.05557955801486969,
0.1346248984336853,
0.024141807109117508,
-0.06218470633029938,
0.02617056667804718,
0.0072029996663331985,
0.0049350811168551445,
-0.11701309680938721,
0.011349614709615707,
-0.000031657316867494956,
-0.09995783120393753,
-0.03101653791964054,
-0.15965521335601807,
0.018605723977088928,
0.0709378644824028,
0.11812309920787811,
-0.09026272594928741,
0.0006367124151438475,
-0.06282365322113037,
-0.04984242469072342,
-0.07110194116830826,
-0.02906663715839386,
0.21884354948997498,
0.04247842729091644,
0.10867176204919815,
-0.05507388710975647,
-0.10106316208839417,
-0.001040037372149527,
0.01029073353856802,
-0.014380070380866528,
0.11158693581819534,
-0.04024725407361984,
-0.07378344982862473,
0.05939120426774025,
0.08508901298046112,
0.02712399698793888,
0.129763662815094,
-0.05573830008506775,
-0.09878280758857727,
-0.030963938683271408,
0.06250237673521042,
0.028079280629754066,
0.10637260973453522,
-0.1000581607222557,
0.014055564068257809,
0.05322778597474098,
-0.0061969757080078125,
0.001469870563596487,
-0.12726108729839325,
0.0016744898166507483,
0.07119940966367722,
-0.03785953298211098,
0.0023484386038035154,
-0.04054928570985794,
0.026600651443004608,
0.05263502895832062,
0.025868650525808334,
0.016948489472270012,
0.006548313423991203,
-0.02920551411807537,
-0.07946464419364929,
0.16104792058467865,
-0.09436352550983429,
-0.16791969537734985,
-0.11764918267726898,
0.03905677795410156,
-0.023343637585639954,
-0.020626237615942955,
0.031099725514650345,
-0.08964215964078903,
-0.08120808750391006,
-0.0948137566447258,
0.0014293099520727992,
-0.03332918509840965,
-0.023561932146549225,
0.10421670228242874,
0.056048061698675156,
0.12995271384716034,
-0.13622575998306274,
0.015468105673789978,
0.022132668644189835,
-0.07040876895189285,
-0.010217981413006783,
0.05781599506735802,
0.07754351943731308,
0.06748882681131363,
-0.003965006675571203,
0.007662899326533079,
-0.03771445155143738,
0.2113053798675537,
-0.09084071964025497,
-0.013655000366270542,
0.1296328753232956,
0.004992763511836529,
0.058950815349817276,
0.11482242494821548,
0.008180572651326656,
-0.08299868553876877,
0.017130179330706596,
0.03983187675476074,
-0.026713615283370018,
-0.2679203748703003,
-0.012909729033708572,
-0.023344861343503,
-0.015639161691069603,
0.13380096852779388,
0.047557391226291656,
0.014361627399921417,
0.04796592518687248,
-0.05923642963171005,
0.050787318497896194,
0.0020757734309881926,
0.09564057737588882,
0.06616219878196716,
0.043068401515483856,
0.07538508623838425,
-0.03530660271644592,
0.002111436566337943,
0.05403922498226166,
0.023437954485416412,
0.22133377194404602,
-0.03350227698683739,
0.192669078707695,
0.008763345889747143,
0.1311357021331787,
-0.06465782970190048,
0.03696245327591896,
0.022852225229144096,
0.008963162079453468,
0.02127133123576641,
-0.08447612076997757,
-0.05001186951994896,
0.07491476088762283,
-0.012063794769346714,
0.03956236317753792,
-0.06283720582723618,
0.06903279572725296,
0.042945850640535355,
0.22425587475299835,
0.053891777992248535,
-0.26859909296035767,
-0.08246123790740967,
0.03698863461613655,
-0.037218913435935974,
-0.06210470572113991,
-0.020329860970377922,
0.1311606913805008,
-0.13958483934402466,
0.08476033061742783,
-0.0303973276168108,
0.0818905308842659,
-0.07216376066207886,
-0.0012177061289548874,
0.029438480734825134,
0.08601056784391403,
0.02040764130651951,
0.09309889376163483,
-0.16676868498325348,
0.18069645762443542,
0.017473267391324043,
0.12422721832990646,
-0.07800472527742386,
0.079254150390625,
0.0015559190651401877,
-0.018654469400644302,
0.1472627818584442,
-0.005570186767727137,
-0.035346869379282,
-0.1665906459093094,
-0.10331303626298904,
0.011139465495944023,
0.10526154935359955,
-0.08473773300647736,
0.1013958603143692,
-0.02512003853917122,
-0.014812120236456394,
0.014075955376029015,
-0.04203251376748085,
-0.14237067103385925,
-0.14133581519126892,
0.04738624021410942,
0.005000357981771231,
-0.0001600008545210585,
-0.0965893492102623,
-0.0840548723936081,
-0.07614744454622269,
0.17316073179244995,
-0.07356246560811996,
-0.08660319447517395,
-0.14416725933551788,
0.060063254088163376,
0.15165039896965027,
-0.07497670501470566,
0.022007623687386513,
0.03524305671453476,
0.1457110047340393,
0.016102761030197144,
-0.027784181758761406,
0.042569372802972794,
-0.06884730607271194,
-0.16820143163204193,
-0.0472860150039196,
0.15619176626205444,
0.018632544204592705,
0.06329246610403061,
0.01857774704694748,
0.0062866308726370335,
0.019353099167346954,
-0.07264372706413269,
0.01669824868440628,
0.048444513231515884,
0.028094859793782234,
0.021123455837368965,
-0.02080134116113186,
-0.019208965823054314,
-0.07838212698698044,
-0.021638857200741768,
0.11230803281068802,
0.28251853585243225,
-0.0857171043753624,
0.10370970517396927,
0.03682688996195793,
-0.06773553043603897,
-0.15102551877498627,
0.019286584109067917,
0.11086884886026382,
0.019228387624025345,
0.09019437432289124,
-0.17642150819301605,
0.07504068315029144,
0.08985298126935959,
-0.02045286074280739,
0.04259432479739189,
-0.2943163514137268,
-0.13511860370635986,
0.03718883544206619,
0.06760997325181961,
-0.03340941295027733,
-0.12636606395244598,
-0.0767301693558693,
-0.03236837312579155,
-0.14658045768737793,
-0.008992553688585758,
-0.06829671561717987,
0.09695321321487427,
0.0024123378098011017,
0.03660758212208748,
0.0485166497528553,
-0.04279744625091553,
0.16955068707466125,
0.03560902178287506,
0.05827859416604042,
-0.06918056309223175,
0.07626122236251831,
0.10850211977958679,
-0.09192030876874924,
0.09316559880971909,
-0.07020353525876999,
0.04478908330202103,
-0.16373682022094727,
-0.023646796122193336,
-0.04592232406139374,
0.06319214403629303,
-0.056120917201042175,
-0.0533951036632061,
-0.010933605954051018,
0.04536070674657822,
0.08908479660749435,
-0.017588606104254723,
0.048326630145311356,
0.025699814781546593,
0.052307672798633575,
0.1416575312614441,
0.08914969116449356,
0.0172463096678257,
-0.13514713943004608,
0.005410093814134598,
-0.003936830908060074,
0.04831019788980484,
-0.15878556668758392,
0.04021667689085007,
0.10668912529945374,
0.048092424869537354,
0.11557701230049133,
0.0005492711206898093,
-0.09951614588499069,
0.006503331940621138,
0.03137866035103798,
-0.06361664831638336,
-0.16169025003910065,
-0.000296221231110394,
0.02985728532075882,
-0.1511489897966385,
-0.005213384982198477,
0.12239531427621841,
-0.051590695977211,
-0.0071271187625825405,
-0.029388802126049995,
0.0208382960408926,
0.0053588468581438065,
0.18986767530441284,
0.009924099780619144,
0.09790857136249542,
-0.07218747586011887,
0.13372978568077087,
0.08544241636991501,
-0.053453970700502396,
0.08188767731189728,
0.054794006049633026,
-0.06914740800857544,
-0.0170213021337986,
0.019602838903665543,
0.063506118953228,
0.0562339723110199,
-0.03230127692222595,
-0.060129664838314056,
-0.08030051738023758,
0.045727021992206573,
0.02519979141652584,
0.027490967884659767,
-0.00031318096444010735,
0.016002850607037544,
0.010598652064800262,
-0.12287643551826477,
0.10705740004777908,
0.06284225732088089,
0.03790444880723953,
-0.13071779906749725,
0.09217695891857147,
0.007353715132921934,
0.011694969609379768,
0.005374102853238583,
0.001946532167494297,
-0.04671154543757439,
0.0038245145697146654,
-0.14213286340236664,
-0.00272746873088181,
-0.03395252674818039,
-0.0030086487531661987,
-0.021546266973018646,
-0.027369888499379158,
-0.025897622108459473,
0.08218309283256531,
-0.06790183484554291,
-0.10702783614397049,
-0.011646728031337261,
0.08728256076574326,
-0.14315900206565857,
-0.037219271063804626,
0.03407029062509537,
-0.1354508101940155,
0.09099844098091125,
0.03960510343313217,
0.008243287913501263,
-0.016477681696414948,
-0.07871994376182556,
-0.02422817423939705,
0.01973274163901806,
0.03104168362915516,
0.058095961809158325,
-0.12402507662773132,
-0.009045655839145184,
-0.0466151125729084,
-0.003340410068631172,
0.008244671858847141,
0.013586273416876793,
-0.1271478235721588,
-0.03206693008542061,
-0.030006341636180878,
-0.03174569830298424,
-0.033348266035318375,
0.04453795403242111,
0.08361926674842834,
-0.002321563195437193,
0.1426287293434143,
-0.05034644529223442,
0.05474991351366043,
-0.2153547704219818,
-0.04067438840866089,
-0.007304190192371607,
-0.015252155251801014,
-0.05155294016003609,
-0.01869064010679722,
0.09184776991605759,
-0.045062463730573654,
0.09322940558195114,
-0.034855298697948456,
0.12668941915035248,
0.051307640969753265,
-0.07252657413482666,
0.0029229260981082916,
0.011271856725215912,
0.17377324402332306,
0.06777200102806091,
-0.0018801982514560223,
0.0780443623661995,
-0.04333443194627762,
0.0808744952082634,
-0.008744657039642334,
0.0765439122915268,
0.19265742599964142,
0.01665477268397808,
0.06508684903383255,
0.04695962369441986,
-0.11720623821020126,
-0.17340025305747986,
0.09737192094326019,
-0.04205767810344696,
0.1099507063627243,
-0.05347539484500885,
0.07712281495332718,
0.1073647141456604,
-0.1645895093679428,
0.0513477623462677,
-0.07268299162387848,
-0.0755028948187828,
-0.07901281118392944,
-0.04809469357132912,
-0.0786462351679802,
-0.09373745322227478,
0.04615003988146782,
-0.0881185457110405,
0.02423929236829281,
0.09554523974657059,
0.008961617946624756,
0.015526085160672665,
0.15593035519123077,
-0.03795519843697548,
-0.009489739313721657,
0.08428756147623062,
-0.0014556110836565495,
-0.007447611074894667,
-0.02340039052069187,
-0.03857782110571861,
0.06228109821677208,
0.029842881485819817,
0.09314318746328354,
-0.013703127391636372,
0.009028641507029533,
0.02362101897597313,
0.006832271348685026,
-0.10488054901361465,
0.008447092026472092,
0.009220120497047901,
0.0060025486163794994,
0.05753735452890396,
0.06155124306678772,
0.027069104835391045,
-0.04483673721551895,
0.2605041265487671,
-0.05888252332806587,
-0.08099272102117538,
-0.13673463463783264,
0.08643314242362976,
0.07208961993455887,
0.0029444049578160048,
0.0510404109954834,
-0.13311849534511566,
0.00507391570135951,
0.10825518518686295,
0.08859459310770035,
-0.006718956399708986,
-0.016178298741579056,
-0.020326199010014534,
-0.010386434383690357,
-0.07068239897489548,
0.06519002467393875,
0.08444561064243317,
-0.019107526168227196,
-0.054267678409814835,
0.03817847743630409,
0.033233072608709335,
-0.06286118924617767,
-0.09665340930223465,
0.06805764138698578,
-0.02563682571053505,
0.034577205777168274,
-0.030865784734487534,
0.06986384093761444,
0.01554832886904478,
-0.22625979781150818,
0.06450099498033524,
-0.17639906704425812,
-0.17554457485675812,
-0.006425840780138969,
0.11765020340681076,
0.011029859073460102,
0.06725797057151794,
0.025789136067032814,
-0.003614965593442321,
0.1501762419939041,
-0.006335021462291479,
-0.043160371482372284,
-0.073695607483387,
0.06128033250570297,
-0.07193386554718018,
0.25483959913253784,
-0.006226510740816593,
0.05072314292192459,
0.1034838855266571,
-0.005529562011361122,
-0.18363617360591888,
0.004644129890948534,
0.10188589245080948,
-0.05202154815196991,
0.04479117691516876,
0.17803989350795746,
-0.0534985177218914,
0.1250573992729187,
0.07155616581439972,
-0.0966748297214508,
-0.044639188796281815,
0.030812013894319534,
0.024115802720189095,
-0.09626778215169907,
-0.0041194092482328415,
-0.03435014933347702,
0.13347940146923065,
0.1770341843366623,
-0.06260789930820465,
-0.020131710916757584,
-0.07163838297128677,
0.014961207285523415,
0.03882589563727379,
0.08906693011522293,
-0.02264426462352276,
-0.16533707082271576,
0.03071664087474346,
0.02348821610212326,
0.07029375433921814,
-0.2089279443025589,
-0.10838286578655243,
0.07514157146215439,
-0.05495080724358559,
-0.040967512875795364,
0.11021652072668076,
0.0705614984035492,
0.015288113616406918,
-0.030432280153036118,
-0.1586906462907791,
-0.023370809853076935,
0.13341014087200165,
-0.13680194318294525,
-0.04364671930670738
] |
null | null | transformers |
# **Finch 7b Merge**
## A SLERP merge of my two current fav 7B models
[macadeliccc/WestLake-7B-v2-laser-truthy-dpo](https://huggingface.co/macadeliccc/WestLake-7B-v2-laser-truthy-dpo) & [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B)
A set of GGUF quants of [Finch](https://huggingface.co/antiven0m/finch)
- [6bpw EXL2 Quant](https://huggingface.co/antiven0m/finch-6bpw-exl2)
## Settings
I reccomend using the **ChatML** format. As for samplers, I reccomend the following:
```yml
Temperature: 1.2
Min P: 0.2
Smoothing Factor: 0.2
```
## Mergekit Config
```yaml
base_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
dtype: float16
merge_method: slerp
parameters:
t:
- filter: self_attn
value: [0.0, 0.5, 0.3, 0.7, 1.0]
- filter: mlp
value: [1.0, 0.5, 0.7, 0.3, 0.0]
- value: 0.5
slices:
- sources:
- layer_range: [0, 32]
model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
- layer_range: [0, 32]
model: SanjiWatsuki/Kunoichi-DPO-v2-7B
``` | {"language": ["en"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["SanjiWatsuki/Kunoichi-DPO-v2-7B", "macadeliccc/WestLake-7B-v2-laser-truthy-dpo"]} | null | antiven0m/finch-gguf | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:SanjiWatsuki/Kunoichi-DPO-v2-7B",
"base_model:macadeliccc/WestLake-7B-v2-laser-truthy-dpo",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:41:09+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #mergekit #merge #en #base_model-SanjiWatsuki/Kunoichi-DPO-v2-7B #base_model-macadeliccc/WestLake-7B-v2-laser-truthy-dpo #license-cc-by-nc-4.0 #endpoints_compatible #region-us
|
!Finch
# Finch 7b Merge
## A SLERP merge of my two current fav 7B models
macadeliccc/WestLake-7B-v2-laser-truthy-dpo & SanjiWatsuki/Kunoichi-DPO-v2-7B
A set of GGUF quants of Finch
- 6bpw EXL2 Quant
## Settings
I reccomend using the ChatML format. As for samplers, I reccomend the following:
## Mergekit Config
| [
"# Finch 7b Merge",
"## A SLERP merge of my two current fav 7B models\n\nmacadeliccc/WestLake-7B-v2-laser-truthy-dpo & SanjiWatsuki/Kunoichi-DPO-v2-7B\n\nA set of GGUF quants of Finch\n\n- 6bpw EXL2 Quant",
"## Settings\nI reccomend using the ChatML format. As for samplers, I reccomend the following:",
"## Mergekit Config"
] | [
"TAGS\n#transformers #gguf #mergekit #merge #en #base_model-SanjiWatsuki/Kunoichi-DPO-v2-7B #base_model-macadeliccc/WestLake-7B-v2-laser-truthy-dpo #license-cc-by-nc-4.0 #endpoints_compatible #region-us \n",
"# Finch 7b Merge",
"## A SLERP merge of my two current fav 7B models\n\nmacadeliccc/WestLake-7B-v2-laser-truthy-dpo & SanjiWatsuki/Kunoichi-DPO-v2-7B\n\nA set of GGUF quants of Finch\n\n- 6bpw EXL2 Quant",
"## Settings\nI reccomend using the ChatML format. As for samplers, I reccomend the following:",
"## Mergekit Config"
] | [
88,
7,
74,
25,
6
] | [
"passage: TAGS\n#transformers #gguf #mergekit #merge #en #base_model-SanjiWatsuki/Kunoichi-DPO-v2-7B #base_model-macadeliccc/WestLake-7B-v2-laser-truthy-dpo #license-cc-by-nc-4.0 #endpoints_compatible #region-us \n# Finch 7b Merge## A SLERP merge of my two current fav 7B models\n\nmacadeliccc/WestLake-7B-v2-laser-truthy-dpo & SanjiWatsuki/Kunoichi-DPO-v2-7B\n\nA set of GGUF quants of Finch\n\n- 6bpw EXL2 Quant## Settings\nI reccomend using the ChatML format. As for samplers, I reccomend the following:## Mergekit Config"
] | [
-0.09173302352428436,
0.007430952973663807,
-0.001698715379461646,
0.03596866503357887,
0.01571897231042385,
0.04825347289443016,
0.052282627671957016,
0.10589247941970825,
0.06305781751871109,
-0.012817134149372578,
-0.022128673270344734,
0.1304464191198349,
0.10192430764436722,
0.2017737478017807,
-0.04236195236444473,
-0.24883578717708588,
0.053264789283275604,
0.07780769467353821,
-0.1349363774061203,
0.056580737233161926,
0.12101898342370987,
-0.03350688889622688,
0.10354021191596985,
0.06697627902030945,
-0.08905889838933945,
-0.021780746057629585,
-0.04710850119590759,
0.014334791339933872,
0.03963363543152809,
0.08080949634313583,
0.040414437651634216,
0.08743378520011902,
0.01422080397605896,
-0.08903264999389648,
0.02434685453772545,
-0.025815539062023163,
-0.02841944806277752,
0.04280603677034378,
0.053796567022800446,
0.01665133610367775,
0.11082438379526138,
-0.04773186147212982,
0.00993395783007145,
0.06894609332084656,
-0.11183960735797882,
-0.07790779322385788,
-0.1456858366727829,
0.06625857949256897,
0.12202639877796173,
0.042691294103860855,
-0.004608157090842724,
0.029748082160949707,
0.026059824973344803,
0.07771541178226471,
0.12330751866102219,
-0.27708670496940613,
-0.017773957923054695,
0.17888958752155304,
0.10750856250524521,
-0.02969352900981903,
-0.009407644160091877,
0.0015110909007489681,
0.0020782097708433867,
-0.05090392008423805,
-0.0332159548997879,
-0.07220752537250519,
0.21073293685913086,
-0.05118159204721451,
-0.11826593428850174,
-0.0003966026415582746,
0.1711713820695877,
0.059990957379341125,
-0.06380545347929001,
-0.03013734146952629,
-0.05354133993387222,
-0.024006344377994537,
-0.03486138582229614,
-0.05394551903009415,
-0.011222339235246181,
-0.014898394234478474,
0.020878350362181664,
-0.09279516339302063,
-0.032099273055791855,
-0.05555269122123718,
-0.10947952419519424,
0.12495013326406479,
0.01336530689150095,
0.04146121069788933,
-0.0294162780046463,
0.04183119907975197,
-0.12006665766239166,
-0.11395244300365448,
-0.06949394941329956,
-0.05147169157862663,
-0.08637794852256775,
-0.022120755165815353,
-0.06745290756225586,
-0.09169508516788483,
0.03268968686461449,
0.22781138122081757,
-0.027112111449241638,
0.03359775245189667,
0.0796831026673317,
0.006305110640823841,
0.022543692961335182,
0.011444066651165485,
-0.09975099563598633,
-0.06426987797021866,
0.02375209890305996,
-0.001958655659109354,
0.007991042919456959,
-0.02231922186911106,
-0.05640807002782822,
-0.04797189682722092,
-0.0582813024520874,
-0.023360390216112137,
0.0671541690826416,
0.02764752507209778,
-0.0785626769065857,
-0.11436944454908371,
0.2720683515071869,
-0.0711788684129715,
0.004186225589364767,
-0.030141813680529594,
-0.013812209479510784,
0.029814226552844048,
0.043425168842077255,
0.06353316456079483,
0.07761946320533752,
0.03579603508114815,
-0.06040734052658081,
-0.04509348049759865,
-0.009769240394234657,
-0.024800579994916916,
-0.00426675146445632,
-0.16210369765758514,
0.00631491094827652,
-0.10385247319936752,
-0.12947140634059906,
0.006115037016570568,
0.002897446509450674,
-0.0498640276491642,
-0.06694621592760086,
0.009243226610124111,
0.03023659624159336,
-0.0501474067568779,
0.028161752969026566,
0.06121068820357323,
-0.009104854427278042,
-0.03804280236363411,
0.029637157917022705,
0.09890400618314743,
-0.18564186990261078,
0.0180622860789299,
-0.06179582327604294,
0.08290739357471466,
-0.18597520887851715,
0.08406262844800949,
-0.08183682709932327,
0.04551015794277191,
-0.11811606585979462,
0.01292313914746046,
-0.02466142363846302,
-0.06261688470840454,
0.027891546487808228,
0.08802134543657303,
-0.14781363308429718,
-0.04392370581626892,
0.046710193157196045,
-0.12415392696857452,
-0.05866697430610657,
0.06495558470487595,
0.03271932899951935,
-0.011323538608849049,
0.04258725792169571,
0.1478293538093567,
0.1794041395187378,
-0.04227634146809578,
-0.04463706165552139,
0.012473826296627522,
0.009668797254562378,
-0.039799511432647705,
0.12312165647745132,
-0.0075468383729457855,
-0.04216589778661728,
0.047166235744953156,
0.004872883204370737,
0.06153394654393196,
-0.041193634271621704,
-0.08556394279003143,
-0.060135357081890106,
-0.08134358376264572,
0.058962881565093994,
-0.0378771610558033,
0.035288698971271515,
-0.04341601952910423,
-0.02239381894469261,
-0.05541263520717621,
0.10420840978622437,
-0.030969953164458275,
-0.0014744559302926064,
-0.10455193370580673,
0.16104155778884888,
-0.06383784860372543,
0.009646493010222912,
-0.10124273598194122,
-0.04246241971850395,
0.03291436657309532,
-0.0890025720000267,
-0.0007577270152978599,
0.08846988528966904,
0.040655042976140976,
0.012245023623108864,
-0.03523954749107361,
0.009008366614580154,
0.023306721821427345,
0.03212181106209755,
-0.019741298630833626,
-0.11294791847467422,
-0.09661109745502472,
-0.04568769037723541,
0.15015678107738495,
0.004728049971163273,
0.03570736199617386,
0.12408661842346191,
0.25533029437065125,
0.008644714020192623,
-0.036410853266716,
0.05781348794698715,
0.01069306954741478,
0.03227432817220688,
0.008150084875524044,
0.05057944729924202,
0.024657269939780235,
-0.14799334108829498,
0.10337609052658081,
-0.023179003968834877,
-0.06372294574975967,
0.09947022795677185,
0.06970711052417755,
-0.005535025615245104,
0.021250557154417038,
-0.031091250479221344,
-0.02924707718193531,
0.017173562198877335,
-0.009358292445540428,
0.11896149814128876,
-0.03600521758198738,
0.06525595486164093,
-0.047379616647958755,
-0.05664074048399925,
0.028167353942990303,
-0.007997158914804459,
-0.0461934395134449,
0.06438539922237396,
0.03533387929201126,
-0.1952759325504303,
0.06935629993677139,
0.12294737249612808,
0.05935186147689819,
0.13336271047592163,
-0.015711303800344467,
-0.04988531768321991,
-0.08043110370635986,
0.004054185468703508,
0.014219843782484531,
0.10265138745307922,
-0.12872636318206787,
0.058814626187086105,
0.07457775622606277,
-0.02243492379784584,
0.04711960256099701,
-0.09196273982524872,
0.00025152048328891397,
0.04469125717878342,
-0.0319974310696125,
0.03331981226801872,
0.07329104840755463,
-0.011470421217381954,
0.019946938380599022,
-0.008057501167058945,
-0.013751253485679626,
0.03201770409941673,
0.0007271075737662613,
-0.06351993978023529,
0.1186840757727623,
-0.08858449757099152,
-0.22332818806171417,
-0.11306701600551605,
-0.02593626081943512,
-0.10854406654834747,
-0.005683994386345148,
0.029815630987286568,
-0.0082882484421134,
-0.040933746844530106,
-0.0785650908946991,
0.014470991678535938,
-0.028661010786890984,
0.06514342129230499,
0.01895192451775074,
0.019530117511749268,
0.016029905527830124,
-0.0948190987110138,
-0.014364097267389297,
0.010734516195952892,
-0.05395966395735741,
0.07578901201486588,
-0.024303531274199486,
0.1102546751499176,
0.03137059509754181,
-0.027572274208068848,
-0.001422069501131773,
-0.005477089434862137,
0.250457763671875,
-0.0406593419611454,
0.03650524467229843,
0.14618425071239471,
-0.06458676606416702,
0.05492657423019409,
0.16143745183944702,
0.004086183849722147,
-0.0469592809677124,
-0.02191103622317314,
-0.0364195890724659,
-0.054461751133203506,
-0.1502792239189148,
-0.06766148656606674,
-0.11004404723644257,
0.09911727905273438,
0.005522701423615217,
0.022147424519062042,
0.02366855926811695,
0.0919484943151474,
-0.045410435646772385,
0.02546503022313118,
-0.021720457822084427,
0.04268011450767517,
0.11327407509088516,
-0.013585656881332397,
0.10385236144065857,
-0.04284706339240074,
-0.009709221310913563,
0.06927569210529327,
0.09500765800476074,
0.11157146096229553,
0.06334061920642853,
0.1254672408103943,
0.04137241095304489,
0.1458798199892044,
0.11100926250219345,
0.04733496531844139,
-0.04830625280737877,
-0.015453712083399296,
-0.05071209371089935,
-0.06271397322416306,
0.03410189598798752,
0.07215950638055801,
0.09834147989749908,
-0.00837322510778904,
-0.013888785615563393,
-0.018811777234077454,
-0.019908566027879715,
0.13435713946819305,
0.1331886500120163,
-0.19961592555046082,
-0.07001560181379318,
0.018218856304883957,
0.03653867170214653,
0.029300397261977196,
-0.06304226070642471,
-0.003506120527163148,
-0.062024544924497604,
0.1171535849571228,
-0.010837658308446407,
0.07007256895303726,
-0.049879904836416245,
-0.03430672362446785,
0.021932773292064667,
0.081133633852005,
0.00810954999178648,
0.038273364305496216,
-0.13169623911380768,
0.13897490501403809,
0.017616402357816696,
-0.02591223269701004,
-0.015274533070623875,
0.06243749335408211,
-0.0234321691095829,
0.05065998062491417,
0.08708712458610535,
0.03288596495985985,
-0.08127953112125397,
-0.08471550792455673,
-0.10975556820631027,
0.021534675732254982,
0.05610518902540207,
-0.08465568721294403,
0.06221809983253479,
0.0216594897210598,
-0.03609117865562439,
-0.030939770862460136,
0.1172805204987526,
-0.1441827416419983,
-0.15376567840576172,
0.14388398826122284,
-0.04205930978059769,
-0.0070708803832530975,
-0.07199578732252121,
-0.02082151174545288,
-0.05668400228023529,
0.1817806512117386,
0.09063347429037094,
-0.06484386324882507,
-0.12263386696577072,
-0.03593466058373451,
0.1583983451128006,
-0.07850794494152069,
0.11197708547115326,
-0.02877597138285637,
0.03682420030236244,
-0.07328673452138901,
-0.10816191136837006,
0.08170559257268906,
-0.0819445550441742,
-0.1040165051817894,
-0.03564215078949928,
0.11649056524038315,
-0.028348112478852272,
0.06309875100851059,
0.04487806186079979,
0.0365925170481205,
0.015478580258786678,
-0.06686747074127197,
0.032874658703804016,
0.06135203316807747,
-0.01485699974000454,
0.08632344752550125,
-0.00510776462033391,
-0.0663621723651886,
-0.05739228054881096,
-0.04015753045678139,
0.09179894626140594,
0.2732391059398651,
-0.05212053284049034,
0.07893957942724228,
0.011042093858122826,
-0.001450339681468904,
-0.1261090189218521,
-0.061685819178819656,
0.009981314651668072,
0.05408236384391785,
-0.02280835434794426,
-0.05436914414167404,
0.10478626936674118,
0.14608214795589447,
-0.0062425388023257256,
0.07735668122768402,
-0.20090849697589874,
-0.11685485392808914,
-0.004970942623913288,
0.07797257602214813,
0.10871413350105286,
-0.09992283582687378,
-0.08000382035970688,
-0.007814697921276093,
-0.2934352457523346,
0.0995464026927948,
0.022289875894784927,
0.0989360511302948,
-0.032791830599308014,
-0.05584345757961273,
0.004027802962809801,
-0.012056224048137665,
0.16855256259441376,
0.055730875581502914,
-0.028329575434327126,
-0.06119225174188614,
-0.0017757390160113573,
0.05412208288908005,
0.007279737386852503,
0.021264763548970222,
-0.03805294632911682,
0.03317658230662346,
-0.12829412519931793,
-0.033072926104068756,
-0.02893196977674961,
0.05754265934228897,
-0.015910346060991287,
-0.06325672566890717,
-0.08736288547515869,
0.07683409005403519,
-0.003910142462700605,
0.007371857762336731,
0.032821107655763626,
-0.03223652020096779,
-0.014143559150397778,
0.16908180713653564,
0.02108571119606495,
-0.12866704165935516,
-0.04615569859743118,
-0.029857169836759567,
-0.048921987414360046,
0.01358729600906372,
-0.029999716207385063,
-0.005870106630027294,
0.08060315251350403,
0.03843158856034279,
0.05854615196585655,
0.03559427708387375,
-0.04775095731019974,
0.026521865278482437,
0.08455731719732285,
-0.12809322774410248,
-0.1647132784128189,
-0.05383123829960823,
-0.0963699221611023,
-0.036890383809804916,
0.039421409368515015,
0.15440818667411804,
0.005592346657067537,
-0.03478594124317169,
-0.009404291398823261,
-0.009550938382744789,
-0.09521530568599701,
0.10707730054855347,
0.01999298296868801,
0.03229602426290512,
-0.09772562235593796,
0.03587633743882179,
0.04992426186800003,
-0.09040474146604538,
-0.07547048479318619,
0.0457187183201313,
-0.09799535572528839,
-0.06448651105165482,
-0.15040770173072815,
0.07615000009536743,
-0.062497418373823166,
0.06702478229999542,
-0.12011787295341492,
-0.12104014307260513,
0.042818132787942886,
0.10800515860319138,
0.0827578455209732,
0.020721321925520897,
0.04614434763789177,
-0.044171061366796494,
-0.0445486344397068,
0.043357979506254196,
0.06954213231801987,
0.092084139585495,
-0.08922775089740753,
0.03395428508520126,
-0.058054257184267044,
0.06717786192893982,
-0.018751807510852814,
0.026509197428822517,
-0.1263734996318817,
-0.07076858729124069,
-0.010121623985469341,
-0.018949253484606743,
-0.16899967193603516,
-0.0262201689183712,
-0.04745037853717804,
-0.06985786557197571,
-0.015548592433333397,
0.018586687743663788,
-0.04783936217427254,
-0.0648723691701889,
-0.03244583681225777,
0.03216913342475891,
-0.00826873816549778,
-0.015932494774460793,
0.06242603808641434,
-0.07363495975732803,
0.03949714079499245,
0.016789549961686134,
0.011174669489264488,
-0.032927628606557846,
-0.08936521410942078,
-0.07209531217813492,
0.004716753028333187,
0.0412430539727211,
0.055643677711486816,
-0.1306164264678955,
-0.018286362290382385,
0.032183658331632614,
-0.0184547770768404,
-0.017137013375759125,
0.08171249181032181,
-0.10260526090860367,
-0.0614260770380497,
-0.07671847194433212,
-0.05900748446583748,
-0.040290962904691696,
-0.03682849556207657,
0.16197149455547333,
0.07057255506515503,
0.12635810673236847,
-0.0036561833694577217,
0.08842428028583527,
-0.17479045689105988,
-0.025545304641127586,
-0.019821329042315483,
-0.08568170666694641,
0.03732648491859436,
-0.08068955689668655,
0.020583374425768852,
0.002098937751725316,
0.09980378299951553,
-0.06413599103689194,
-0.07070650905370712,
0.017025355249643326,
-0.04425673931837082,
0.18230018019676208,
0.05105169862508774,
0.3334656357765198,
0.09169230610132217,
0.012088186107575893,
0.0209488645195961,
0.09503504633903503,
-0.006678015924990177,
0.07670897245407104,
0.06645471602678299,
0.11515345424413681,
-0.012705291621387005,
0.058743949979543686,
0.1299980878829956,
-0.003623757278546691,
-0.010508732870221138,
-0.003898023394867778,
0.0007152403122745454,
0.04003205895423889,
0.016817549243569374,
0.10954167693853378,
0.09738227725028992,
-0.22251836955547333,
0.08407223969697952,
0.09856157749891281,
-0.060405127704143524,
-0.05545584484934807,
-0.13787797093391418,
-0.11546724289655685,
-0.12651053071022034,
0.01818537339568138,
-0.07450840622186661,
-0.006991252768784761,
0.03531026467680931,
-0.003186106914654374,
0.032202426344156265,
0.07451198995113373,
-0.07900576293468475,
0.024549229070544243,
0.030060160905122757,
-0.00033989158691838384,
-0.05836029723286629,
0.04995567351579666,
-0.047666143625974655,
0.02918563224375248,
0.019946767017245293,
-0.034125979989767075,
-0.04694357141852379,
-0.007571676280349493,
0.042406730353832245,
0.037227779626846313,
-0.10652973502874374,
-0.019623521715402603,
-0.03384898975491524,
0.05096613988280296,
0.04384790360927582,
0.043073635548353195,
0.00949842669069767,
0.0033112047240138054,
0.011903953738510609,
-0.0031829748768359423,
-0.0947936549782753,
-0.11541840434074402,
0.012265190482139587,
0.0013662076089531183,
0.018061494454741478,
0.08033342659473419,
-0.09650946408510208,
0.06400204449892044,
0.13706807792186737,
0.22908435761928558,
0.0006531246472150087,
0.036272112280130386,
0.039195626974105835,
0.006655137985944748,
0.0707872211933136,
-0.004899822175502777,
0.041417960077524185,
0.11257579922676086,
-0.037950508296489716,
-0.03262881189584732,
-0.03006686270236969,
-0.06814829260110855,
-0.054836586117744446,
-0.04364743083715439,
0.08683636039495468,
-0.0436500608921051,
0.03594522550702095,
0.07609274238348007,
-0.07055386900901794,
0.008837155066430569,
0.08293677121400833,
-0.13460035622119904,
-0.10287564247846603,
-0.08715386688709259,
-0.014171470887959003,
0.0073287999257445335,
0.07098729908466339,
-0.055002305656671524,
0.013288883492350578,
0.1447342038154602,
0.02573496662080288,
-0.1775103062391281,
-0.08518213778734207,
0.03701864182949066,
-0.006928879301995039,
-0.007191106677055359,
-0.03633542358875275,
0.07589061558246613,
0.10475708544254303,
0.061355143785476685,
-0.09412840753793716,
0.011240308173000813,
-0.020102975890040398,
-0.04189111664891243,
0.010519997216761112,
0.11622945964336395,
-0.026971103623509407,
0.09544295072555542,
0.022579338401556015,
-0.1139063611626625,
0.06685486435890198,
0.014272747561335564,
0.024015994742512703,
-0.03325653821229935,
0.04859905317425728,
-0.1036529615521431,
0.152162104845047,
0.2078811228275299,
-0.04143018275499344,
-0.008436876349151134,
-0.004772443324327469,
0.025614077225327492,
0.08519241958856583,
0.048748720437288284,
-0.07519437372684479,
-0.14951622486114502,
-0.04041809216141701,
-0.013842727988958359,
0.017509950324892998,
-0.0891033336520195,
-0.13392005860805511,
-0.1318259835243225,
-0.046210791915655136,
-0.024942131713032722,
0.07775257527828217,
0.11921852827072144,
-0.02391991578042507,
-0.00681363744661212,
-0.10389363765716553,
-0.02653820812702179,
0.04351605847477913,
-0.1319659799337387,
-0.08476855605840683
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | null | sanjay920/cortex-small | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:46:31+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
31,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06646376848220825,
0.2168014943599701,
-0.00225935154594481,
0.023818302899599075,
0.1271018385887146,
-0.001635765191167593,
0.04218708351254463,
0.13324736058712006,
-0.020175931975245476,
0.11144465953111649,
0.046588581055402756,
0.09377603232860565,
0.09928803145885468,
0.18404334783554077,
0.04859916493296623,
-0.2059975117444992,
0.007056170143187046,
-0.09090408682823181,
0.014076028019189835,
0.1116579994559288,
0.13719257712364197,
-0.10291384905576706,
0.08272874355316162,
-0.04045208916068077,
-0.02019004337489605,
0.00012576708104461432,
-0.09259183704853058,
-0.07032395154237747,
0.06885425746440887,
0.06264153122901917,
0.051234472543001175,
0.001456156256608665,
0.09140396863222122,
-0.2864592671394348,
0.017265573143959045,
0.08406311273574829,
0.0027674848679453135,
0.06290827691555023,
0.07236549258232117,
-0.07389893382787704,
0.11328595131635666,
-0.08021481335163116,
0.13019037246704102,
0.08625296503305435,
-0.062064990401268005,
-0.23071379959583282,
-0.07525765895843506,
0.0963398814201355,
0.12251301854848862,
0.06215599179267883,
-0.022921854630112648,
0.15455181896686554,
-0.06248689442873001,
0.012971068732440472,
0.1294165402650833,
-0.11526761949062347,
-0.05572471022605896,
0.061741601675748825,
0.11775490641593933,
0.10740239918231964,
-0.14110268652439117,
-0.0017287094378843904,
0.04900608956813812,
0.029121357947587967,
0.08589313924312592,
0.022661056369543076,
0.12003941088914871,
0.04652795568108559,
-0.13695219159126282,
-0.04037507623434067,
0.12011898308992386,
0.038862764835357666,
-0.06446044892072678,
-0.2168138176202774,
-0.006778308190405369,
-0.0601806715130806,
-0.014732478186488152,
-0.07019448280334473,
0.039128515869379044,
-0.02470310963690281,
0.07317749410867691,
-0.04465159401297569,
-0.1063927412033081,
-0.0421026237308979,
0.0892222449183464,
0.07748593389987946,
0.011527054943144321,
-0.02519804798066616,
0.04627908393740654,
0.13455867767333984,
0.05402068421244621,
-0.10399353504180908,
-0.07017925381660461,
-0.06942764669656754,
-0.09420394152402878,
-0.04035796597599983,
0.056760527193546295,
0.031942449510097504,
0.02665667235851288,
0.22703726589679718,
0.016653569415211678,
0.04155244305729866,
0.0224777739495039,
0.01032855175435543,
0.043662428855895996,
0.0955500528216362,
-0.05303520709276199,
-0.15660029649734497,
-0.04072032496333122,
0.09077946096658707,
-0.0027527001220732927,
-0.036689214408397675,
-0.03966725245118141,
0.03849169611930847,
0.06843466311693192,
0.13122352957725525,
0.07552056759595871,
-0.017929591238498688,
-0.04813180863857269,
-0.030096933245658875,
0.23523783683776855,
-0.1493375599384308,
0.04426715523004532,
-0.02271856553852558,
-0.01804111897945404,
-0.03908449783921242,
0.03597262129187584,
0.022118929773569107,
-0.000004518366949923802,
0.09706240892410278,
-0.058981191366910934,
-0.05378659814596176,
-0.10168042778968811,
-0.03272576630115509,
0.04088849574327469,
-0.013975566253066063,
-0.010589460842311382,
-0.09025166928768158,
-0.09490354359149933,
-0.04766594246029854,
0.05537205561995506,
-0.05123869329690933,
-0.03770573064684868,
0.009465423412621021,
-0.08151785284280777,
-0.005444355774670839,
-0.005417742300778627,
0.10699385404586792,
-0.03222226724028587,
0.04445803165435791,
-0.027600755915045738,
0.05225523188710213,
0.09919606149196625,
0.031576547771692276,
-0.0773419588804245,
0.0561848059296608,
-0.22559374570846558,
0.07503069192171097,
-0.11481974273920059,
0.04335082694888115,
-0.1704932004213333,
-0.042439818382263184,
0.005444696638733149,
0.0139949731528759,
0.013206101022660732,
0.12720820307731628,
-0.19255615770816803,
-0.01654396951198578,
0.13260798156261444,
-0.09212633967399597,
-0.118110790848732,
0.07884611934423447,
-0.029701577499508858,
0.1624738723039627,
0.04682036489248276,
-0.027025915682315826,
0.09224298596382141,
-0.16434773802757263,
-0.07092688232660294,
-0.00949116237461567,
-0.01727987825870514,
0.12109188735485077,
0.07512219995260239,
-0.05991523340344429,
0.046571120619773865,
0.02832140028476715,
-0.038078423589468,
-0.04424772411584854,
-0.050857074558734894,
-0.10884185880422592,
-0.01070026308298111,
-0.08987759798765182,
0.04065500199794769,
-0.01250192429870367,
-0.07916021347045898,
-0.029885273426771164,
-0.18612512946128845,
-0.0030564051121473312,
0.10038342326879501,
0.0035033065360039473,
-0.005652366206049919,
-0.08666291832923889,
0.026358824223279953,
-0.03112892620265484,
-0.008404186926782131,
-0.16764774918556213,
-0.04399421438574791,
0.046902090311050415,
-0.16094985604286194,
0.020117372274398804,
-0.06413903087377548,
0.06334125250577927,
0.03641495108604431,
-0.05590536445379257,
-0.0248766727745533,
-0.01730942726135254,
0.011945613659918308,
-0.05083848536014557,
-0.18994836509227753,
-0.056277405470609665,
-0.037882111966609955,
0.149809330701828,
-0.25956398248672485,
0.032966937869787216,
0.051140617579221725,
0.14649195969104767,
0.00406361510977149,
-0.05115427449345589,
0.01429014839231968,
-0.05360214412212372,
-0.054652128368616104,
-0.06746816635131836,
-0.006135428790003061,
-0.027576493099331856,
-0.05147203803062439,
0.019243421033024788,
-0.1755700707435608,
-0.021410830318927765,
0.09424154460430145,
0.12876708805561066,
-0.1486445665359497,
-0.018640631809830666,
-0.048725154250860214,
-0.06339836865663528,
-0.0715010017156601,
-0.07038594037294388,
0.10712739825248718,
0.0513901449739933,
0.04796046018600464,
-0.07435787469148636,
-0.07092321664094925,
0.02726263552904129,
0.006906150374561548,
-0.03382374346256256,
0.08727246522903442,
0.05199531093239784,
-0.09209315478801727,
0.0756213590502739,
0.1092359870672226,
0.07177663594484329,
0.09363535046577454,
0.01574566215276718,
-0.11756632477045059,
-0.028492970392107964,
0.036266472190618515,
0.02740776725113392,
0.1465986967086792,
-0.05952361226081848,
0.04016614332795143,
0.04494241625070572,
-0.04170418903231621,
0.022319864481687546,
-0.08787637203931808,
0.024075502529740334,
0.025203049182891846,
-0.0034381982404738665,
0.06284574419260025,
-0.02525499276816845,
-0.0050758360885083675,
0.07016654312610626,
0.047779910266399384,
0.04621000960469246,
0.009655474685132504,
-0.01720241829752922,
-0.1047825813293457,
0.16950392723083496,
-0.0951867327094078,
-0.269941508769989,
-0.17632324993610382,
0.026197833940386772,
0.04035249724984169,
-0.022378476336598396,
0.031619444489479065,
-0.07056326419115067,
-0.10630585998296738,
-0.1060405746102333,
-0.002429972169920802,
0.01714223250746727,
-0.06364088505506516,
-0.0741225928068161,
0.07348573952913284,
0.04382912442088127,
-0.14902326464653015,
0.038552410900592804,
0.055694397538900375,
-0.057955220341682434,
-0.0233661737293005,
0.09118817001581192,
0.12397737801074982,
0.14583967626094818,
-0.021366750821471214,
-0.028626007959246635,
0.029004426673054695,
0.19620531797409058,
-0.13469526171684265,
0.10371150821447372,
0.13814030587673187,
-0.04545360431075096,
0.08360563963651657,
0.1560150384902954,
0.029186224564909935,
-0.08317049592733383,
0.05044832453131676,
0.04082648828625679,
-0.043159641325473785,
-0.2666129767894745,
-0.0534592866897583,
0.012832709588110447,
-0.06255637854337692,
0.09786593168973923,
0.10183793306350708,
0.11542957276105881,
0.034910861402750015,
-0.07166364789009094,
-0.043925940990448,
-0.0058974819257855415,
0.11737963557243347,
-0.05490213260054588,
-0.012639665976166725,
0.07686592638492584,
-0.05086168646812439,
0.005355054512619972,
0.10266812145709991,
0.02973790094256401,
0.17442677915096283,
0.020399179309606552,
0.11231429129838943,
0.06195578724145889,
0.08633565157651901,
0.0007386076031252742,
0.02951662428677082,
0.05147615820169449,
0.017203815281391144,
-0.002300140680745244,
-0.10421168059110641,
-0.006156572140753269,
0.1449710875749588,
0.028103826567530632,
0.029669636860489845,
-0.0018948549404740334,
-0.005003341939300299,
0.05121048167347908,
0.1746254414319992,
-0.011592294089496136,
-0.22072425484657288,
-0.0845772922039032,
0.06936841458082199,
-0.06218599155545235,
-0.12968985736370087,
-0.026130788028240204,
0.045467354357242584,
-0.17519839107990265,
0.026703642681241035,
-0.027433741837739944,
0.0919293761253357,
-0.09345759451389313,
-0.02221956104040146,
0.03687324374914169,
0.084866963326931,
-0.014529162086546421,
0.08703910559415817,
-0.14498743414878845,
0.11886418610811234,
0.02978132851421833,
0.09024628251791,
-0.11081171780824661,
0.07909037172794342,
-0.007550720125436783,
0.009180475026369095,
0.19379350543022156,
-0.011335089802742004,
-0.03514958545565605,
-0.08774717897176743,
-0.11210042238235474,
-0.013537433929741383,
0.12687496840953827,
-0.1243172138929367,
0.08773399889469147,
-0.015198243781924248,
-0.044079482555389404,
0.00937260314822197,
-0.12100647389888763,
-0.17273177206516266,
-0.19628387689590454,
0.05585884302854538,
-0.09575839340686798,
0.025643249973654747,
-0.11914430558681488,
-0.07089093327522278,
-0.02952558360993862,
0.241120383143425,
-0.1745356321334839,
-0.06510113179683685,
-0.1468164622783661,
-0.046294767409563065,
0.1662203073501587,
-0.04437198117375374,
0.0718095526099205,
-0.0208172257989645,
0.20345525443553925,
0.005988610442727804,
-0.004939318168908358,
0.06724198162555695,
-0.08892562240362167,
-0.16873881220817566,
-0.06771010160446167,
0.1510489284992218,
0.11680185794830322,
0.04907919466495514,
-0.002248800592496991,
0.0011772146681323647,
-0.016943959519267082,
-0.1137804463505745,
-0.0033210667315870523,
0.16037839651107788,
0.03878779336810112,
0.025986969470977783,
-0.05243593826889992,
-0.08797456324100494,
-0.06899320334196091,
-0.06853509694337845,
0.06221301481127739,
0.19590823352336884,
-0.10376439243555069,
0.1700313836336136,
0.147536963224411,
-0.07305635511875153,
-0.23175598680973053,
0.035342130810022354,
0.04983805492520332,
0.0014306638622656465,
0.04886869341135025,
-0.18252557516098022,
0.10521943867206573,
0.019543392583727837,
-0.05505957826972008,
0.13485197722911835,
-0.1557481735944748,
-0.1552847921848297,
0.0722852572798729,
0.03904085233807564,
-0.22423844039440155,
-0.1354004591703415,
-0.09622503817081451,
-0.05825018882751465,
-0.14065024256706238,
0.06054598465561867,
-0.002136280992999673,
0.015948504209518433,
0.03500790148973465,
-0.0015643214574083686,
0.027123261243104935,
-0.058935679495334625,
0.18609118461608887,
-0.004065449349582195,
0.020676052197813988,
-0.060264769941568375,
-0.0478842556476593,
0.09839435666799545,
-0.06130504235625267,
0.12208222597837448,
0.004057085141539574,
0.01594383642077446,
-0.10362856835126877,
-0.048314861953258514,
-0.04328322783112526,
0.05154227837920189,
-0.07548051327466965,
-0.10070807486772537,
-0.043625857681035995,
0.08841723203659058,
0.07005169242620468,
-0.03383097052574158,
0.00549331633374095,
-0.07189501076936722,
0.10019614547491074,
0.17795267701148987,
0.17573626339435577,
0.009926567785441875,
-0.07241068035364151,
0.01677953451871872,
-0.04142116755247116,
0.044231921434402466,
-0.2513144314289093,
0.03756171092391014,
0.06098250672221184,
0.029438555240631104,
0.09217222779989243,
-0.020435843616724014,
-0.1820858269929886,
-0.04050002992153168,
0.08094815909862518,
-0.05452597141265869,
-0.22617179155349731,
-0.019085140898823738,
0.0954197570681572,
-0.2020406424999237,
-0.007372708059847355,
0.03995226323604584,
-0.048725228756666183,
-0.023169852793216705,
0.00010950004070764408,
0.06317184865474701,
0.002471912419423461,
0.09773622453212738,
0.0735151618719101,
0.09715340286493301,
-0.08337292820215225,
0.10562895983457565,
0.10150538384914398,
-0.09572599828243256,
0.03605884686112404,
0.06754924356937408,
-0.05300498008728027,
-0.043293699622154236,
0.03665391728281975,
0.033023297786712646,
0.005234600510448217,
-0.060321882367134094,
0.013913018628954887,
-0.036497246474027634,
0.044923391193151474,
0.08326134830713272,
0.03754979372024536,
-0.013354414142668247,
0.06462216377258301,
0.03401726484298706,
-0.10898099094629288,
0.10366570204496384,
0.01731540448963642,
0.04105307161808014,
-0.08384523540735245,
-0.019968897104263306,
0.035425446927547455,
0.030576206743717194,
-0.01765924133360386,
-0.02306121215224266,
-0.02860277332365513,
-0.01614218018949032,
-0.14299540221691132,
-0.023106401786208153,
-0.07243485748767853,
0.006181265693157911,
0.014656842686235905,
-0.031884219497442245,
-0.011233693920075893,
0.02475680410861969,
-0.06979699432849884,
-0.07426341623067856,
-0.006949664559215307,
0.09833318740129471,
-0.15115703642368317,
0.008848577737808228,
0.06907843053340912,
-0.11088496446609497,
0.08190931379795074,
-0.008411259390413761,
0.016245156526565552,
0.022527478635311127,
-0.15448406338691711,
0.05601610988378525,
0.0008648968650959432,
0.01916889287531376,
0.025886621326208115,
-0.16471809148788452,
0.004104440100491047,
-0.04661374166607857,
-0.02149827405810356,
-0.00004464812809601426,
-0.02647159807384014,
-0.12325995415449142,
0.06858719140291214,
-0.015622655861079693,
-0.035931166261434555,
-0.02701525390148163,
0.0539589487016201,
0.07888586074113846,
-0.027474910020828247,
0.10445091128349304,
-0.008690856397151947,
0.04941811040043831,
-0.16801609098911285,
-0.02470702864229679,
-0.04982255399227142,
0.019377702847123146,
0.009884213097393513,
-0.007693959400057793,
0.04183054715394974,
-0.00976533442735672,
0.21883612871170044,
-0.05075952783226967,
0.1607085019350052,
0.05847611650824547,
-0.017352959141135216,
-0.0007513365126214921,
0.06180921941995621,
0.05997028574347496,
0.04658793285489082,
0.009480604901909828,
0.023740366101264954,
-0.022450892254710197,
-0.006695089396089315,
-0.15932634472846985,
0.01890849508345127,
0.14999441802501678,
0.06301083415746689,
0.024745315313339233,
0.05866100639104843,
-0.12775006890296936,
-0.12135478109121323,
0.09311001747846603,
-0.026755332946777344,
0.00928465835750103,
-0.08245618641376495,
0.1358020007610321,
0.14980104565620422,
-0.14000412821769714,
0.05256148427724838,
-0.06134212389588356,
-0.05217423290014267,
-0.10388828068971634,
-0.12032219022512436,
-0.05887215584516525,
-0.053666237741708755,
0.002330566756427288,
-0.03760887682437897,
0.054546963423490524,
0.03344334661960602,
-0.009351172484457493,
-0.00022941511997487396,
0.13597318530082703,
-0.019751882180571556,
-0.0028988157864660025,
0.048313532024621964,
0.03693558648228645,
0.02373051457107067,
-0.05275435373187065,
0.02940409444272518,
0.02539868652820587,
0.032232340425252914,
0.06546790152788162,
0.033412106335163116,
-0.047448933124542236,
0.03804153576493263,
-0.0025254099164158106,
-0.11207924783229828,
0.019641218706965446,
-0.00460948096588254,
-0.0742158442735672,
0.1268945336341858,
0.0407399944961071,
0.010224059224128723,
-0.03741471841931343,
0.24361543357372284,
-0.06653323769569397,
-0.06378097087144852,
-0.13251738250255585,
0.10491154342889786,
-0.0027236645109951496,
0.06476365029811859,
0.023412218317389488,
-0.1284150779247284,
0.005243356805294752,
0.13858191668987274,
0.12181595712900162,
0.0045748427510261536,
0.009228081442415714,
0.0518609918653965,
0.0025186820421367884,
-0.06998204439878464,
0.054019294679164886,
0.06992026418447495,
0.12919506430625916,
-0.07847554981708527,
0.07680778950452805,
0.0006860480643808842,
-0.08370215445756912,
-0.02947772853076458,
0.11312682181596756,
-0.0409729965031147,
0.03491825982928276,
-0.047444481402635574,
0.10916327685117722,
-0.05787910893559456,
-0.29412412643432617,
0.02350960113108158,
-0.09588567912578583,
-0.15202060341835022,
-0.018367812037467957,
0.05944539234042168,
-0.02624768204987049,
0.018029648810625076,
0.06971040368080139,
-0.06011629104614258,
0.20098382234573364,
0.0335683599114418,
-0.07864278554916382,
-0.0664360448718071,
0.04837050288915634,
-0.06564252078533173,
0.2949807047843933,
0.008418165147304535,
0.02863333560526371,
0.10770907253026962,
-0.03253700211644173,
-0.18271861970424652,
0.010723991319537163,
0.1133992001414299,
-0.08056149631738663,
0.08200647681951523,
0.19000613689422607,
-0.012578671798110008,
0.1209007054567337,
0.05294662341475487,
-0.047376248985528946,
0.04217283055186272,
-0.03389401361346245,
-0.051268599927425385,
-0.10752558708190918,
0.058453381061553955,
-0.05909625440835953,
0.15447644889354706,
0.10152646154165268,
-0.05671518296003342,
-0.004550917539745569,
-0.05555408447980881,
0.04875178262591362,
0.01804669201374054,
0.12263146042823792,
0.02951994352042675,
-0.1865430772304535,
0.032826557755470276,
-0.01144319772720337,
0.10186848044395447,
-0.25588861107826233,
-0.08421015739440918,
0.08833149075508118,
-0.011924264021217823,
-0.05105875805020332,
0.10560628771781921,
0.057650718837976456,
0.04243382066488266,
-0.043439045548439026,
-0.10480839014053345,
-0.02186836116015911,
0.14663739502429962,
-0.1469624787569046,
-0.025013303384184837
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | null | rubra-ai/cortex-small | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-11T03:48:05+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
31,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06646376848220825,
0.2168014943599701,
-0.00225935154594481,
0.023818302899599075,
0.1271018385887146,
-0.001635765191167593,
0.04218708351254463,
0.13324736058712006,
-0.020175931975245476,
0.11144465953111649,
0.046588581055402756,
0.09377603232860565,
0.09928803145885468,
0.18404334783554077,
0.04859916493296623,
-0.2059975117444992,
0.007056170143187046,
-0.09090408682823181,
0.014076028019189835,
0.1116579994559288,
0.13719257712364197,
-0.10291384905576706,
0.08272874355316162,
-0.04045208916068077,
-0.02019004337489605,
0.00012576708104461432,
-0.09259183704853058,
-0.07032395154237747,
0.06885425746440887,
0.06264153122901917,
0.051234472543001175,
0.001456156256608665,
0.09140396863222122,
-0.2864592671394348,
0.017265573143959045,
0.08406311273574829,
0.0027674848679453135,
0.06290827691555023,
0.07236549258232117,
-0.07389893382787704,
0.11328595131635666,
-0.08021481335163116,
0.13019037246704102,
0.08625296503305435,
-0.062064990401268005,
-0.23071379959583282,
-0.07525765895843506,
0.0963398814201355,
0.12251301854848862,
0.06215599179267883,
-0.022921854630112648,
0.15455181896686554,
-0.06248689442873001,
0.012971068732440472,
0.1294165402650833,
-0.11526761949062347,
-0.05572471022605896,
0.061741601675748825,
0.11775490641593933,
0.10740239918231964,
-0.14110268652439117,
-0.0017287094378843904,
0.04900608956813812,
0.029121357947587967,
0.08589313924312592,
0.022661056369543076,
0.12003941088914871,
0.04652795568108559,
-0.13695219159126282,
-0.04037507623434067,
0.12011898308992386,
0.038862764835357666,
-0.06446044892072678,
-0.2168138176202774,
-0.006778308190405369,
-0.0601806715130806,
-0.014732478186488152,
-0.07019448280334473,
0.039128515869379044,
-0.02470310963690281,
0.07317749410867691,
-0.04465159401297569,
-0.1063927412033081,
-0.0421026237308979,
0.0892222449183464,
0.07748593389987946,
0.011527054943144321,
-0.02519804798066616,
0.04627908393740654,
0.13455867767333984,
0.05402068421244621,
-0.10399353504180908,
-0.07017925381660461,
-0.06942764669656754,
-0.09420394152402878,
-0.04035796597599983,
0.056760527193546295,
0.031942449510097504,
0.02665667235851288,
0.22703726589679718,
0.016653569415211678,
0.04155244305729866,
0.0224777739495039,
0.01032855175435543,
0.043662428855895996,
0.0955500528216362,
-0.05303520709276199,
-0.15660029649734497,
-0.04072032496333122,
0.09077946096658707,
-0.0027527001220732927,
-0.036689214408397675,
-0.03966725245118141,
0.03849169611930847,
0.06843466311693192,
0.13122352957725525,
0.07552056759595871,
-0.017929591238498688,
-0.04813180863857269,
-0.030096933245658875,
0.23523783683776855,
-0.1493375599384308,
0.04426715523004532,
-0.02271856553852558,
-0.01804111897945404,
-0.03908449783921242,
0.03597262129187584,
0.022118929773569107,
-0.000004518366949923802,
0.09706240892410278,
-0.058981191366910934,
-0.05378659814596176,
-0.10168042778968811,
-0.03272576630115509,
0.04088849574327469,
-0.013975566253066063,
-0.010589460842311382,
-0.09025166928768158,
-0.09490354359149933,
-0.04766594246029854,
0.05537205561995506,
-0.05123869329690933,
-0.03770573064684868,
0.009465423412621021,
-0.08151785284280777,
-0.005444355774670839,
-0.005417742300778627,
0.10699385404586792,
-0.03222226724028587,
0.04445803165435791,
-0.027600755915045738,
0.05225523188710213,
0.09919606149196625,
0.031576547771692276,
-0.0773419588804245,
0.0561848059296608,
-0.22559374570846558,
0.07503069192171097,
-0.11481974273920059,
0.04335082694888115,
-0.1704932004213333,
-0.042439818382263184,
0.005444696638733149,
0.0139949731528759,
0.013206101022660732,
0.12720820307731628,
-0.19255615770816803,
-0.01654396951198578,
0.13260798156261444,
-0.09212633967399597,
-0.118110790848732,
0.07884611934423447,
-0.029701577499508858,
0.1624738723039627,
0.04682036489248276,
-0.027025915682315826,
0.09224298596382141,
-0.16434773802757263,
-0.07092688232660294,
-0.00949116237461567,
-0.01727987825870514,
0.12109188735485077,
0.07512219995260239,
-0.05991523340344429,
0.046571120619773865,
0.02832140028476715,
-0.038078423589468,
-0.04424772411584854,
-0.050857074558734894,
-0.10884185880422592,
-0.01070026308298111,
-0.08987759798765182,
0.04065500199794769,
-0.01250192429870367,
-0.07916021347045898,
-0.029885273426771164,
-0.18612512946128845,
-0.0030564051121473312,
0.10038342326879501,
0.0035033065360039473,
-0.005652366206049919,
-0.08666291832923889,
0.026358824223279953,
-0.03112892620265484,
-0.008404186926782131,
-0.16764774918556213,
-0.04399421438574791,
0.046902090311050415,
-0.16094985604286194,
0.020117372274398804,
-0.06413903087377548,
0.06334125250577927,
0.03641495108604431,
-0.05590536445379257,
-0.0248766727745533,
-0.01730942726135254,
0.011945613659918308,
-0.05083848536014557,
-0.18994836509227753,
-0.056277405470609665,
-0.037882111966609955,
0.149809330701828,
-0.25956398248672485,
0.032966937869787216,
0.051140617579221725,
0.14649195969104767,
0.00406361510977149,
-0.05115427449345589,
0.01429014839231968,
-0.05360214412212372,
-0.054652128368616104,
-0.06746816635131836,
-0.006135428790003061,
-0.027576493099331856,
-0.05147203803062439,
0.019243421033024788,
-0.1755700707435608,
-0.021410830318927765,
0.09424154460430145,
0.12876708805561066,
-0.1486445665359497,
-0.018640631809830666,
-0.048725154250860214,
-0.06339836865663528,
-0.0715010017156601,
-0.07038594037294388,
0.10712739825248718,
0.0513901449739933,
0.04796046018600464,
-0.07435787469148636,
-0.07092321664094925,
0.02726263552904129,
0.006906150374561548,
-0.03382374346256256,
0.08727246522903442,
0.05199531093239784,
-0.09209315478801727,
0.0756213590502739,
0.1092359870672226,
0.07177663594484329,
0.09363535046577454,
0.01574566215276718,
-0.11756632477045059,
-0.028492970392107964,
0.036266472190618515,
0.02740776725113392,
0.1465986967086792,
-0.05952361226081848,
0.04016614332795143,
0.04494241625070572,
-0.04170418903231621,
0.022319864481687546,
-0.08787637203931808,
0.024075502529740334,
0.025203049182891846,
-0.0034381982404738665,
0.06284574419260025,
-0.02525499276816845,
-0.0050758360885083675,
0.07016654312610626,
0.047779910266399384,
0.04621000960469246,
0.009655474685132504,
-0.01720241829752922,
-0.1047825813293457,
0.16950392723083496,
-0.0951867327094078,
-0.269941508769989,
-0.17632324993610382,
0.026197833940386772,
0.04035249724984169,
-0.022378476336598396,
0.031619444489479065,
-0.07056326419115067,
-0.10630585998296738,
-0.1060405746102333,
-0.002429972169920802,
0.01714223250746727,
-0.06364088505506516,
-0.0741225928068161,
0.07348573952913284,
0.04382912442088127,
-0.14902326464653015,
0.038552410900592804,
0.055694397538900375,
-0.057955220341682434,
-0.0233661737293005,
0.09118817001581192,
0.12397737801074982,
0.14583967626094818,
-0.021366750821471214,
-0.028626007959246635,
0.029004426673054695,
0.19620531797409058,
-0.13469526171684265,
0.10371150821447372,
0.13814030587673187,
-0.04545360431075096,
0.08360563963651657,
0.1560150384902954,
0.029186224564909935,
-0.08317049592733383,
0.05044832453131676,
0.04082648828625679,
-0.043159641325473785,
-0.2666129767894745,
-0.0534592866897583,
0.012832709588110447,
-0.06255637854337692,
0.09786593168973923,
0.10183793306350708,
0.11542957276105881,
0.034910861402750015,
-0.07166364789009094,
-0.043925940990448,
-0.0058974819257855415,
0.11737963557243347,
-0.05490213260054588,
-0.012639665976166725,
0.07686592638492584,
-0.05086168646812439,
0.005355054512619972,
0.10266812145709991,
0.02973790094256401,
0.17442677915096283,
0.020399179309606552,
0.11231429129838943,
0.06195578724145889,
0.08633565157651901,
0.0007386076031252742,
0.02951662428677082,
0.05147615820169449,
0.017203815281391144,
-0.002300140680745244,
-0.10421168059110641,
-0.006156572140753269,
0.1449710875749588,
0.028103826567530632,
0.029669636860489845,
-0.0018948549404740334,
-0.005003341939300299,
0.05121048167347908,
0.1746254414319992,
-0.011592294089496136,
-0.22072425484657288,
-0.0845772922039032,
0.06936841458082199,
-0.06218599155545235,
-0.12968985736370087,
-0.026130788028240204,
0.045467354357242584,
-0.17519839107990265,
0.026703642681241035,
-0.027433741837739944,
0.0919293761253357,
-0.09345759451389313,
-0.02221956104040146,
0.03687324374914169,
0.084866963326931,
-0.014529162086546421,
0.08703910559415817,
-0.14498743414878845,
0.11886418610811234,
0.02978132851421833,
0.09024628251791,
-0.11081171780824661,
0.07909037172794342,
-0.007550720125436783,
0.009180475026369095,
0.19379350543022156,
-0.011335089802742004,
-0.03514958545565605,
-0.08774717897176743,
-0.11210042238235474,
-0.013537433929741383,
0.12687496840953827,
-0.1243172138929367,
0.08773399889469147,
-0.015198243781924248,
-0.044079482555389404,
0.00937260314822197,
-0.12100647389888763,
-0.17273177206516266,
-0.19628387689590454,
0.05585884302854538,
-0.09575839340686798,
0.025643249973654747,
-0.11914430558681488,
-0.07089093327522278,
-0.02952558360993862,
0.241120383143425,
-0.1745356321334839,
-0.06510113179683685,
-0.1468164622783661,
-0.046294767409563065,
0.1662203073501587,
-0.04437198117375374,
0.0718095526099205,
-0.0208172257989645,
0.20345525443553925,
0.005988610442727804,
-0.004939318168908358,
0.06724198162555695,
-0.08892562240362167,
-0.16873881220817566,
-0.06771010160446167,
0.1510489284992218,
0.11680185794830322,
0.04907919466495514,
-0.002248800592496991,
0.0011772146681323647,
-0.016943959519267082,
-0.1137804463505745,
-0.0033210667315870523,
0.16037839651107788,
0.03878779336810112,
0.025986969470977783,
-0.05243593826889992,
-0.08797456324100494,
-0.06899320334196091,
-0.06853509694337845,
0.06221301481127739,
0.19590823352336884,
-0.10376439243555069,
0.1700313836336136,
0.147536963224411,
-0.07305635511875153,
-0.23175598680973053,
0.035342130810022354,
0.04983805492520332,
0.0014306638622656465,
0.04886869341135025,
-0.18252557516098022,
0.10521943867206573,
0.019543392583727837,
-0.05505957826972008,
0.13485197722911835,
-0.1557481735944748,
-0.1552847921848297,
0.0722852572798729,
0.03904085233807564,
-0.22423844039440155,
-0.1354004591703415,
-0.09622503817081451,
-0.05825018882751465,
-0.14065024256706238,
0.06054598465561867,
-0.002136280992999673,
0.015948504209518433,
0.03500790148973465,
-0.0015643214574083686,
0.027123261243104935,
-0.058935679495334625,
0.18609118461608887,
-0.004065449349582195,
0.020676052197813988,
-0.060264769941568375,
-0.0478842556476593,
0.09839435666799545,
-0.06130504235625267,
0.12208222597837448,
0.004057085141539574,
0.01594383642077446,
-0.10362856835126877,
-0.048314861953258514,
-0.04328322783112526,
0.05154227837920189,
-0.07548051327466965,
-0.10070807486772537,
-0.043625857681035995,
0.08841723203659058,
0.07005169242620468,
-0.03383097052574158,
0.00549331633374095,
-0.07189501076936722,
0.10019614547491074,
0.17795267701148987,
0.17573626339435577,
0.009926567785441875,
-0.07241068035364151,
0.01677953451871872,
-0.04142116755247116,
0.044231921434402466,
-0.2513144314289093,
0.03756171092391014,
0.06098250672221184,
0.029438555240631104,
0.09217222779989243,
-0.020435843616724014,
-0.1820858269929886,
-0.04050002992153168,
0.08094815909862518,
-0.05452597141265869,
-0.22617179155349731,
-0.019085140898823738,
0.0954197570681572,
-0.2020406424999237,
-0.007372708059847355,
0.03995226323604584,
-0.048725228756666183,
-0.023169852793216705,
0.00010950004070764408,
0.06317184865474701,
0.002471912419423461,
0.09773622453212738,
0.0735151618719101,
0.09715340286493301,
-0.08337292820215225,
0.10562895983457565,
0.10150538384914398,
-0.09572599828243256,
0.03605884686112404,
0.06754924356937408,
-0.05300498008728027,
-0.043293699622154236,
0.03665391728281975,
0.033023297786712646,
0.005234600510448217,
-0.060321882367134094,
0.013913018628954887,
-0.036497246474027634,
0.044923391193151474,
0.08326134830713272,
0.03754979372024536,
-0.013354414142668247,
0.06462216377258301,
0.03401726484298706,
-0.10898099094629288,
0.10366570204496384,
0.01731540448963642,
0.04105307161808014,
-0.08384523540735245,
-0.019968897104263306,
0.035425446927547455,
0.030576206743717194,
-0.01765924133360386,
-0.02306121215224266,
-0.02860277332365513,
-0.01614218018949032,
-0.14299540221691132,
-0.023106401786208153,
-0.07243485748767853,
0.006181265693157911,
0.014656842686235905,
-0.031884219497442245,
-0.011233693920075893,
0.02475680410861969,
-0.06979699432849884,
-0.07426341623067856,
-0.006949664559215307,
0.09833318740129471,
-0.15115703642368317,
0.008848577737808228,
0.06907843053340912,
-0.11088496446609497,
0.08190931379795074,
-0.008411259390413761,
0.016245156526565552,
0.022527478635311127,
-0.15448406338691711,
0.05601610988378525,
0.0008648968650959432,
0.01916889287531376,
0.025886621326208115,
-0.16471809148788452,
0.004104440100491047,
-0.04661374166607857,
-0.02149827405810356,
-0.00004464812809601426,
-0.02647159807384014,
-0.12325995415449142,
0.06858719140291214,
-0.015622655861079693,
-0.035931166261434555,
-0.02701525390148163,
0.0539589487016201,
0.07888586074113846,
-0.027474910020828247,
0.10445091128349304,
-0.008690856397151947,
0.04941811040043831,
-0.16801609098911285,
-0.02470702864229679,
-0.04982255399227142,
0.019377702847123146,
0.009884213097393513,
-0.007693959400057793,
0.04183054715394974,
-0.00976533442735672,
0.21883612871170044,
-0.05075952783226967,
0.1607085019350052,
0.05847611650824547,
-0.017352959141135216,
-0.0007513365126214921,
0.06180921941995621,
0.05997028574347496,
0.04658793285489082,
0.009480604901909828,
0.023740366101264954,
-0.022450892254710197,
-0.006695089396089315,
-0.15932634472846985,
0.01890849508345127,
0.14999441802501678,
0.06301083415746689,
0.024745315313339233,
0.05866100639104843,
-0.12775006890296936,
-0.12135478109121323,
0.09311001747846603,
-0.026755332946777344,
0.00928465835750103,
-0.08245618641376495,
0.1358020007610321,
0.14980104565620422,
-0.14000412821769714,
0.05256148427724838,
-0.06134212389588356,
-0.05217423290014267,
-0.10388828068971634,
-0.12032219022512436,
-0.05887215584516525,
-0.053666237741708755,
0.002330566756427288,
-0.03760887682437897,
0.054546963423490524,
0.03344334661960602,
-0.009351172484457493,
-0.00022941511997487396,
0.13597318530082703,
-0.019751882180571556,
-0.0028988157864660025,
0.048313532024621964,
0.03693558648228645,
0.02373051457107067,
-0.05275435373187065,
0.02940409444272518,
0.02539868652820587,
0.032232340425252914,
0.06546790152788162,
0.033412106335163116,
-0.047448933124542236,
0.03804153576493263,
-0.0025254099164158106,
-0.11207924783229828,
0.019641218706965446,
-0.00460948096588254,
-0.0742158442735672,
0.1268945336341858,
0.0407399944961071,
0.010224059224128723,
-0.03741471841931343,
0.24361543357372284,
-0.06653323769569397,
-0.06378097087144852,
-0.13251738250255585,
0.10491154342889786,
-0.0027236645109951496,
0.06476365029811859,
0.023412218317389488,
-0.1284150779247284,
0.005243356805294752,
0.13858191668987274,
0.12181595712900162,
0.0045748427510261536,
0.009228081442415714,
0.0518609918653965,
0.0025186820421367884,
-0.06998204439878464,
0.054019294679164886,
0.06992026418447495,
0.12919506430625916,
-0.07847554981708527,
0.07680778950452805,
0.0006860480643808842,
-0.08370215445756912,
-0.02947772853076458,
0.11312682181596756,
-0.0409729965031147,
0.03491825982928276,
-0.047444481402635574,
0.10916327685117722,
-0.05787910893559456,
-0.29412412643432617,
0.02350960113108158,
-0.09588567912578583,
-0.15202060341835022,
-0.018367812037467957,
0.05944539234042168,
-0.02624768204987049,
0.018029648810625076,
0.06971040368080139,
-0.06011629104614258,
0.20098382234573364,
0.0335683599114418,
-0.07864278554916382,
-0.0664360448718071,
0.04837050288915634,
-0.06564252078533173,
0.2949807047843933,
0.008418165147304535,
0.02863333560526371,
0.10770907253026962,
-0.03253700211644173,
-0.18271861970424652,
0.010723991319537163,
0.1133992001414299,
-0.08056149631738663,
0.08200647681951523,
0.19000613689422607,
-0.012578671798110008,
0.1209007054567337,
0.05294662341475487,
-0.047376248985528946,
0.04217283055186272,
-0.03389401361346245,
-0.051268599927425385,
-0.10752558708190918,
0.058453381061553955,
-0.05909625440835953,
0.15447644889354706,
0.10152646154165268,
-0.05671518296003342,
-0.004550917539745569,
-0.05555408447980881,
0.04875178262591362,
0.01804669201374054,
0.12263146042823792,
0.02951994352042675,
-0.1865430772304535,
0.032826557755470276,
-0.01144319772720337,
0.10186848044395447,
-0.25588861107826233,
-0.08421015739440918,
0.08833149075508118,
-0.011924264021217823,
-0.05105875805020332,
0.10560628771781921,
0.057650718837976456,
0.04243382066488266,
-0.043439045548439026,
-0.10480839014053345,
-0.02186836116015911,
0.14663739502429962,
-0.1469624787569046,
-0.025013303384184837
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | visual-question-answering | devlocalhost/blip2-opt-2.7b-xray-captions | [
"transformers",
"safetensors",
"blip-2",
"visual-question-answering",
"arxiv:1910.09700",
"endpoints_compatible",
"8-bit",
"region:us"
] | 2024-02-11T03:55:35+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #blip-2 #visual-question-answering #arxiv-1910.09700 #endpoints_compatible #8-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #blip-2 #visual-question-answering #arxiv-1910.09700 #endpoints_compatible #8-bit #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
48,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #blip-2 #visual-question-answering #arxiv-1910.09700 #endpoints_compatible #8-bit #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.07271717488765717,
0.1462213695049286,
-0.003739255480468273,
0.02520480938255787,
0.11044304817914963,
0.00959368608891964,
0.06718060374259949,
0.1096024215221405,
-0.018762679770588875,
0.12628422677516937,
0.04289289191365242,
0.09932772070169449,
0.10995030403137207,
0.1915307343006134,
-0.0011826788540929556,
-0.20405612885951996,
0.06082766875624657,
-0.10913116484880447,
0.020718209445476532,
0.128014475107193,
0.14257431030273438,
-0.10971422493457794,
0.06506987661123276,
-0.042726192623376846,
-0.024991154670715332,
-0.03272318094968796,
-0.06033550947904587,
-0.04857552796602249,
0.06779912114143372,
0.060832858085632324,
0.06375675648450851,
0.023315908387303352,
0.07654352486133575,
-0.29829928278923035,
0.02085038088262081,
0.0747900977730751,
0.0012071739183738828,
0.05975053459405899,
0.06952104717493057,
-0.076975516974926,
0.10181508958339691,
-0.05805303156375885,
0.15735869109630585,
0.0757477730512619,
-0.09829076379537582,
-0.19649271667003632,
-0.0805990993976593,
0.10252653062343597,
0.16779549419879913,
0.05328480526804924,
-0.03827608376741409,
0.14487145841121674,
-0.08451572805643082,
0.02095337025821209,
0.07702124863862991,
-0.068269744515419,
-0.0515994168817997,
0.05630451813340187,
0.07989779859781265,
0.1008293628692627,
-0.1304725706577301,
-0.009385058656334877,
0.04659117013216019,
0.016529792919754982,
0.10762419551610947,
0.02476903237402439,
0.12605644762516022,
0.034999262541532516,
-0.14481042325496674,
-0.06929261982440948,
0.11167963594198227,
0.04125034064054489,
-0.059823375195264816,
-0.24535909295082092,
-0.0062233866192400455,
-0.03814292326569557,
-0.02232135273516178,
-0.04037896916270256,
0.04209379851818085,
-0.03390825539827347,
0.08756627887487411,
0.0009869468631222844,
-0.0696851909160614,
-0.061396144330501556,
0.09551212936639786,
0.062174487859010696,
0.02726743556559086,
-0.022533666342496872,
0.014723648317158222,
0.1252734512090683,
0.1036650687456131,
-0.11140952259302139,
-0.07090071588754654,
-0.06506195664405823,
-0.08919397741556168,
-0.04061158001422882,
0.03309352323412895,
0.0856185182929039,
0.04694141075015068,
0.20068174600601196,
0.0055265286937355995,
0.04576319083571434,
0.021277880296111107,
0.02111504040658474,
0.06641212105751038,
0.0625743716955185,
-0.05112277343869209,
-0.11941734701395035,
-0.034975696355104446,
0.12519456446170807,
0.00803601648658514,
-0.03154774010181427,
-0.03582203760743141,
0.058265771716833115,
0.04794970527291298,
0.1254071146249771,
0.06687863916158676,
0.015347245149314404,
-0.07716487348079681,
-0.047167420387268066,
0.172003835439682,
-0.1576755791902542,
0.01667320355772972,
0.02020881511271,
-0.057240936905145645,
-0.033679619431495667,
0.01895018480718136,
0.0014261045726016164,
-0.03015488013625145,
0.09593997150659561,
-0.06642770767211914,
-0.04322639852762222,
-0.11063750833272934,
-0.055177126079797745,
0.034227605909109116,
-0.027163641527295113,
-0.025448691099882126,
-0.03355420380830765,
-0.12961998581886292,
-0.06731672585010529,
0.06839311867952347,
-0.06231367588043213,
-0.06423833221197128,
-0.03474767133593559,
-0.06238805502653122,
0.006944245658814907,
-0.004978098440915346,
0.1337849348783493,
-0.029860278591513634,
0.059146929532289505,
-0.051294781267642975,
0.07297048717737198,
0.1310596764087677,
0.030268574133515358,
-0.06567537784576416,
0.07108072936534882,
-0.2051660269498825,
0.10585404932498932,
-0.09438333660364151,
0.019465692341327667,
-0.15923836827278137,
-0.028278343379497528,
0.037596940994262695,
0.039220597594976425,
-0.01620505377650261,
0.13659273087978363,
-0.1778019517660141,
-0.035219985991716385,
0.19030030071735382,
-0.13222359120845795,
-0.09952818602323532,
0.061143796890974045,
-0.06246606633067131,
0.1292867511510849,
0.0519234798848629,
-0.022055577486753464,
0.04954872280359268,
-0.1393166035413742,
-0.020555265247821808,
-0.0527074821293354,
-0.013890955597162247,
0.15456520020961761,
0.06786748766899109,
-0.04683452472090721,
0.029803667217493057,
0.01970171555876732,
-0.03446275368332863,
-0.04989227280020714,
-0.03609102591872215,
-0.09889619797468185,
0.00003323877899674699,
-0.07841253280639648,
0.0245562382042408,
-0.023881498724222183,
-0.09563962370157242,
-0.04233105108141899,
-0.16101622581481934,
0.0037206385750323534,
0.10413408279418945,
0.0002018377126660198,
-0.02807445451617241,
-0.10337230563163757,
0.0028852110262960196,
0.010398123413324356,
-0.01067549828439951,
-0.15158994495868683,
-0.052349235862493515,
0.023143911734223366,
-0.17400582134723663,
0.023373397067189217,
-0.03427615016698837,
0.033877596259117126,
0.041987039148807526,
-0.0512651763856411,
-0.029245685786008835,
0.006207993719726801,
0.017970094457268715,
-0.015880770981311798,
-0.25540295243263245,
-0.02182118035852909,
-0.05261756107211113,
0.17530494928359985,
-0.25205808877944946,
0.04698914662003517,
0.07806582748889923,
0.12057049572467804,
0.00605192594230175,
-0.042886536568403244,
0.03554277494549751,
-0.05920074135065079,
-0.03898201137781143,
-0.06502778083086014,
0.0003872159868478775,
-0.035538870841264725,
-0.05130879953503609,
0.034953054040670395,
-0.1796254813671112,
-0.030568523332476616,
0.11921762675046921,
0.07690974324941635,
-0.1640525460243225,
-0.07909505814313889,
-0.04051972180604935,
-0.06093563884496689,
-0.08196593821048737,
-0.06131401285529137,
0.08174535632133484,
0.04664049670100212,
0.05524424836039543,
-0.07875093072652817,
-0.059460606426000595,
0.0158400759100914,
-0.009211813099682331,
-0.03139946237206459,
0.0901939645409584,
0.07273924350738525,
-0.12483544647693634,
0.10482379794120789,
0.06626434624195099,
0.06889796257019043,
0.10992487519979477,
0.0030324056278914213,
-0.10129817575216293,
-0.017282668501138687,
0.037887852638959885,
0.010079976171255112,
0.16439227759838104,
-0.08274517953395844,
0.03866717964410782,
0.04586486890912056,
-0.03140925243496895,
0.013293097727000713,
-0.10816118121147156,
0.014137182384729385,
0.029531411826610565,
-0.016649728640913963,
0.010793685913085938,
-0.05292259156703949,
0.014706378802657127,
0.10823408514261246,
0.03359263762831688,
0.032809384167194366,
0.02373073808848858,
-0.04535824432969093,
-0.13099053502082825,
0.17709705233573914,
-0.0891105979681015,
-0.2558141350746155,
-0.13088452816009521,
-0.009369281120598316,
0.04229086637496948,
-0.016989465802907944,
0.022671543061733246,
-0.056313656270504,
-0.1054081991314888,
-0.10378290712833405,
0.0318046398460865,
0.05052268132567406,
-0.09002601355314255,
-0.0664730817079544,
0.05641505867242813,
0.04088861867785454,
-0.1303827166557312,
0.026516394689679146,
0.042090438306331635,
-0.06788553297519684,
0.008541574701666832,
0.053215909749269485,
0.08243905752897263,
0.1801401674747467,
0.008247803896665573,
-0.01302481908351183,
0.009755769744515419,
0.2179976999759674,
-0.14842036366462708,
0.08762172609567642,
0.14204081892967224,
-0.06799646466970444,
0.08390257507562637,
0.2011299431324005,
0.029746301472187042,
-0.09914945811033249,
0.03940511867403984,
0.03707100450992584,
-0.039259593933820724,
-0.24604962766170502,
-0.07261364907026291,
0.006433946080505848,
-0.06500997394323349,
0.10010333359241486,
0.08935008198022842,
0.10651203989982605,
0.049958426505327225,
-0.11518595367670059,
-0.07097794115543365,
0.04682750627398491,
0.12112680822610855,
-0.028284575790166855,
-0.007388358935713768,
0.09323699027299881,
-0.02779475785791874,
0.02935989759862423,
0.0927397683262825,
0.02686217986047268,
0.19634699821472168,
0.037253402173519135,
0.1330881416797638,
0.09396109730005264,
0.06280652433633804,
0.02010536380112171,
0.01708180457353592,
0.015533287078142166,
0.030100706964731216,
-0.022734519094228745,
-0.08217218518257141,
-0.0064850482158362865,
0.14045384526252747,
0.028358059003949165,
0.047067172825336456,
0.0054138582199811935,
-0.050519928336143494,
0.07114485651254654,
0.16704896092414856,
0.014490289613604546,
-0.22024035453796387,
-0.06729906052350998,
0.07841052860021591,
-0.07070231437683105,
-0.11687877029180527,
-0.011938784271478653,
0.036938004195690155,
-0.18149414658546448,
0.03585916385054588,
-0.023140614852309227,
0.10183990001678467,
-0.10788391530513763,
-0.02343798615038395,
0.03441723808646202,
0.05932255834341049,
-0.03287558630108833,
0.08174688369035721,
-0.21104924380779266,
0.14513428509235382,
0.009222227148711681,
0.06495018303394318,
-0.10594829171895981,
0.0785311833024025,
0.012096169404685497,
-0.00010399520397186279,
0.1753602921962738,
-0.004946180619299412,
-0.05306371673941612,
-0.08788393437862396,
-0.07348717004060745,
-0.011570964008569717,
0.10219644010066986,
-0.11301751434803009,
0.0919216126203537,
-0.006671504583209753,
-0.02968967892229557,
-0.0015144519275054336,
-0.12411268800497055,
-0.12614630162715912,
-0.18059955537319183,
0.048917658627033234,
-0.12901310622692108,
0.03660067170858383,
-0.11326277256011963,
-0.05896054953336716,
-0.033213816583156586,
0.19080448150634766,
-0.2089945673942566,
-0.0845150500535965,
-0.1439433991909027,
-0.05837400630116463,
0.11475379765033722,
-0.03810673579573631,
0.08270101249217987,
0.008430763147771358,
0.20551495254039764,
-0.003010113025084138,
0.000403517740778625,
0.09053049236536026,
-0.09361360967159271,
-0.21014350652694702,
-0.09628060460090637,
0.1443578600883484,
0.1290321946144104,
0.04536246508359909,
0.00031286876765079796,
0.015587059780955315,
-0.005217792931944132,
-0.11498799175024033,
0.03720242902636528,
0.15110363066196442,
0.09938907623291016,
0.043811969459056854,
-0.029002564027905464,
-0.13600069284439087,
-0.10245570540428162,
-0.05769775062799454,
0.015730546787381172,
0.2012956440448761,
-0.07231741398572922,
0.16824878752231598,
0.15526428818702698,
-0.05860832706093788,
-0.20668168365955353,
0.03981078416109085,
0.030895283445715904,
-0.006049614865332842,
0.04320519417524338,
-0.20029093325138092,
0.06697110086679459,
0.013522611930966377,
-0.05706821009516716,
0.1384991705417633,
-0.17863737046718597,
-0.14717553555965424,
0.08729562908411026,
0.08795326203107834,
-0.19967041909694672,
-0.13047698140144348,
-0.09727919846773148,
-0.04887104406952858,
-0.11643301695585251,
0.0954473689198494,
-0.01034938357770443,
0.00644347071647644,
0.02943265251815319,
0.014792537316679955,
0.01717582903802395,
-0.05249704420566559,
0.20024169981479645,
-0.0031617581844329834,
0.04977048933506012,
-0.07458613812923431,
-0.08326690644025803,
0.05189245194196701,
-0.06262268871068954,
0.08512204140424728,
-0.02232930064201355,
0.011282147839665413,
-0.12348084896802902,
-0.06796886771917343,
-0.05566633865237236,
0.024876773357391357,
-0.0935557559132576,
-0.10108795762062073,
-0.05694815143942833,
0.10562699288129807,
0.09605633467435837,
-0.03378688544034958,
-0.07535665482282639,
-0.09805359691381454,
0.05181685462594032,
0.22370406985282898,
0.18468716740608215,
0.07653791457414627,
-0.0860554501414299,
-0.010018577799201012,
-0.022519495338201523,
0.05901143699884415,
-0.21836121380329132,
0.04584529250860214,
0.03836448863148689,
0.037701647728681564,
0.1331673115491867,
-0.022388923913240433,
-0.1646881401538849,
-0.045324213802814484,
0.05375394970178604,
-0.06963463127613068,
-0.17386744916439056,
0.004559111315757036,
0.08124831318855286,
-0.15838943421840668,
-0.04816775396466255,
0.02879445068538189,
-0.026583047583699226,
-0.025924822315573692,
0.0035989710595458746,
0.0804956927895546,
0.02167467586696148,
0.09829863905906677,
0.07253812253475189,
0.11784360557794571,
-0.10475602000951767,
0.07147132605314255,
0.07766921818256378,
-0.1183786541223526,
0.033319998532533646,
0.05343807488679886,
-0.06441166251897812,
-0.03152685984969139,
0.021238690242171288,
0.07744776457548141,
0.030669089406728745,
-0.0720914676785469,
0.0030328123830258846,
-0.11422017216682434,
0.06784636527299881,
0.1446647047996521,
0.039866913110017776,
0.010241357609629631,
0.04654799401760101,
0.0313367135822773,
-0.09969954192638397,
0.12000445276498795,
0.03793122619390488,
0.034675128757953644,
-0.05219447612762451,
-0.006350463721901178,
0.04507572576403618,
-0.009730980731546879,
-0.01692533865571022,
-0.03980020806193352,
-0.06630539894104004,
-0.002227820223197341,
-0.17145000398159027,
0.026521187275648117,
-0.061845384538173676,
0.012216710485517979,
0.015618357807397842,
-0.03043844737112522,
0.004895725753158331,
0.01318447757512331,
-0.07884406298398972,
-0.03733738884329796,
0.0026910637971013784,
0.10190366208553314,
-0.16608543694019318,
0.0065719615668058395,
0.08680541813373566,
-0.13178376853466034,
0.08610151708126068,
-0.0027042021974921227,
-0.010017439723014832,
0.021784408017992973,
-0.1385512351989746,
0.06294634938240051,
-0.009974944405257702,
0.006947639863938093,
0.025122690945863724,
-0.20444543659687042,
0.003976424224674702,
-0.0502600222826004,
-0.06445887684822083,
-0.0011681586038321257,
-0.038139618933200836,
-0.11466933786869049,
0.09938924759626389,
0.020413469523191452,
-0.07895620912313461,
-0.0221401397138834,
0.05254509299993515,
0.10368907451629639,
-0.04709184169769287,
0.13944989442825317,
-0.011523711495101452,
0.05696758255362511,
-0.18287083506584167,
-0.02139449492096901,
-0.016634542495012283,
0.021677732467651367,
-0.025945905596017838,
-0.0014768552500754595,
0.04870397225022316,
-0.024354778230190277,
0.2333051711320877,
-0.03120492212474346,
0.023413510993123055,
0.06554826349020004,
-0.005246917717158794,
-0.01005570124834776,
0.09247083216905594,
0.06280691921710968,
0.006047483067959547,
0.026575298979878426,
0.013055658899247646,
-0.05032086744904518,
-0.015141602605581284,
-0.12894347310066223,
0.08493354916572571,
0.16985470056533813,
0.0912419930100441,
-0.006043106317520142,
0.054353393614292145,
-0.11146140098571777,
-0.09290971606969833,
0.10712950676679611,
-0.021798735484480858,
-0.013565287925302982,
-0.05129361152648926,
0.1526717245578766,
0.16535356640815735,
-0.18747006356716156,
0.06838773190975189,
-0.06590040773153305,
-0.05774319916963577,
-0.10396960377693176,
-0.1736048310995102,
-0.058737896382808685,
-0.04148640111088753,
-0.0014276166912168264,
-0.06220769137144089,
0.06891323626041412,
0.11430013924837112,
0.01645878702402115,
0.0030132692772895098,
0.08721863478422165,
-0.02335207536816597,
0.0073115942068398,
0.042498305439949036,
0.05724534019827843,
0.017757704481482506,
-0.055854495614767075,
0.01390614453703165,
0.01345670036971569,
0.027207477018237114,
0.05255920812487602,
0.03368041291832924,
-0.010791914537549019,
0.0023666610941290855,
-0.023355789482593536,
-0.09659216552972794,
0.0387103445827961,
-0.025840135291218758,
-0.044649962335824966,
0.1594165861606598,
0.019039129838347435,
-0.004390132613480091,
-0.025447912514209747,
0.2335977554321289,
-0.06348272413015366,
-0.07535601407289505,
-0.13545635342597961,
0.13397976756095886,
-0.04372372478246689,
0.05371178314089775,
0.0543164387345314,
-0.10723716765642166,
0.037706177681684494,
0.14293628931045532,
0.13284818828105927,
-0.03356185927987099,
0.01127989124506712,
0.016867216676473618,
0.005736035760492086,
-0.0272873155772686,
0.04870697110891342,
0.04691021889448166,
0.12474405020475388,
-0.06582619249820709,
0.08981626480817795,
-0.006426694802939892,
-0.09176424145698547,
-0.009551966562867165,
0.13901732861995697,
0.003880350152030587,
0.021723000332713127,
-0.09134092181921005,
0.11565329879522324,
-0.05851466581225395,
-0.2576787769794464,
0.07443003356456757,
-0.06408559530973434,
-0.14776328206062317,
-0.02171725407242775,
0.023623820394277573,
-0.00544528104364872,
0.0202016718685627,
0.05773065239191055,
-0.062478192150592804,
0.15378037095069885,
0.03621054068207741,
-0.07772532850503922,
-0.07883642613887787,
0.08430228382349014,
-0.0783846452832222,
0.30289405584335327,
0.0078877042979002,
0.06448312103748322,
0.09460984915494919,
-0.0401495061814785,
-0.13397376239299774,
0.0407712459564209,
0.09214770048856735,
-0.05453372746706009,
0.06215652450919151,
0.2163061797618866,
-0.01061305496841669,
0.11778761446475983,
0.07223958522081375,
-0.08420556038618088,
0.04974168911576271,
-0.07692530006170273,
-0.10101944953203201,
-0.09397020190954208,
0.0901845172047615,
-0.061835210770368576,
0.14743098616600037,
0.1304152011871338,
-0.04911902919411659,
0.0024146477226167917,
-0.02519647590816021,
0.05723709240555763,
-0.00011716534936567768,
0.11799878627061844,
0.03660281375050545,
-0.187918022274971,
0.03658631071448326,
0.00104029371868819,
0.09636683762073517,
-0.25620052218437195,
-0.08737737685441971,
0.04791741073131561,
-0.009769735857844353,
-0.055573008954524994,
0.12262251228094101,
0.059473756700754166,
0.05434578284621239,
-0.05604046955704689,
-0.051960308104753494,
-0.008857020176947117,
0.16002598404884338,
-0.10623971372842789,
-0.0027591893449425697
] |
null | null | transformers |
# Uploaded model
- **Developed by:** sanjay920
- **License:** apache-2.0
- **Finetuned from model :** codellama/CodeLlama-7b-Instruct-hf
| {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "llama", "trl"], "base_model": "codellama/CodeLlama-7b-Instruct-hf"} | text-generation | sanjay920/cortex-small-16bit | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"trl",
"en",
"base_model:codellama/CodeLlama-7b-Instruct-hf",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T04:01:58+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #text-generation-inference #trl #en #base_model-codellama/CodeLlama-7b-Instruct-hf #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: sanjay920
- License: apache-2.0
- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf
| [
"# Uploaded model\n\n- Developed by: sanjay920\n- License: apache-2.0\n- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #text-generation-inference #trl #en #base_model-codellama/CodeLlama-7b-Instruct-hf #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: sanjay920\n- License: apache-2.0\n- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf"
] | [
80,
43
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #text-generation-inference #trl #en #base_model-codellama/CodeLlama-7b-Instruct-hf #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# Uploaded model\n\n- Developed by: sanjay920\n- License: apache-2.0\n- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf"
] | [
-0.09922805428504944,
0.14187538623809814,
-0.003620576113462448,
0.04808757081627846,
0.04584633558988571,
-0.018410108983516693,
0.1382761150598526,
0.11475300788879395,
-0.054321907460689545,
-0.01778518781065941,
0.12908349931240082,
0.15186412632465363,
0.029984433203935623,
0.06964520364999771,
-0.04739869385957718,
-0.08490107953548431,
0.06224800646305084,
-0.008419428952038288,
-0.07951400429010391,
0.0739855095744133,
0.11662182956933975,
-0.024007128551602364,
0.10055046528577805,
-0.031920336186885834,
0.0053684301674366,
0.041744742542505264,
0.01617700792849064,
-0.07578734308481216,
0.06915932893753052,
0.022663865238428116,
0.04666665196418762,
0.09410693496465683,
0.03325628861784935,
-0.1923113912343979,
0.027778005227446556,
0.03952781483530998,
-0.06578407436609268,
0.031928423792123795,
0.02214902639389038,
-0.025243651121854782,
0.09658230096101761,
0.02138928696513176,
-0.05403532087802887,
0.08509616553783417,
-0.06115271896123886,
-0.05678793042898178,
-0.061819013208150864,
0.022755326703190804,
0.16537649929523468,
0.09291301667690277,
0.02728314884006977,
0.08035683631896973,
-0.02341631054878235,
0.08028890937566757,
0.0796063020825386,
-0.24798020720481873,
-0.021955927833914757,
0.16394788026809692,
0.032017942517995834,
0.03085213713347912,
0.003929094411432743,
0.04217393323779106,
0.09361159056425095,
-0.011110932566225529,
0.10288592427968979,
-0.10468625277280807,
-0.12291914969682693,
0.009960566647350788,
-0.07333896309137344,
-0.03137044608592987,
0.2394016683101654,
0.038740161806344986,
-0.03839229419827461,
-0.0020067316945642233,
-0.11382409930229187,
-0.0011204148177057505,
-0.05088247358798981,
0.04463475942611694,
0.05455819144845009,
0.09109844267368317,
0.09352146089076996,
-0.05110501870512962,
-0.13109450042247772,
-0.058505646884441376,
-0.02761862240731716,
-0.031787484884262085,
0.019176654517650604,
0.05707274377346039,
-0.15081137418746948,
0.06012852489948273,
0.03372634947299957,
-0.14954063296318054,
-0.026895951479673386,
-0.027383310720324516,
0.14529526233673096,
0.05941950902342796,
-0.031203020364046097,
-0.08545445650815964,
0.20561471581459045,
0.1543915718793869,
0.04482119902968407,
0.06082591041922569,
-0.07212549448013306,
0.03419309854507446,
-0.07129181176424026,
0.05088126286864281,
-0.05930516496300697,
-0.029627840965986252,
0.18103300034999847,
0.046065233647823334,
0.1293373852968216,
0.002579611958935857,
-0.11380612105131149,
-0.0068158600479364395,
0.05499706044793129,
0.11550140380859375,
0.05800261348485947,
0.09150254726409912,
-0.006198519375175238,
0.018819283694028854,
0.059805937111377716,
-0.11191823333501816,
-0.06174788251519203,
0.004166267812252045,
0.027457542717456818,
-0.02811715006828308,
0.10020451992750168,
0.04693058505654335,
-0.06072133406996727,
-0.11545023322105408,
-0.043966494500637054,
-0.04560298100113869,
-0.02753579430282116,
-0.001816892297938466,
0.07254690676927567,
-0.08640733361244202,
0.03933285176753998,
-0.1656753569841385,
-0.23360277712345123,
0.014072495512664318,
0.07992643117904663,
-0.0023293255362659693,
-0.013601203449070454,
-0.03989604860544205,
-0.042026277631521225,
-0.003942063078284264,
-0.03490690886974335,
-0.10227210819721222,
-0.08325893431901932,
0.027281442657113075,
-0.01454847026616335,
0.04871364310383797,
-0.17204897105693817,
0.02187281660735607,
-0.11455561220645905,
0.07399997115135193,
-0.0681132823228836,
0.005340998061001301,
-0.04719993472099304,
0.15317903459072113,
-0.0990624725818634,
0.014255759306252003,
0.01932094618678093,
0.022723225876688957,
0.0185087863355875,
0.21065416932106018,
-0.16638188064098358,
0.04343096539378166,
0.19401845335960388,
-0.11312694847583771,
-0.23864734172821045,
0.08405279368162155,
0.005152937490493059,
0.1229139119386673,
0.05369332432746887,
0.1350228190422058,
0.10893119126558304,
-0.07009726017713547,
0.08907736837863922,
0.09020596742630005,
-0.0007039486663416028,
-0.17047849297523499,
0.04645513743162155,
-0.028055502101778984,
-0.12615405023097992,
0.06415748596191406,
-0.050565510988235474,
0.04305274412035942,
0.0659412294626236,
-0.10432152450084686,
-0.059611473232507706,
-0.10161767899990082,
-0.05680009722709656,
-0.034337762743234634,
0.01663888245820999,
-0.0512208491563797,
-0.00047816161531955004,
-0.10327766090631485,
0.10380713641643524,
-0.07845375686883926,
0.033512454479932785,
-0.09271867573261261,
0.08928917348384857,
-0.04604095593094826,
0.028468633070588112,
-0.03311349079012871,
0.02672714926302433,
-0.0326286219060421,
0.009223518893122673,
-0.022428657859563828,
-0.033615343272686005,
0.043345823884010315,
-0.012075698934495449,
-0.009178206324577332,
-0.0638849064707756,
0.10752785205841064,
0.03527364134788513,
-0.03833627700805664,
-0.12707273662090302,
0.02235177904367447,
-0.00508964154869318,
0.26274344325065613,
-0.11610561609268188,
0.06560933589935303,
0.022229967638850212,
0.0758638009428978,
-0.026072347536683083,
0.07979261875152588,
0.06768452376127243,
-0.04077773913741112,
-0.05166498199105263,
-0.038487523794174194,
0.06707456707954407,
0.04559661075472832,
-0.11720193177461624,
0.0662536695599556,
-0.12348593026399612,
0.14049607515335083,
0.15202641487121582,
-0.09700333327054977,
0.07090611755847931,
0.04210054874420166,
0.024474505335092545,
-0.0011522505665197968,
0.05493311956524849,
-0.0231193695217371,
-0.05073525011539459,
-0.01875162497162819,
0.17160163819789886,
-0.11014258116483688,
-0.0035936918575316668,
0.01872519589960575,
-0.13379555940628052,
-0.0006950884126126766,
0.04204953834414482,
0.10209841281175613,
-0.0759492889046669,
0.11017182469367981,
0.30651164054870605,
-0.0805487111210823,
0.11810466647148132,
-0.07612795382738113,
-0.0138362692669034,
0.01058226078748703,
0.06068864092230797,
0.016777921468019485,
0.029269210994243622,
-0.06982293725013733,
0.020581189543008804,
0.04052310809493065,
-0.03723175451159477,
0.07113927602767944,
-0.13469848036766052,
-0.03331542760133743,
-0.003295263973996043,
-0.058369915932416916,
0.0020960671827197075,
0.02496674656867981,
-0.07346303015947342,
0.06635253131389618,
-0.04745567589998245,
-0.120484359562397,
0.07559070736169815,
-0.02369529940187931,
-0.11019568890333176,
0.18988433480262756,
-0.1316349357366562,
-0.21465426683425903,
-0.19418060779571533,
0.006704800762236118,
-0.11275225132703781,
0.025060025975108147,
0.09126245230436325,
-0.06291457265615463,
-0.058444466441869736,
-0.17122453451156616,
-0.07938931882381439,
0.05503850802779198,
-0.024672212079167366,
-0.008135069161653519,
0.06297609210014343,
0.08211951702833176,
-0.14627157151699066,
-0.03363453224301338,
0.055465128272771835,
-0.08496970683336258,
0.08167993277311325,
-0.11311282962560654,
0.12458649277687073,
0.14591148495674133,
0.017102284356951714,
0.0073857237584888935,
0.02174343355000019,
0.12382278591394424,
-0.011818884871900082,
0.0906415656208992,
0.2954280376434326,
0.0017495577922090888,
0.06560637056827545,
0.16331110894680023,
-0.0030205233488231897,
-0.09220119565725327,
0.014997722581028938,
-0.04223211482167244,
-0.07075876742601395,
-0.20237955451011658,
-0.06775181740522385,
-0.06304122507572174,
0.08598572015762329,
0.041539859026670456,
0.0559445358812809,
0.1542152315378189,
0.15634985268115997,
-0.06461578607559204,
0.031742267310619354,
0.021194515749812126,
0.09576928615570068,
0.09396388381719589,
0.021624363958835602,
0.05488820746541023,
-0.1309756636619568,
-0.011493557132780552,
0.07853595167398453,
0.09417708218097687,
-0.015321772545576096,
0.037760406732559204,
0.09272229671478271,
0.1001659706234932,
0.21416540443897247,
0.017466891556978226,
0.12540817260742188,
-0.03651786595582962,
0.016640635207295418,
-0.03784176707267761,
-0.10201990604400635,
-0.11067590117454529,
0.0761045441031456,
-0.21102853119373322,
-0.03689323738217354,
-0.026590975001454353,
0.04960069805383682,
0.043246764689683914,
0.2027796357870102,
0.08717991411685944,
-0.23609508574008942,
0.012424042448401451,
0.11044906079769135,
0.08754253387451172,
-0.044842831790447235,
0.10956356674432755,
-0.023288782685995102,
-0.024891382083296776,
0.10376457870006561,
-0.016397051513195038,
0.10477031022310257,
0.02977745421230793,
0.04567088186740875,
-0.05759677663445473,
-0.0024017752148211002,
0.02996385656297207,
0.1153411865234375,
-0.24339492619037628,
0.1529769003391266,
0.04696539416909218,
0.021753396838903427,
-0.08341427147388458,
0.04488762840628624,
0.06713306903839111,
0.17597997188568115,
0.12108258157968521,
-0.0028678986709564924,
-0.013801447115838528,
-0.058245737105607986,
-0.03639320284128189,
0.07908621430397034,
0.004779771436005831,
-0.04114747419953346,
0.043545905500650406,
-0.049691129475831985,
-0.01875877007842064,
0.0100710429251194,
0.025443147867918015,
-0.08450471609830856,
-0.10818029195070267,
0.027654236182570457,
0.16443365812301636,
0.05190074443817139,
-0.10035619139671326,
0.05160177871584892,
-0.0427914522588253,
0.08909813314676285,
-0.09503961354494095,
-0.09892358630895615,
-0.08394362032413483,
-0.14766521751880646,
0.05169987305998802,
-0.08137232810258865,
0.08728527277708054,
-0.06416305899620056,
0.01234473381191492,
-0.007166261784732342,
-0.19107556343078613,
0.07526569813489914,
-0.12474934756755829,
-0.034587614238262177,
0.00015838972467463464,
0.13860486447811127,
-0.10673045367002487,
-0.04985376447439194,
0.07682433724403381,
-0.029628964141011238,
-0.052538517862558365,
-0.10345375537872314,
-0.06396952271461487,
0.04688170179724693,
0.03678150102496147,
-0.03527997061610222,
-0.07773535698652267,
-0.06888927519321442,
0.009507088921964169,
-0.038415536284446716,
0.09605801105499268,
0.18635186553001404,
-0.03117167204618454,
0.06442026793956757,
0.22893036901950836,
-0.07784721255302429,
-0.29047277569770813,
-0.1434512436389923,
-0.16861608624458313,
-0.057819463312625885,
-0.009833794087171555,
-0.0981116071343422,
0.14815101027488708,
0.049222804605960846,
-0.07224901765584946,
0.03046879731118679,
-0.22284048795700073,
-0.08285126835107803,
0.15923026204109192,
0.10949143022298813,
0.22012752294540405,
-0.2009335309267044,
-0.07716017216444016,
-0.15669560432434082,
-0.2577408254146576,
0.02190093696117401,
-0.3108416497707367,
0.03384512662887573,
-0.008165626786649227,
-0.024378515779972076,
-0.008196324110031128,
-0.04998483508825302,
0.11553552746772766,
-0.031880639493465424,
0.08645666390657425,
-0.11268791556358337,
0.06714371591806412,
0.1571159064769745,
-0.06973270326852798,
0.15178945660591125,
-0.24626661837100983,
0.07355152815580368,
-0.10032936185598373,
0.006515278480947018,
-0.032942622900009155,
0.048312585800886154,
-0.04838714003562927,
-0.07144731283187866,
-0.03866461291909218,
-0.03900187462568283,
0.09136989712715149,
0.011987142264842987,
0.16820067167282104,
-0.01349000632762909,
0.06278803944587708,
0.26601654291152954,
0.12872371077537537,
-0.15043942630290985,
0.0976104810833931,
-0.04986043646931648,
-0.05126330256462097,
0.056421540677547455,
-0.24016553163528442,
0.09416747838258743,
0.0211456511169672,
-0.03214070200920105,
0.06720967590808868,
0.016666611656546593,
0.019619451835751534,
0.012567262165248394,
0.1139039397239685,
-0.14190222322940826,
-0.0670248419046402,
-0.046574968844652176,
0.11006391048431396,
-0.02105027809739113,
0.1779276579618454,
0.19294457137584686,
-0.02606944739818573,
0.008789905346930027,
-0.03124738484621048,
0.05875145643949509,
-0.05180365592241287,
0.04096464812755585,
0.09158212691545486,
0.024388356134295464,
-0.09540431946516037,
0.12050551176071167,
0.017743462696671486,
0.008445424027740955,
0.03434700146317482,
0.03786629065871239,
-0.1438986212015152,
-0.12468062341213226,
0.04281311482191086,
0.11693330854177475,
-0.1390969306230545,
-0.1310226023197174,
-0.11483599990606308,
-0.08630172908306122,
-0.04909352585673332,
0.16070036590099335,
0.07843693345785141,
0.03810815513134003,
0.0647835060954094,
-0.08817063271999359,
-0.028340306133031845,
0.03696766123175621,
-0.029710622504353523,
0.025255708023905754,
-0.15041731297969818,
-0.008336442522704601,
-0.013945833779871464,
0.05435861647129059,
-0.03490930050611496,
0.004058823920786381,
-0.06739883124828339,
0.00835652370005846,
-0.24829788506031036,
0.06923231482505798,
-0.11132047325372696,
0.006206965073943138,
-0.006624335423111916,
0.02087930217385292,
-0.040012020617723465,
0.05926976725459099,
-0.06772167235612869,
-0.016672933474183083,
-0.056067585945129395,
0.08185672760009766,
-0.10958004742860794,
-0.042537666857242584,
0.012598204426467419,
-0.05636489391326904,
0.06891500949859619,
-0.026965687051415443,
-0.0894981324672699,
0.07193906605243683,
-0.19734328985214233,
-0.01526868250221014,
0.044680844992399216,
0.022589920088648796,
-0.02324686013162136,
0.046331580728292465,
-0.03630266338586807,
0.09005150198936462,
-0.03700541704893112,
-0.03101600892841816,
0.04199518263339996,
-0.08163298666477203,
-0.03970058634877205,
-0.03892938792705536,
-0.02812833897769451,
-0.039431411772966385,
-0.02148786373436451,
0.11996441334486008,
-0.029288025572896004,
0.16663289070129395,
-0.058477938175201416,
0.014163807034492493,
-0.10743398219347,
-0.0037664039991796017,
-0.004641795996576548,
-0.07161849737167358,
-0.20366422832012177,
-0.09058070182800293,
-0.01903294026851654,
-0.06400104612112045,
0.11069142073392868,
-0.01552086416631937,
-0.0027676864992827177,
0.008090002462267876,
0.023685945197939873,
0.1739484816789627,
0.01754397712647915,
0.3148361146450043,
0.014543014578521252,
0.0163405854254961,
-0.07514894753694534,
-0.004453987814486027,
0.07993007451295853,
0.03661220520734787,
-0.03601368889212608,
0.11918409168720245,
-0.017382534220814705,
0.1424717903137207,
0.029222814366221428,
0.05722835287451744,
0.052574533969163895,
-0.03825298696756363,
-0.016098646447062492,
0.07691895216703415,
0.014569789171218872,
0.09213629364967346,
0.21666276454925537,
-0.046517934650182724,
-0.02001328580081463,
-0.04927900433540344,
-0.02612427808344364,
-0.11630624532699585,
-0.21550625562667847,
-0.12468485534191132,
-0.15585193037986755,
-0.02093646116554737,
-0.07812272012233734,
-0.02789374813437462,
0.13725577294826508,
0.016515830531716347,
-0.05028267949819565,
0.1128792092204094,
0.0037014521658420563,
-0.05325939133763313,
0.034354113042354584,
0.013837799429893494,
-0.028533069416880608,
0.07800035923719406,
-0.027311131358146667,
0.01597549021244049,
-0.02653748169541359,
-0.02439897693693638,
0.02508861944079399,
0.08395247906446457,
0.08072677999734879,
-0.08689851313829422,
-0.08964959532022476,
-0.0191679447889328,
0.015595752745866776,
0.031795743852853775,
0.10184954851865768,
0.03307396546006203,
-0.04370211064815521,
0.08474959433078766,
0.14535579085350037,
-0.051291730254888535,
-0.14050191640853882,
-0.08950785547494888,
0.10596739500761032,
-0.016034023836255074,
0.038556262850761414,
-0.019160356372594833,
-0.06853926926851273,
0.04506313055753708,
0.3253110349178314,
0.1893002837896347,
-0.07301383465528488,
0.02449677139520645,
-0.09836726635694504,
0.01606610044836998,
-0.02954760752618313,
0.12666936218738556,
0.08690322190523148,
0.06927505135536194,
-0.042024049907922745,
-0.031201718375086784,
-0.028787994757294655,
-0.04835376515984535,
-0.1733073890209198,
0.06955511122941971,
-0.09195315837860107,
-0.06665270030498505,
0.043345000594854355,
0.07093184441328049,
-0.03937549889087677,
-0.010721361264586449,
-0.03576287627220154,
-0.03789343312382698,
-0.017871452495455742,
-0.06307578831911087,
0.09757308661937714,
0.04730945825576782,
-0.009874232113361359,
-0.060481246560811996,
0.014946319162845612,
0.10655923932790756,
-0.017110807821154594,
-0.1305413395166397,
-0.04201652109622955,
0.030797798186540604,
-0.10508878529071808,
0.18417760729789734,
0.029818983748555183,
-0.00035255702096037567,
0.10374850779771805,
-0.015664827078580856,
-0.08995278924703598,
0.17586159706115723,
0.04649747908115387,
0.0038982664700597525,
0.04259872063994408,
-0.0845508724451065,
-0.03050888516008854,
-0.0007834059069864452,
0.04161880910396576,
-0.025570129975676537,
0.016862355172634125,
0.11763086169958115,
-0.08202853053808212,
-0.07000457495450974,
0.020989449694752693,
-0.10530044883489609,
0.08155161142349243,
0.007770280819386244,
-0.09277986735105515,
-0.022420335561037064,
-0.05106830596923828,
0.05605657026171684,
0.01079187635332346,
-0.18912772834300995,
0.01584768295288086,
-0.04667278751730919,
-0.01119054015725851,
0.0017300844192504883,
0.03669951856136322,
-0.19705605506896973,
0.02557935193181038,
-0.08918339014053345,
-0.0046678343787789345,
-0.124102883040905,
0.07175017148256302,
0.16948969662189484,
0.014286516234278679,
-0.012104654684662819,
-0.03784459829330444,
-0.03836303949356079,
0.08207015693187714,
-0.04195544496178627,
-0.13660413026809692
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | text-generation | sudipto-ducs/llama-2-7b-miniplatypus | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T04:05:46+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
56,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06061961501836777,
0.15481999516487122,
-0.004844071343541145,
0.02074851468205452,
0.0983177199959755,
0.007407687604427338,
0.07119518518447876,
0.11185134947299957,
-0.023851769044995308,
0.1167980208992958,
0.031993988901376724,
0.09781743586063385,
0.11217817664146423,
0.16186554729938507,
0.0015333457849919796,
-0.22897611558437347,
0.049678247421979904,
-0.125278040766716,
-0.0294334813952446,
0.11977242678403854,
0.1422213912010193,
-0.10954539477825165,
0.0752737894654274,
-0.038042325526475906,
-0.005828251596540213,
-0.0323176346719265,
-0.06205610930919647,
-0.05266609415411949,
0.05311284959316254,
0.06794639676809311,
0.07308239489793777,
0.01171939354389906,
0.09106900542974472,
-0.2724283039569855,
0.02348201349377632,
0.0805930644273758,
-0.0006441773730330169,
0.07586129754781723,
0.04993962123990059,
-0.08749990910291672,
0.07524524629116058,
-0.060156844556331635,
0.1498761922121048,
0.07955671846866608,
-0.09018243104219437,
-0.19217631220817566,
-0.07921334356069565,
0.09916994720697403,
0.1890910118818283,
0.05953684076666832,
-0.026427440345287323,
0.11642678081989288,
-0.08593545109033585,
0.013638701289892197,
0.06446459144353867,
-0.06054406240582466,
-0.055855002254247665,
0.06904532760381699,
0.08335285633802414,
0.08567540347576141,
-0.12976622581481934,
-0.010767064057290554,
0.015032444149255753,
0.008952446281909943,
0.08948688954114914,
0.017146794125437737,
0.1335189938545227,
0.040557652711868286,
-0.13501930236816406,
-0.043155476450920105,
0.09761431813240051,
0.03665134683251381,
-0.04888195917010307,
-0.2485782504081726,
-0.023432478308677673,
-0.04339504987001419,
-0.03198111802339554,
-0.03649339824914932,
0.043764639645814896,
-0.014506848528981209,
0.07738617807626724,
-0.004502781666815281,
-0.0837155357003212,
-0.04301247000694275,
0.07241875678300858,
0.06128999963402748,
0.02571401372551918,
-0.015821760520339012,
0.0059297760017216206,
0.12327717989683151,
0.11431120336055756,
-0.126715749502182,
-0.052547648549079895,
-0.06306339055299759,
-0.08449548482894897,
-0.044861067086458206,
0.030838407576084137,
0.037995077669620514,
0.045936476439237595,
0.23867325484752655,
0.007765117567032576,
0.053257301449775696,
0.04455438256263733,
0.014407169073820114,
0.06501194834709167,
0.11008983850479126,
-0.05894824117422104,
-0.09719445556402206,
-0.028582042083144188,
0.10156717151403427,
0.007986726239323616,
-0.04139331728219986,
-0.05712985619902611,
0.07059531658887863,
0.018587570637464523,
0.12360043078660965,
0.08000938594341278,
0.003056557849049568,
-0.0755772516131401,
-0.062465377151966095,
0.17764076590538025,
-0.15825673937797546,
0.04532013460993767,
0.03055616281926632,
-0.0341108962893486,
-0.009745313785970211,
0.012105142697691917,
0.025474950671195984,
-0.021481726318597794,
0.09522198140621185,
-0.05601342022418976,
-0.034448131918907166,
-0.11389608681201935,
-0.03694311901926994,
0.030394554138183594,
0.011153047904372215,
-0.02865210548043251,
-0.03502652049064636,
-0.08865131437778473,
-0.06405586749315262,
0.09101516753435135,
-0.07148737460374832,
-0.04784895107150078,
-0.016645915806293488,
-0.07833752781152725,
0.021804187446832657,
0.01691517047584057,
0.09064167737960815,
-0.0222476739436388,
0.03985358029603958,
-0.0550384595990181,
0.061440225690603256,
0.11723454296588898,
0.027987057343125343,
-0.05787884071469307,
0.061519939452409744,
-0.2424532175064087,
0.10252492874860764,
-0.07715212553739548,
0.04971238598227501,
-0.15203025937080383,
-0.02478341944515705,
0.03986154496669769,
0.01284773275256157,
-0.008251311257481575,
0.14196595549583435,
-0.21994100511074066,
-0.030957341194152832,
0.16964265704154968,
-0.10025953501462936,
-0.08109250664710999,
0.060782887041568756,
-0.05354252830147743,
0.11210215091705322,
0.04557164013385773,
-0.02375967986881733,
0.05775221437215805,
-0.14725260436534882,
-0.011030761525034904,
-0.041942402720451355,
-0.0180682260543108,
0.16207332909107208,
0.0703711211681366,
-0.06047816202044487,
0.07456906884908676,
0.01960151270031929,
-0.014246034435927868,
-0.04887177795171738,
-0.02822130173444748,
-0.1047162413597107,
0.01184528972953558,
-0.06102835759520531,
0.018109694123268127,
-0.021768750622868538,
-0.09445013850927353,
-0.029118487611413002,
-0.17402999103069305,
-0.0031633328180760145,
0.08821269869804382,
-0.011630427092313766,
-0.021509924903512,
-0.11245372891426086,
0.009332616813480854,
0.030967719852924347,
0.0002618339203763753,
-0.13677829504013062,
-0.06033218279480934,
0.026970699429512024,
-0.16097871959209442,
0.029791243374347687,
-0.05741601809859276,
0.04530094936490059,
0.04005871340632439,
-0.03433511033654213,
-0.03489551320672035,
0.010874404571950436,
0.010431389324367046,
-0.01894843392074108,
-0.25422003865242004,
-0.01882786676287651,
-0.0234990194439888,
0.1751047968864441,
-0.22956320643424988,
0.042598169296979904,
0.07489731162786484,
0.1460893303155899,
0.007349682506173849,
-0.03550100699067116,
0.015185600146651268,
-0.07262228429317474,
-0.03268764168024063,
-0.06316669285297394,
-0.01207790058106184,
-0.038400664925575256,
-0.05820201337337494,
0.04906858503818512,
-0.1686294972896576,
-0.030321966856718063,
0.10717973858118057,
0.06342670321464539,
-0.1473218947649002,
-0.02780107781291008,
-0.04056945815682411,
-0.04624456167221069,
-0.06676914542913437,
-0.05461418256163597,
0.11812574416399002,
0.056411582976579666,
0.04860803112387657,
-0.07140495628118515,
-0.07455260306596756,
0.008036690764129162,
-0.01956399530172348,
-0.014917809516191483,
0.09334591031074524,
0.07554110884666443,
-0.12264352291822433,
0.09177418053150177,
0.09668384492397308,
0.08576478064060211,
0.10314212739467621,
-0.014663571491837502,
-0.08914592862129211,
-0.040637146681547165,
0.02245822176337242,
0.016187267377972603,
0.15129362046718597,
-0.012961224652826786,
0.055492039769887924,
0.0358695350587368,
-0.014034898020327091,
0.011105312965810299,
-0.09736533463001251,
0.02655916102230549,
0.030835967510938644,
-0.016302183270454407,
0.03745110332965851,
-0.0447014644742012,
0.019208140671253204,
0.09039704501628876,
0.040895868092775345,
0.040978945791721344,
0.010155045427381992,
-0.04354988783597946,
-0.11037563532590866,
0.1787576973438263,
-0.12389461696147919,
-0.24818050861358643,
-0.13812170922756195,
0.010281167924404144,
0.04737642779946327,
-0.010411068797111511,
0.006690691225230694,
-0.06616118550300598,
-0.1175973042845726,
-0.09878289699554443,
0.018617089837789536,
0.045352302491664886,
-0.07590975612401962,
-0.06842505931854248,
0.06414616107940674,
0.03875524550676346,
-0.13939815759658813,
0.024007495492696762,
0.04662325978279114,
-0.08205481618642807,
-0.0029386086389422417,
0.0791812464594841,
0.06965780258178711,
0.17661017179489136,
0.013885351829230785,
-0.023669935762882233,
0.026634456589818,
0.20819635689258575,
-0.1436755359172821,
0.10975687950849533,
0.13545554876327515,
-0.08767466992139816,
0.08120133727788925,
0.1998777538537979,
0.03777998685836792,
-0.10680917650461197,
0.03608465939760208,
0.028374753892421722,
-0.028325283899903297,
-0.2502254545688629,
-0.06958996504545212,
0.0019060121849179268,
-0.05172049254179001,
0.07064855098724365,
0.08791537582874298,
0.09593888372182846,
0.016860228031873703,
-0.09976044297218323,
-0.07697858661413193,
0.046900223940610886,
0.10824491083621979,
-0.00015424020239152014,
-0.015208319760859013,
0.0904119610786438,
-0.03033481352031231,
0.01743943803012371,
0.09215071052312851,
0.0030607767403125763,
0.17535938322544098,
0.051709048449993134,
0.17189906537532806,
0.07866133749485016,
0.06444311141967773,
0.02004685252904892,
0.007725914940237999,
0.021817529574036598,
0.017227526754140854,
-0.0030957073904573917,
-0.08709781616926193,
-0.0034981227945536375,
0.1202581599354744,
0.049845851957798004,
0.029173865914344788,
0.012042860500514507,
-0.030704669654369354,
0.08337877690792084,
0.1770893782377243,
0.0029054484330117702,
-0.1893385946750641,
-0.07169844210147858,
0.07795937359333038,
-0.08648337423801422,
-0.10729733109474182,
-0.029470939189195633,
0.041069481521844864,
-0.1729043871164322,
0.016882894560694695,
-0.019335895776748657,
0.10788324475288391,
-0.13190391659736633,
-0.01772487722337246,
0.05657728388905525,
0.06932812184095383,
-0.009677323512732983,
0.06694949418306351,
-0.16090403497219086,
0.11770165711641312,
0.01751571334898472,
0.06636732816696167,
-0.09608277678489685,
0.09618937969207764,
-0.007830657996237278,
0.0041499207727611065,
0.1410749852657318,
0.010120149701833725,
-0.05952107161283493,
-0.09608154743909836,
-0.10546442121267319,
-0.009841260500252247,
0.1306990385055542,
-0.14852415025234222,
0.08813067525625229,
-0.02661319263279438,
-0.044553373008966446,
0.003614129964262247,
-0.12497276812791824,
-0.13103094696998596,
-0.18366187810897827,
0.05707118660211563,
-0.12947207689285278,
0.04045100137591362,
-0.10902881622314453,
-0.045833900570869446,
-0.02098964899778366,
0.20040063560009003,
-0.23137451708316803,
-0.06714103370904922,
-0.1551055610179901,
-0.08061286807060242,
0.14446212351322174,
-0.046455029398202896,
0.08550118654966354,
0.0008278203313238919,
0.19068008661270142,
0.021319707855582237,
-0.017237508669495583,
0.1072206199169159,
-0.10052918642759323,
-0.2010865956544876,
-0.09273224323987961,
0.15895552933216095,
0.13766798377037048,
0.03809428587555885,
-0.004381525795906782,
0.03171157464385033,
-0.02098114788532257,
-0.12076930701732635,
0.020226983353495598,
0.17317426204681396,
0.08982043713331223,
0.025265544652938843,
-0.02972041629254818,
-0.11267432570457458,
-0.07061342149972916,
-0.03774050623178482,
0.024755435064435005,
0.18072067201137543,
-0.07222156971693039,
0.18405316770076752,
0.13775517046451569,
-0.05534014105796814,
-0.19904261827468872,
0.021996473893523216,
0.04293542355298996,
0.0070380112156271935,
0.0323902890086174,
-0.20307663083076477,
0.09384101629257202,
0.0008334947633557022,
-0.05131231248378754,
0.1379684954881668,
-0.1823476254940033,
-0.151598259806633,
0.06042521819472313,
0.043563615530729294,
-0.19374065101146698,
-0.12374074012041092,
-0.08848230540752411,
-0.04693066328763962,
-0.15487661957740784,
0.10312657803297043,
0.0020827590487897396,
0.008401188999414444,
0.03778626397252083,
0.02252252586185932,
0.012139533646404743,
-0.04198719933629036,
0.1914343535900116,
-0.025891713798046112,
0.03347287327051163,
-0.0790715217590332,
-0.060851071029901505,
0.062408581376075745,
-0.058187782764434814,
0.0755455270409584,
-0.025226406753063202,
0.015947066247463226,
-0.10598332434892654,
-0.048235729336738586,
-0.02852320298552513,
0.019321219995617867,
-0.09431382268667221,
-0.09348297864198685,
-0.04829427972435951,
0.09367614984512329,
0.09042316675186157,
-0.03652578964829445,
-0.03649144619703293,
-0.078715980052948,
0.038977332413196564,
0.17627815902233124,
0.18159319460391998,
0.04659178853034973,
-0.07959239184856415,
-0.001915142871439457,
-0.014336181804537773,
0.04684065282344818,
-0.22077152132987976,
0.060553863644599915,
0.04557652771472931,
0.016117896884679794,
0.11537692695856094,
-0.0208132341504097,
-0.16198977828025818,
-0.06710557639598846,
0.061360616236925125,
-0.06944561004638672,
-0.17825035750865936,
0.0039279889315366745,
0.07344977557659149,
-0.16578389704227448,
-0.037031736224889755,
0.04200848564505577,
-0.01189455483108759,
-0.0403641052544117,
0.012352054007351398,
0.08063354343175888,
0.007078902795910835,
0.07699975371360779,
0.055281639099121094,
0.09124495089054108,
-0.10227900743484497,
0.07410510629415512,
0.08149529248476028,
-0.08644098788499832,
0.030720343813300133,
0.09573426842689514,
-0.06469762325286865,
-0.0346054881811142,
0.04237886518239975,
0.08354541659355164,
0.024281201884150505,
-0.04682289808988571,
0.0023111123591661453,
-0.09734189510345459,
0.05927345156669617,
0.11483542621135712,
0.03496333956718445,
0.011234734207391739,
0.03813567012548447,
0.04486291855573654,
-0.08093374222517014,
0.11926916986703873,
0.023795632645487785,
0.020354853942990303,
-0.04112942889332771,
-0.040553025901317596,
0.035851649940013885,
-0.026020776480436325,
-0.011440055444836617,
-0.035174157470464706,
-0.0722682997584343,
-0.014069457538425922,
-0.16000694036483765,
-0.0076758842915296555,
-0.03660871088504791,
0.005114538595080376,
0.022510098293423653,
-0.03652830421924591,
0.00792311318218708,
0.012217256240546703,
-0.06868947297334671,
-0.05553458258509636,
-0.023233558982610703,
0.09422210603952408,
-0.16494666039943695,
0.0220257006585598,
0.0823851153254509,
-0.12121747434139252,
0.09289738535881042,
0.016782134771347046,
0.00412249518558383,
0.026962365955114365,
-0.1545863002538681,
0.04763968288898468,
-0.020152103155851364,
0.013473534025251865,
0.04222847521305084,
-0.21637047827243805,
-0.004404853098094463,
-0.04015503451228142,
-0.05566934496164322,
-0.008993052877485752,
-0.0319182425737381,
-0.11338426172733307,
0.09645436704158783,
0.011025024577975273,
-0.08443772792816162,
-0.02965564839541912,
0.03353232145309448,
0.07690354436635971,
-0.027447547763586044,
0.1498211771249771,
-0.004663881380110979,
0.07559948414564133,
-0.17581342160701752,
-0.02282017655670643,
-0.011197620071470737,
0.022367527708411217,
-0.021871577948331833,
-0.01622559316456318,
0.04623444378376007,
-0.02704801969230175,
0.19120801985263824,
-0.024701936170458794,
0.049393873661756516,
0.06364397704601288,
0.009232889860868454,
-0.013832193799316883,
0.11151392012834549,
0.05708572641015053,
0.024334950372576714,
0.022262847051024437,
0.003451440716162324,
-0.04008655622601509,
-0.009981024079024792,
-0.18596695363521576,
0.06803664565086365,
0.14585918188095093,
0.09060460329055786,
-0.012669353745877743,
0.0707244873046875,
-0.10161512345075607,
-0.12005364894866943,
0.10127941519021988,
-0.06415384262800217,
-0.010188822634518147,
-0.06542414426803589,
0.14027701318264008,
0.14953285455703735,
-0.1886233240365982,
0.06583356112241745,
-0.06602055579423904,
-0.0566304549574852,
-0.11457879096269608,
-0.1930263340473175,
-0.057075321674346924,
-0.050602465867996216,
-0.018466074019670486,
-0.05384097993373871,
0.06939727067947388,
0.05750798434019089,
0.01126816775649786,
0.00868057832121849,
0.08568526059389114,
-0.009656033478677273,
0.00248199631460011,
0.030120067298412323,
0.06713981181383133,
0.016768986359238625,
-0.0321255661547184,
0.0179112758487463,
-0.00597198773175478,
0.034156378358602524,
0.059282708913087845,
0.03608176112174988,
-0.028436895459890366,
0.015559280291199684,
-0.034912437200546265,
-0.11309733241796494,
0.042801856994628906,
-0.029640642926096916,
-0.0749855786561966,
0.1347348988056183,
0.026981467381119728,
0.005015076603740454,
-0.023140020668506622,
0.2503887414932251,
-0.07436972856521606,
-0.09334370493888855,
-0.14373961091041565,
0.11701542884111404,
-0.04212593287229538,
0.0635172426700592,
0.03596310690045357,
-0.10810714215040207,
0.017985546961426735,
0.1320217251777649,
0.15442703664302826,
-0.04732590913772583,
0.019251897931098938,
0.028577854856848717,
0.00439635943621397,
-0.04075566306710243,
0.05177190154790878,
0.07100846618413925,
0.14500564336776733,
-0.05157303810119629,
0.08530787378549576,
0.002609728369861841,
-0.1021018698811531,
-0.041973695158958435,
0.11415864527225494,
-0.014296893030405045,
0.017620453611016273,
-0.057136841118335724,
0.124222531914711,
-0.05874236673116684,
-0.23697422444820404,
0.06316976249217987,
-0.0765061303973198,
-0.1432730257511139,
-0.024886758998036385,
0.071670763194561,
-0.016632623970508575,
0.02605951391160488,
0.07167234271764755,
-0.0754380151629448,
0.18880942463874817,
0.03957989811897278,
-0.05233397334814072,
-0.05954399332404137,
0.0744764655828476,
-0.11850855499505997,
0.27879106998443604,
0.010482731275260448,
0.051307905465364456,
0.1042102724313736,
-0.02021743729710579,
-0.13270841538906097,
0.023401619866490364,
0.09579801559448242,
-0.08917027711868286,
0.04087764397263527,
0.21448291838169098,
-0.00629545608535409,
0.11935057491064072,
0.07611140608787537,
-0.07468950748443604,
0.047562725841999054,
-0.11468592286109924,
-0.07639975845813751,
-0.08699081838130951,
0.09244474768638611,
-0.06785612553358078,
0.14258281886577606,
0.12599852681159973,
-0.05530165135860443,
0.011584274470806122,
-0.028389399871230125,
0.045467376708984375,
0.005578654818236828,
0.100032277405262,
0.011115525849163532,
-0.18496567010879517,
0.024811718612909317,
0.016259413212537766,
0.10884406417608261,
-0.18112654983997345,
-0.09105053544044495,
0.046958595514297485,
0.0005061255069449544,
-0.06443515419960022,
0.12483241409063339,
0.057313691824674606,
0.04654949903488159,
-0.0451689288020134,
-0.026830285787582397,
-0.006042256020009518,
0.14264579117298126,
-0.10707559436559677,
-0.005129707511514425
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": ["unsloth"]} | text-generation | rubra-ai/cortex-small-v0.1-lora | [
"transformers",
"safetensors",
"llama",
"text-generation",
"unsloth",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | 2024-02-11T04:08:47+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #unsloth #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #unsloth #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
63,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #unsloth #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.04292343929409981,
0.18826867640018463,
-0.005377055611461401,
0.01779043860733509,
0.10202369838953018,
0.006763845216482878,
0.05548536777496338,
0.11715483665466309,
-0.05078177899122238,
0.12557542324066162,
0.0411979965865612,
0.11146166175603867,
0.11804298311471939,
0.14329783618450165,
0.00002410791057627648,
-0.21835729479789734,
0.049665696918964386,
-0.10991441458463669,
-0.0106809725984931,
0.12213768064975739,
0.14416629076004028,
-0.10152151435613632,
0.06854484230279922,
-0.03602901101112366,
-0.017661886289715767,
-0.03734491392970085,
-0.06368496268987656,
-0.041672609746456146,
0.03853093832731247,
0.05424622446298599,
0.0640019103884697,
0.0008005748968571424,
0.0846111923456192,
-0.27982035279273987,
0.018390439450740814,
0.06937906891107559,
-0.0023142043501138687,
0.06504538655281067,
0.06703895330429077,
-0.0643777847290039,
0.10560540109872818,
-0.05572549253702164,
0.1365208476781845,
0.08376910537481308,
-0.09230275452136993,
-0.18153217434883118,
-0.0921248346567154,
0.1093878373503685,
0.17717865109443665,
0.05059289559721947,
-0.02799699455499649,
0.10320482403039932,
-0.08263788372278214,
0.016451768577098846,
0.05110875144600868,
-0.08650156855583191,
-0.05617035552859306,
0.06494492292404175,
0.09247919917106628,
0.052732132375240326,
-0.1271737962961197,
-0.03365660458803177,
0.004899790044873953,
0.016557635739445686,
0.07190205156803131,
0.021786099299788475,
0.1472795307636261,
0.034876905381679535,
-0.1331535279750824,
-0.051329996436834335,
0.1048947125673294,
0.04056032747030258,
-0.040847018361091614,
-0.2426268309354782,
-0.027707915753126144,
-0.025109421461820602,
-0.03402986750006676,
-0.0437135249376297,
0.04242107644677162,
-0.0035838026087731123,
0.08458299934864044,
-0.007490561809390783,
-0.07259652763605118,
-0.03244706988334656,
0.0688263401389122,
0.064784474670887,
0.030094482004642487,
-0.020735738798975945,
0.02483791671693325,
0.10849814862012863,
0.0949249416589737,
-0.11696284264326096,
-0.058448728173971176,
-0.06557316333055496,
-0.07224222272634506,
-0.04181387275457382,
0.03500311076641083,
0.015896132215857506,
0.071471206843853,
0.2602509558200836,
0.01899585872888565,
0.05600179731845856,
0.029530007392168045,
0.0073724533431231976,
0.05294303596019745,
0.10623796284198761,
-0.06396427750587463,
-0.11310389637947083,
-0.02034088596701622,
0.09129863977432251,
0.02021746337413788,
-0.036910805851221085,
-0.04569694399833679,
0.06657931953668594,
0.04505877196788788,
0.11183920502662659,
0.1006806343793869,
0.019416874274611473,
-0.07564955204725266,
-0.06204071268439293,
0.19905975461006165,
-0.15675219893455505,
0.039149727672338486,
0.043250180780887604,
-0.03578011691570282,
-0.02036311849951744,
0.009607705287635326,
0.026054807007312775,
-0.03432466462254524,
0.08814160525798798,
-0.05473000556230545,
-0.04614151641726494,
-0.11089799553155899,
-0.030556926503777504,
0.0442013218998909,
0.010448796674609184,
-0.03395242616534233,
-0.03711342439055443,
-0.07666761428117752,
-0.08680769801139832,
0.08644384890794754,
-0.07048791646957397,
-0.05712197721004486,
-0.027583591639995575,
-0.08218405395746231,
0.023172836750745773,
0.019756721332669258,
0.0729556605219841,
-0.025309210643172264,
0.05618005245923996,
-0.053604111075401306,
0.05488147959113121,
0.10356975346803665,
0.03610638156533241,
-0.06198744475841522,
0.05823414400219917,
-0.22975605726242065,
0.08514560014009476,
-0.06982189416885376,
0.06414492428302765,
-0.15622174739837646,
-0.02446330152451992,
0.03592666983604431,
0.004316574428230524,
-0.004745627753436565,
0.1365443617105484,
-0.20896528661251068,
-0.02342131733894348,
0.1669033318758011,
-0.09443739056587219,
-0.0715414509177208,
0.050615932792425156,
-0.04599856585264206,
0.10239199548959732,
0.03290434554219246,
0.002775689819827676,
0.0626225471496582,
-0.10854848474264145,
-0.013959519565105438,
-0.055099017918109894,
-0.025059405714273453,
0.13819867372512817,
0.07562530040740967,
-0.07902952283620834,
0.06477715075016022,
0.022813700139522552,
-0.020409759134054184,
-0.06547383219003677,
-0.01951533555984497,
-0.10126182436943054,
0.01546517014503479,
-0.06879144161939621,
0.011947265826165676,
-0.016198530793190002,
-0.09417803585529327,
-0.02866245061159134,
-0.16998343169689178,
-0.029649244621396065,
0.08252308517694473,
-0.004467182792723179,
-0.014274250715970993,
-0.10941161960363388,
0.02704133465886116,
0.03371654078364372,
0.0044359853491187096,
-0.13195890188217163,
-0.04033959284424782,
0.034737132489681244,
-0.15329891443252563,
0.03500048816204071,
-0.07348592579364777,
0.051377225667238235,
0.015687594190239906,
-0.029155118390917778,
-0.026816358789801598,
0.022950554266572,
0.00845371000468731,
-0.015416091307997704,
-0.23671619594097137,
-0.02562868967652321,
-0.02933376282453537,
0.1596956104040146,
-0.2073163241147995,
0.03471647948026657,
0.07962728291749954,
0.15802165865898132,
0.002939125057309866,
-0.05216621235013008,
0.019714290276169777,
-0.07012677937746048,
-0.024032827466726303,
-0.057665277272462845,
0.0032831889111548662,
-0.018774664029479027,
-0.04345292970538139,
0.025579115375876427,
-0.17645572125911713,
-0.046705566346645355,
0.09828836470842361,
0.04776141792535782,
-0.126988023519516,
-0.020474793389439583,
-0.03759893402457237,
-0.052560579031705856,
-0.04305299371480942,
-0.06037580594420433,
0.096319779753685,
0.06287256628274918,
0.03674183785915375,
-0.05966869741678238,
-0.07946930080652237,
-0.004839655943214893,
-0.0153745636343956,
-0.02353493496775627,
0.09512404352426529,
0.07751291990280151,
-0.13043329119682312,
0.09360626339912415,
0.08417011797428131,
0.07712284475564957,
0.08935420215129852,
-0.02144179306924343,
-0.075404092669487,
-0.0370500348508358,
0.03699750825762749,
0.019515717402100563,
0.12300322204828262,
-0.03906695544719696,
0.04399838298559189,
0.04019251465797424,
-0.027942534536123276,
0.01802278310060501,
-0.07876281440258026,
0.03273193538188934,
0.020718198269605637,
-0.014756618067622185,
0.050279535353183746,
-0.036855414509773254,
0.018754903227090836,
0.08659088611602783,
0.05881096050143242,
0.044072698801755905,
0.016800886020064354,
-0.052010320127010345,
-0.1115691065788269,
0.15924349427223206,
-0.12276260554790497,
-0.21748638153076172,
-0.1328210085630417,
0.014497416093945503,
0.026223482564091682,
-0.01506797969341278,
0.00576651468873024,
-0.05971094220876694,
-0.10903192311525345,
-0.09009502828121185,
0.005795407574623823,
0.057016320526599884,
-0.08362492173910141,
-0.06093323975801468,
0.04702426865696907,
0.043084245175123215,
-0.14079512655735016,
0.02152630127966404,
0.04325500503182411,
-0.09207198023796082,
-0.01115967147052288,
0.08168168365955353,
0.07780283689498901,
0.18435634672641754,
0.020768070593476295,
-0.021172961220145226,
0.032526228576898575,
0.22063808143138885,
-0.13656745851039886,
0.11198467016220093,
0.13181617856025696,
-0.08575399219989777,
0.08299451321363449,
0.20879633724689484,
0.04222285374999046,
-0.09664907306432724,
0.0304343793541193,
0.030948897823691368,
-0.022790847346186638,
-0.23554196953773499,
-0.06883510947227478,
0.0009722800459712744,
-0.0659257248044014,
0.07941686362028122,
0.09556294232606888,
0.07574138045310974,
0.01872626319527626,
-0.09533156454563141,
-0.09108595550060272,
0.05632733553647995,
0.10894450545310974,
0.014029460027813911,
-0.006910799536854029,
0.08843157440423965,
-0.03546027094125748,
0.01583779789507389,
0.08756837993860245,
0.0024584103375673294,
0.1598428189754486,
0.04778169468045235,
0.17317496240139008,
0.08422500640153885,
0.07279623299837112,
0.000603687425609678,
0.008512238040566444,
0.014100469648838043,
0.041183922439813614,
-0.005525778979063034,
-0.08351922780275345,
-0.02603893168270588,
0.11030695587396622,
0.06851852685213089,
0.01754682883620262,
0.01248775515705347,
-0.04759526997804642,
0.0871804729104042,
0.17926573753356934,
0.004300123080611229,
-0.18129703402519226,
-0.05778562277555466,
0.074430450797081,
-0.09818711876869202,
-0.10275593400001526,
-0.00784407276660204,
0.013536486774682999,
-0.16616149246692657,
0.03770674765110016,
-0.020995361730456352,
0.10762384533882141,
-0.13448180258274078,
-0.016813986003398895,
0.07832744717597961,
0.0712333619594574,
-0.0029534129425883293,
0.05958399921655655,
-0.18045948445796967,
0.09713280200958252,
0.011677161790430546,
0.07155559211969376,
-0.09598501026630402,
0.09018103778362274,
-0.007205406203866005,
-0.029768822714686394,
0.1431937962770462,
-0.003142349421977997,
-0.07371359318494797,
-0.06319711357355118,
-0.09517261385917664,
-0.010899929329752922,
0.1268581748008728,
-0.13050828874111176,
0.09160564839839935,
-0.03312861919403076,
-0.03596508502960205,
-0.011182941496372223,
-0.0880916640162468,
-0.1122843474149704,
-0.17711912095546722,
0.06018149107694626,
-0.12945356965065002,
0.03882477059960365,
-0.10549931228160858,
-0.026717960834503174,
-0.026683486998081207,
0.178618922829628,
-0.23788060247898102,
-0.07397715002298355,
-0.14370791614055634,
-0.09402398020029068,
0.1324852705001831,
-0.04830838367342949,
0.08988931030035019,
-0.015055065974593163,
0.15817634761333466,
0.021827908232808113,
-0.020078346133232117,
0.08633492141962051,
-0.0848253071308136,
-0.19780774414539337,
-0.06955822557210922,
0.16248609125614166,
0.12084493786096573,
0.03335541859269142,
-0.0013899571495130658,
0.037777941673994064,
-0.02108919247984886,
-0.11882339417934418,
0.022981705144047737,
0.15345308184623718,
0.06721732765436172,
0.011430226266384125,
-0.024014320224523544,
-0.10809025913476944,
-0.07674530893564224,
-0.029322028160095215,
0.02987777628004551,
0.1724686175584793,
-0.07139913737773895,
0.17051774263381958,
0.14364555478096008,
-0.0588962584733963,
-0.20953300595283508,
-0.0034934862051159143,
0.025866392999887466,
-0.00958812702447176,
0.01262340322136879,
-0.19036969542503357,
0.08587159216403961,
-0.002174045192077756,
-0.05474715679883957,
0.1073274239897728,
-0.1594780534505844,
-0.13815680146217346,
0.08379834145307541,
0.04926612973213196,
-0.18574541807174683,
-0.13679726421833038,
-0.09653197973966599,
-0.04133835434913635,
-0.15640324354171753,
0.09362965822219849,
0.022156093269586563,
0.012721545062959194,
0.02991352044045925,
0.015599608421325684,
0.024388102814555168,
-0.048591915518045425,
0.17602954804897308,
-0.016234640032052994,
0.02279195562005043,
-0.09626507014036179,
-0.07968656718730927,
0.018025947734713554,
-0.051882676780223846,
0.07170172780752182,
-0.017266500741243362,
0.012935908511281013,
-0.10264335572719574,
-0.03540561720728874,
-0.04268501326441765,
0.01661405898630619,
-0.099188432097435,
-0.085202656686306,
-0.04659072309732437,
0.09497132152318954,
0.09788262099027634,
-0.02253568172454834,
-0.026998797431588173,
-0.0772315189242363,
0.05453493818640709,
0.20757755637168884,
0.18566472828388214,
0.04546947404742241,
-0.06112571433186531,
-0.003745796624571085,
-0.016034787520766258,
0.04216223955154419,
-0.19591552019119263,
0.058634500950574875,
0.056738704442977905,
0.022449525073170662,
0.10273087024688721,
-0.019446061924099922,
-0.1581314206123352,
-0.0764765590429306,
0.06901811063289642,
-0.06423882395029068,
-0.20066112279891968,
0.008975905366241932,
0.05530434846878052,
-0.1775708645582199,
-0.03917059674859047,
0.04495568946003914,
-0.002727912273257971,
-0.03902778401970863,
0.023089852184057236,
0.09468687325716019,
0.003924074117094278,
0.0782470852136612,
0.07192396372556686,
0.0822129026055336,
-0.09933636337518692,
0.08582625538110733,
0.09758522361516953,
-0.0720822811126709,
0.028736449778079987,
0.10113639384508133,
-0.05638568103313446,
-0.03886125236749649,
0.034486688673496246,
0.08152203261852264,
0.025647565722465515,
-0.044451456516981125,
0.010355938225984573,
-0.09268626570701599,
0.06836600601673126,
0.09989523887634277,
0.029670365154743195,
0.017934802919626236,
0.04530128091573715,
0.046947747468948364,
-0.07622124254703522,
0.12428463250398636,
0.034861911088228226,
0.015623697079718113,
-0.04374397173523903,
-0.045552048832178116,
0.009736912325024605,
-0.03028755635023117,
-0.004958131350576878,
-0.02133471518754959,
-0.08800674229860306,
-0.015880294144153595,
-0.13308630883693695,
-0.009298216551542282,
-0.06151175871491432,
0.013635284267365932,
0.027435721829533577,
-0.032538071274757385,
0.005575480870902538,
0.005044261459261179,
-0.07019834965467453,
-0.0691831111907959,
-0.012711147777736187,
0.095164455473423,
-0.1670372188091278,
0.02610124461352825,
0.08352641016244888,
-0.11222398281097412,
0.09912886470556259,
0.012217588722705841,
-0.005713800899684429,
0.022394387051463127,
-0.14695370197296143,
0.03546147048473358,
-0.03938230127096176,
0.008286556228995323,
0.022746257483959198,
-0.19988538324832916,
-0.000013934964044892695,
-0.03536801412701607,
-0.06939463317394257,
-0.008364387787878513,
-0.027196144685149193,
-0.11335262656211853,
0.1067931056022644,
0.0012342236004769802,
-0.08100111037492752,
-0.03039664961397648,
0.031982820481061935,
0.07636885344982147,
-0.028471706435084343,
0.15208598971366882,
-0.013617309741675854,
0.06672896444797516,
-0.1587895303964615,
-0.011663785204291344,
-0.010776839219033718,
0.01560376025736332,
-0.03581136837601662,
-0.007234253454953432,
0.05085217207670212,
-0.013196735642850399,
0.17413955926895142,
-0.03515728563070297,
0.016792291775345802,
0.06547330319881439,
0.045002423226833344,
-0.034976135939359665,
0.0982886403799057,
0.051650237292051315,
0.017417224124073982,
0.008780776523053646,
0.011892673559486866,
-0.042148590087890625,
-0.03601905331015587,
-0.19182322919368744,
0.07043200731277466,
0.18725112080574036,
0.09618266671895981,
-0.020147977396845818,
0.07248927652835846,
-0.1016421988606453,
-0.09610612690448761,
0.15260624885559082,
-0.03709828853607178,
-0.005899024195969105,
-0.07303978502750397,
0.1281641572713852,
0.14302216470241547,
-0.18107613921165466,
0.06588808447122574,
-0.07227024435997009,
-0.04245559871196747,
-0.11048944294452667,
-0.19562652707099915,
-0.06181143969297409,
-0.04950173199176788,
-0.017301756888628006,
-0.046650297939777374,
0.06790224462747574,
0.06302686780691147,
-0.0009760049870237708,
-0.00815952941775322,
0.07094833999872208,
-0.03396129235625267,
-0.0016717935213819146,
0.029484858736395836,
0.059591714292764664,
0.0060126567259430885,
-0.036931898444890976,
0.016109824180603027,
-0.01176763791590929,
0.05502614006400108,
0.07581013441085815,
0.04883652552962303,
-0.027538318186998367,
0.020281067118048668,
-0.0400039367377758,
-0.10745270550251007,
0.04913952574133873,
-0.027562124654650688,
-0.07319166511297226,
0.15083648264408112,
0.020662441849708557,
0.005448428448289633,
-0.012079499661922455,
0.24070440232753754,
-0.064145527780056,
-0.10332037508487701,
-0.14430701732635498,
0.07491715997457504,
-0.041465189307928085,
0.049052558839321136,
0.038524940609931946,
-0.11372357606887817,
0.026006104424595833,
0.14732374250888824,
0.15270641446113586,
-0.0402783565223217,
0.022211361676454544,
0.03488355875015259,
0.00868822168558836,
-0.024850280955433846,
0.03838307037949562,
0.06393134593963623,
0.14742381870746613,
-0.0477873831987381,
0.07836286723613739,
0.0009453904931433499,
-0.08714000135660172,
-0.03805996850132942,
0.11301322281360626,
-0.010510249063372612,
0.015199603512883186,
-0.0608166866004467,
0.11857125908136368,
-0.07339458167552948,
-0.21728423237800598,
0.039847232401371,
-0.06880895793437958,
-0.1338454782962799,
-0.025233695283532143,
0.07665672153234482,
-0.010742755606770515,
0.021982967853546143,
0.07774899899959564,
-0.07041120529174805,
0.1911073625087738,
0.0385311022400856,
-0.058266088366508484,
-0.04942469671368599,
0.07217175513505936,
-0.07537322491407394,
0.29618796706199646,
0.015248388051986694,
0.039003998041152954,
0.11050893366336823,
-0.016553720459342003,
-0.14173917472362518,
0.022491389885544777,
0.0963440090417862,
-0.09687109291553497,
0.053855426609516144,
0.18176445364952087,
0.001875719171948731,
0.12723487615585327,
0.07698098570108414,
-0.08834564685821533,
0.045245129615068436,
-0.07325270026922226,
-0.07016976177692413,
-0.0993812158703804,
0.10319076478481293,
-0.08812170475721359,
0.14497129619121552,
0.12399062514305115,
-0.055769409984350204,
0.010903195478022099,
-0.034286584705114365,
0.04751160740852356,
-0.0033840627875179052,
0.12132634967565536,
0.012232412584125996,
-0.18882830440998077,
0.02651413343846798,
-0.026405373588204384,
0.10246428102254868,
-0.1690295934677124,
-0.08598951250314713,
0.04612896963953972,
0.009267891757190228,
-0.07218426465988159,
0.1265496462583542,
0.05560595914721489,
0.029229512438178062,
-0.049114905297756195,
-0.02625749073922634,
-0.01127582136541605,
0.14144857227802277,
-0.10424615442752838,
-0.004776977468281984
] |
null | null | transformers |
# Uploaded model
- **Developed by:** rubra-ai
- **License:** apache-2.0
- **Finetuned from model :** codellama/CodeLlama-7b-Instruct-hf
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
| {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "gguf"], "base_model": "codellama/CodeLlama-7b-Instruct-hf"} | null | rubra-ai/cortex-small-v0.1-GGUF | [
"transformers",
"gguf",
"llama",
"text-generation-inference",
"unsloth",
"en",
"base_model:codellama/CodeLlama-7b-Instruct-hf",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-11T04:22:49+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #llama #text-generation-inference #unsloth #en #base_model-codellama/CodeLlama-7b-Instruct-hf #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: rubra-ai
- License: apache-2.0
- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: rubra-ai\n- License: apache-2.0\n- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
"TAGS\n#transformers #gguf #llama #text-generation-inference #unsloth #en #base_model-codellama/CodeLlama-7b-Instruct-hf #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Uploaded model\n\n- Developed by: rubra-ai\n- License: apache-2.0\n- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
66,
81
] | [
"passage: TAGS\n#transformers #gguf #llama #text-generation-inference #unsloth #en #base_model-codellama/CodeLlama-7b-Instruct-hf #license-apache-2.0 #endpoints_compatible #region-us \n# Uploaded model\n\n- Developed by: rubra-ai\n- License: apache-2.0\n- Finetuned from model : codellama/CodeLlama-7b-Instruct-hf\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
] | [
-0.08745938539505005,
0.13389022648334503,
-0.003145229769870639,
0.07457835972309113,
0.07017320394515991,
0.04224654659628868,
0.05792272835969925,
0.1571575403213501,
-0.014038111083209515,
-0.01990891993045807,
0.09754228591918945,
0.1377968043088913,
0.05273914337158203,
-0.04597315937280655,
0.004402210935950279,
-0.12487487494945526,
0.075959213078022,
-0.011073525063693523,
-0.15983028709888458,
0.031692348420619965,
0.07178941369056702,
0.003305023768916726,
0.09372958540916443,
-0.017714180052280426,
-0.052898868918418884,
0.03604232892394066,
-0.0644339919090271,
-0.008870703168213367,
0.008252973668277264,
0.061702944338321686,
0.006441556848585606,
0.04841920733451843,
0.044970039278268814,
-0.14834551513195038,
0.025218548253178596,
0.03546251729130745,
-0.010048262774944305,
0.05085817351937294,
-0.026555906981229782,
0.06875487416982651,
0.17050854861736298,
-0.002901989035308361,
-0.08260732889175415,
0.07106088101863861,
-0.013154752552509308,
-0.08159647136926651,
-0.025459464639425278,
0.06598857790231705,
0.07028943300247192,
0.06717949360609055,
0.04588519036769867,
0.021632520481944084,
-0.0496138371527195,
0.04658552631735802,
0.15011705458164215,
-0.28347066044807434,
-0.0536021813750267,
0.16059690713882446,
-0.006561102345585823,
-0.0022783810272812843,
-0.029506202787160873,
0.042448367923498154,
0.05963151901960373,
-0.013691030442714691,
0.03218567743897438,
-0.08429458737373352,
-0.17672017216682434,
0.05939282104372978,
-0.08792285621166229,
0.0033043331932276487,
0.15033911168575287,
0.05472377687692642,
-0.031991008669137955,
0.05719822645187378,
-0.12409115582704544,
-0.006281574722379446,
-0.08030114322900772,
0.08257239311933517,
0.08540739119052887,
0.08446422964334488,
0.03935663402080536,
-0.07966993004083633,
-0.058055579662323,
-0.055733006447553635,
-0.046040140092372894,
0.07468508183956146,
0.07161547988653183,
0.11173604428768158,
-0.06566638499498367,
0.0764961987733841,
0.061145536601543427,
-0.1473715752363205,
-0.08691462129354477,
-0.010294499807059765,
0.08920948952436447,
0.10203740745782852,
-0.05445060506463051,
0.026453420519828796,
0.19914661347866058,
0.09711480885744095,
0.10539615154266357,
0.09072431921958923,
0.035044699907302856,
0.030294867232441902,
-0.09298330545425415,
0.10811720043420792,
-0.1305214911699295,
-0.0249106977134943,
0.13928844034671783,
0.055390674620866776,
0.06822050362825394,
0.0033662235364317894,
-0.12083111703395844,
-0.06455247849225998,
-0.023942390456795692,
0.06490548700094223,
-0.011066557839512825,
0.09367766231298447,
0.023125657811760902,
-0.03799588605761528,
-0.04280373454093933,
-0.12540243566036224,
-0.059231001883745193,
-0.014674740843474865,
-0.043841201812028885,
0.1310219168663025,
0.09548543393611908,
-0.006983826402574778,
-0.07067526131868362,
-0.16186749935150146,
-0.05841141566634178,
-0.015885422006249428,
-0.039621300995349884,
0.045091234147548676,
0.041490789502859116,
-0.08137916773557663,
0.021068226546049118,
-0.14155974984169006,
-0.24050627648830414,
0.02389700710773468,
0.14990119636058807,
-0.03713919594883919,
-0.022814704105257988,
-0.049878545105457306,
-0.040221769362688065,
0.012008626945316792,
-0.02031060680747032,
-0.02365666627883911,
-0.08120012283325195,
0.04582047462463379,
-0.01815037801861763,
0.08032185584306717,
-0.14266914129257202,
0.03800160810351372,
-0.07492607086896896,
0.0593147836625576,
-0.050723761320114136,
0.08969369530677795,
-0.05411692336201668,
0.13439564406871796,
-0.10040615499019623,
0.02464357204735279,
-0.026415321975946426,
0.02492278255522251,
0.04032699018716812,
0.1488312929868698,
-0.1527199149131775,
0.03576931729912758,
0.1638997495174408,
-0.01727081462740898,
-0.13873670995235443,
0.08517970889806747,
-0.00942823477089405,
0.1029827669262886,
0.05479302257299423,
0.0996922180056572,
0.16409556567668915,
-0.08846587687730789,
0.060719169676303864,
0.15822124481201172,
0.022478502243757248,
-0.15583954751491547,
0.060076866298913956,
0.028278179466724396,
-0.1383175551891327,
0.10568832606077194,
-0.09088503569364548,
0.11003641039133072,
0.053285516798496246,
-0.0903337374329567,
-0.10381857305765152,
-0.13161569833755493,
-0.08265399187803268,
-0.009826208464801311,
0.0333901047706604,
0.038228485733270645,
-0.048577938228845596,
-0.08496345579624176,
0.19148384034633636,
-0.10632102191448212,
0.01560985017567873,
-0.06192835047841072,
0.09269347041845322,
-0.0774247944355011,
0.07100274413824081,
-0.0523202046751976,
0.03416578844189644,
-0.051363226026296616,
-0.05312638729810715,
0.06325571238994598,
0.03380155190825462,
0.03213482350111008,
-0.056772347539663315,
0.010974334552884102,
0.016960864886641502,
0.05589017644524574,
-0.02003207989037037,
-0.043668653815984726,
-0.07931233942508698,
0.014682981185615063,
0.009581837803125381,
0.22163257002830505,
-0.054594703018665314,
0.056694839149713516,
-0.05101802572607994,
0.08327371627092361,
-0.06559357047080994,
0.06862270087003708,
0.05895204842090607,
-0.10030226409435272,
-0.01298573799431324,
-0.0824958086013794,
0.08131527900695801,
0.0666121244430542,
-0.08178374916315079,
0.01452071126550436,
-0.00256953202188015,
0.0927339419722557,
0.12587368488311768,
-0.018177276477217674,
0.06149069592356682,
0.03968529775738716,
-0.003410143544897437,
0.031951047480106354,
0.059623997658491135,
0.014319860376417637,
0.05205753818154335,
-0.019848009571433067,
0.1671883910894394,
-0.11917641013860703,
-0.01829395815730095,
0.016739066690206528,
-0.0945102721452713,
0.04994727298617363,
0.03474412113428116,
0.14942988753318787,
-0.08930137008428574,
0.03809423744678497,
0.27126213908195496,
-0.11395370960235596,
0.17192664742469788,
-0.08900970965623856,
-0.060814667493104935,
-0.00005855189374415204,
0.05182633921504021,
-0.0228401068598032,
0.015704238787293434,
-0.049133263528347015,
0.015123291872441769,
0.025359658524394035,
-0.05417345091700554,
0.0804496482014656,
-0.1456713229417801,
-0.006287029013037682,
-0.03303711488842964,
-0.08622698485851288,
0.03204960748553276,
0.037036385387182236,
-0.07409678399562836,
0.05322187766432762,
-0.00821949914097786,
-0.11511615663766861,
0.05818130820989609,
0.019302083179354668,
-0.0328763984143734,
0.17386068403720856,
-0.05778824910521507,
-0.1526818424463272,
-0.17489218711853027,
-0.005147231742739677,
-0.13629436492919922,
-0.01771637797355652,
0.04001226648688316,
-0.07762761414051056,
-0.06024782732129097,
-0.09209384769201279,
-0.035471633076667786,
0.02069738879799843,
0.016537142917513847,
0.0885712280869484,
0.056583404541015625,
0.09920130670070648,
-0.13727723062038422,
-0.01382916048169136,
0.009947748854756355,
-0.07478483021259308,
-0.03059193678200245,
-0.10491904616355896,
0.09214739501476288,
0.15560004115104675,
0.010332535021007061,
0.023837892338633537,
0.08561647683382034,
0.14442123472690582,
0.0060734995640814304,
0.053527459502220154,
0.23800335824489594,
0.03225022926926613,
0.08214239776134491,
0.11781321465969086,
0.00999550148844719,
-0.07862240076065063,
-0.03648017346858978,
0.0025515039451420307,
-0.06333597749471664,
-0.1574958711862564,
0.002112589543685317,
-0.10965485870838165,
-0.006262233480811119,
0.043449681252241135,
0.06461286544799805,
0.014275943860411644,
0.1647784411907196,
-0.030850157141685486,
0.11993560940027237,
-0.03521151468157768,
0.06352372467517853,
0.122671939432621,
0.042467936873435974,
0.04085637629032135,
-0.1467892825603485,
-0.0473298653960228,
0.08686419576406479,
0.11974062770605087,
0.08338440209627151,
-0.026438962668180466,
0.022083142772316933,
0.05209648236632347,
0.16399237513542175,
-0.0011980179697275162,
0.0868607833981514,
-0.05543667823076248,
-0.002282968955114484,
-0.06083407625555992,
-0.06303167343139648,
-0.10808371007442474,
0.05626364424824715,
-0.15036478638648987,
-0.07001349329948425,
0.013305739499628544,
0.10016109049320221,
0.0425950363278389,
0.24288247525691986,
0.0645730197429657,
-0.23809149861335754,
-0.00011317669122945517,
0.06872250139713287,
0.018218964338302612,
-0.05196646973490715,
0.09286316484212875,
-0.04948938265442848,
-0.012852621264755726,
0.08144202083349228,
-0.02920112945139408,
0.11654900759458542,
0.007915891706943512,
0.049569059163331985,
0.014997187070548534,
0.11473622918128967,
0.08293493092060089,
0.1284930408000946,
-0.15621189773082733,
0.06092781573534012,
0.036540187895298004,
0.028337659314274788,
-0.06733763962984085,
0.027049805968999863,
0.13111285865306854,
0.10026544332504272,
0.08000382035970688,
-0.0006965783541090786,
0.037826381623744965,
-0.024274317547678947,
-0.08205799758434296,
0.1112852692604065,
0.007894615642726421,
-0.023282432928681374,
0.09182827919721603,
-0.08227096498012543,
-0.02319633960723877,
-0.015431230887770653,
0.06641148775815964,
-0.017645342275500298,
-0.14681531488895416,
0.02020992524921894,
0.13518968224525452,
-0.03777769207954407,
-0.03390024974942207,
0.05419265106320381,
-0.08905379474163055,
0.11915221810340881,
-0.010979312472045422,
-0.11041533946990967,
-0.09204410016536713,
-0.05179908871650696,
0.1136874258518219,
-0.079351507127285,
0.035177163779735565,
-0.10998660326004028,
-0.00018487742636352777,
0.04670127481222153,
-0.2231626957654953,
0.026630057021975517,
-0.07933030277490616,
0.00757617736235261,
0.02653268538415432,
0.05973788723349571,
-0.14029856026172638,
-0.04490583389997482,
0.037501562386751175,
-0.05929150432348251,
-0.08412661403417587,
-0.1309996396303177,
-0.09419547021389008,
0.10773300379514694,
-0.06216832995414734,
-0.0052117551676929,
-0.11606691032648087,
0.05391139164566994,
0.006156128365546465,
0.015799343585968018,
0.04602253437042236,
0.14625373482704163,
-0.03489034250378609,
0.052258070558309555,
0.18283505737781525,
-0.059500984847545624,
-0.28981614112854004,
-0.16158638894557953,
-0.05989285185933113,
-0.023701131343841553,
-0.06745323538780212,
-0.1447601169347763,
0.17520838975906372,
0.044719357043504715,
-0.04641622304916382,
0.09033889323472977,
-0.2444816529750824,
-0.06968002766370773,
0.1277020424604416,
0.027377473190426826,
0.30467596650123596,
-0.1619749814271927,
-0.04966195672750473,
-0.1573851853609085,
-0.2756357491016388,
0.042197998613119125,
-0.2787357270717621,
0.13687764108181,
-0.05543871596455574,
0.05009063705801964,
0.006430146284401417,
-0.01628449745476246,
0.11951332539319992,
0.0020939211826771498,
0.06740252673625946,
-0.0847640261054039,
0.091637022793293,
0.07834358513355255,
-0.09517434984445572,
0.19558951258659363,
-0.24751725792884827,
0.08867138624191284,
-0.13006611168384552,
-0.005072169471532106,
-0.013567343354225159,
-0.011039196513593197,
0.00828324444591999,
-0.012096391059458256,
-0.0877298042178154,
-0.029646215960383415,
0.09812918305397034,
0.023757776245474815,
0.13159175217151642,
0.03681112080812454,
-0.07920634746551514,
0.19945554435253143,
0.009779805317521095,
-0.12700097262859344,
0.007980297319591045,
-0.08679540455341339,
-0.013848833739757538,
0.07535924017429352,
-0.30223461985588074,
0.07907842844724655,
0.05240162834525108,
-0.03359934315085411,
0.036735184490680695,
0.026537440717220306,
0.016516629606485367,
-0.018212540075182915,
0.06950564682483673,
-0.08441147953271866,
-0.052798591554164886,
-0.058677081018686295,
0.04488092288374901,
-0.08056695014238358,
0.11995568126440048,
0.16623404622077942,
-0.03543856367468834,
0.011692353524267673,
0.0023955008946359158,
0.020259112119674683,
-0.06187966465950012,
0.05107474699616432,
0.10282260179519653,
0.0008221585303544998,
-0.11719672381877899,
0.1269102543592453,
-0.013713564723730087,
0.10984408110380173,
0.030957208946347237,
0.045836951583623886,
-0.12981313467025757,
-0.08976859599351883,
0.01997460052371025,
0.1388530731201172,
-0.2304467409849167,
-0.07145612686872482,
-0.13937976956367493,
-0.06109088659286499,
0.015412637032568455,
0.06172800436615944,
0.07812327891588211,
0.008032196201384068,
-0.017627939581871033,
-0.05492205172777176,
-0.029551329091191292,
0.019856201484799385,
0.013477134518325329,
0.025299202650785446,
-0.1891443431377411,
-0.033567167818546295,
-0.00932562630623579,
0.09081457555294037,
-0.04090819135308266,
0.015150717459619045,
-0.07761450111865997,
0.0018593556014820933,
-0.3242458403110504,
0.05419382452964783,
-0.0420537143945694,
0.03535418584942818,
0.013862417079508305,
0.012242994271218777,
-0.07659443467855453,
0.07545413076877594,
-0.09253913909196854,
-0.036551568657159805,
-0.06641755998134613,
0.01322279404848814,
-0.05734876170754433,
-0.0466705821454525,
0.0015901714796200395,
-0.07543057948350906,
0.022148573771119118,
-0.001149031799286604,
-0.06475836038589478,
0.05932236835360527,
-0.14203552901744843,
-0.06689931452274323,
0.014193807728588581,
0.05309795215725899,
-0.029152629896998405,
0.07585975527763367,
0.02226390689611435,
0.039080794900655746,
0.03988027572631836,
-0.05904955044388771,
0.020597290247678757,
-0.061307407915592194,
-0.06091533601284027,
-0.11289340257644653,
0.027231408283114433,
-0.048011522740125656,
-0.012109065428376198,
0.11620205640792847,
0.08627556264400482,
0.14967942237854004,
-0.018789131194353104,
-0.025924941524863243,
-0.1197739690542221,
-0.01442039106041193,
0.020681971684098244,
-0.06872308254241943,
-0.09494682401418686,
-0.14524102210998535,
-0.0038955165073275566,
-0.06366375833749771,
0.11530609428882599,
0.0164109505712986,
-0.0004212424682918936,
-0.037747256457805634,
0.05490803346037865,
0.12759940326213837,
-0.039533667266368866,
0.24569085240364075,
0.06666698306798935,
0.07140034437179565,
-0.0470038540661335,
-0.014385645277798176,
0.09570696204900742,
0.05557548999786377,
-0.011575493961572647,
0.08074679225683212,
-0.03358782082796097,
0.192372128367424,
0.026059206575155258,
0.05129874125123024,
0.05974366143345833,
0.09000155329704285,
-0.037611089646816254,
0.07247914373874664,
-0.031714849174022675,
0.14375244081020355,
0.1721789687871933,
-0.0564790703356266,
-0.0025418084114789963,
-0.027187615633010864,
-0.026242420077323914,
-0.13017216324806213,
-0.14465709030628204,
-0.09927207976579666,
-0.19068413972854614,
0.015873467549681664,
-0.04299059510231018,
0.03544674068689346,
0.14730478823184967,
-0.003948842640966177,
0.03227697312831879,
0.06935320049524307,
-0.022711530327796936,
-0.08548207581043243,
0.07004672288894653,
-0.004918418824672699,
-0.058498065918684006,
0.1152176782488823,
-0.017261626198887825,
0.053601957857608795,
-0.03501909598708153,
0.004365100525319576,
0.008353333920240402,
0.10800917446613312,
0.047631874680519104,
-0.07918582856655121,
-0.033366378396749496,
-0.03718111664056778,
0.0332232229411602,
0.05527687817811966,
0.051648642867803574,
0.039971258491277695,
-0.04882011190056801,
0.029412241652607918,
0.11202765256166458,
-0.08890584111213684,
-0.1195613369345665,
-0.11958925426006317,
0.0310619305819273,
-0.034013379365205765,
0.01839878410100937,
-0.025695115327835083,
-0.05800647661089897,
-0.004124476108700037,
0.3768705427646637,
0.06189119443297386,
-0.16760604083538055,
-0.025113515555858612,
-0.03452795371413231,
0.012185923755168915,
-0.023369988426566124,
0.15860356390476227,
0.13251569867134094,
0.0922049954533577,
-0.04740659520030022,
-0.0952882245182991,
-0.009829278104007244,
-0.04972435534000397,
-0.1750558614730835,
0.06737612932920456,
-0.10964673012495041,
-0.05132352560758591,
0.00917028822004795,
-0.013090225867927074,
-0.08771754801273346,
-0.07715392857789993,
0.0253814198076725,
0.0002120661665685475,
-0.05300833284854889,
-0.10706053674221039,
-0.0010359864681959152,
0.05481787398457527,
-0.0043706768192350864,
-0.10127852112054825,
0.03722387179732323,
0.1703570932149887,
-0.03362897410988808,
-0.15921944379806519,
-0.0509699247777462,
0.050321727991104126,
-0.02927880920469761,
0.0960024744272232,
0.040347009897232056,
0.018939577043056488,
0.08381931483745575,
-0.04328608512878418,
-0.10222736746072769,
0.10618463903665543,
0.003740273881703615,
-0.04423445463180542,
0.030227800831198692,
-0.04890430346131325,
-0.05480404943227768,
-0.04832260310649872,
0.04182331636548042,
0.10709237307310104,
-0.04308905825018883,
0.12776851654052734,
-0.03223026171326637,
-0.08125093579292297,
-0.023439040407538414,
-0.11343672126531601,
0.09773524105548859,
0.09548269957304001,
-0.0651404857635498,
-0.0396711565554142,
-0.08304159343242645,
0.09273722022771835,
0.02053319849073887,
-0.16803231835365295,
0.004594400059431791,
0.016486864537000656,
-0.041280072182416916,
0.005130276549607515,
0.031221402809023857,
-0.12865617871284485,
-0.010428558103740215,
-0.04946392774581909,
-0.008942368440330029,
-0.06876754760742188,
0.11777409166097641,
0.17174212634563446,
0.04561625421047211,
-0.008935659192502499,
-0.12006811797618866,
-0.0532652921974659,
0.026753166690468788,
-0.04730325937271118,
-0.11738646030426025
] |
null | null | null |
Submission for Hacklytics 2024 Datascience Hackthon
# Training
Random forest model trained on TEDS(TREATMENT EPISODE DATA SET
ADMISSIONS) dataset. Random search was employed to hyperparamter fine tune the model.
# Results
An accuracy of 74% was achieved with lots of potential to increase accuracy by fruther cleaning the input data set and feature engineering.
### Most important features
| {"license": "mit"} | null | arian81/TEDS_Readmission_random_forest | [
"joblib",
"license:mit",
"region:us"
] | 2024-02-11T04:31:40+00:00 | [] | [] | TAGS
#joblib #license-mit #region-us
|
Submission for Hacklytics 2024 Datascience Hackthon
# Training
Random forest model trained on TEDS(TREATMENT EPISODE DATA SET
ADMISSIONS) dataset. Random search was employed to hyperparamter fine tune the model.
# Results
An accuracy of 74% was achieved with lots of potential to increase accuracy by fruther cleaning the input data set and feature engineering.
### Most important features
!Most important features
| [
"# Training\n\nRandom forest model trained on TEDS(TREATMENT EPISODE DATA SET\nADMISSIONS) dataset. Random search was employed to hyperparamter fine tune the model.",
"# Results\n\nAn accuracy of 74% was achieved with lots of potential to increase accuracy by fruther cleaning the input data set and feature engineering.",
"### Most important features\n\n!Most important features"
] | [
"TAGS\n#joblib #license-mit #region-us \n",
"# Training\n\nRandom forest model trained on TEDS(TREATMENT EPISODE DATA SET\nADMISSIONS) dataset. Random search was employed to hyperparamter fine tune the model.",
"# Results\n\nAn accuracy of 74% was achieved with lots of potential to increase accuracy by fruther cleaning the input data set and feature engineering.",
"### Most important features\n\n!Most important features"
] | [
14,
45,
33,
10
] | [
"passage: TAGS\n#joblib #license-mit #region-us \n# Training\n\nRandom forest model trained on TEDS(TREATMENT EPISODE DATA SET\nADMISSIONS) dataset. Random search was employed to hyperparamter fine tune the model.# Results\n\nAn accuracy of 74% was achieved with lots of potential to increase accuracy by fruther cleaning the input data set and feature engineering.### Most important features\n\n!Most important features"
] | [
-0.046542126685380936,
0.0702434703707695,
-0.0009563295170664787,
-0.003138973843306303,
0.08404290676116943,
-0.07355297356843948,
-0.08074291050434113,
-0.007400815840810537,
-0.06278898566961288,
-0.02292068488895893,
0.18966278433799744,
0.19826829433441162,
-0.03572431579232216,
0.16784460842609406,
-0.1317417472600937,
-0.14022479951381683,
0.07350656390190125,
-0.06082259491086006,
0.04051196202635765,
0.03630540892481804,
0.012942548841238022,
-0.09298603236675262,
0.05848473682999611,
-0.06320326030254364,
-0.22692720592021942,
0.04090398922562599,
-0.00041271484224125743,
-0.0117352195084095,
0.0983901247382164,
0.038774631917476654,
0.05873667448759079,
-0.020914865657687187,
0.0811353325843811,
-0.01828453689813614,
0.007380620576441288,
-0.026707636192440987,
0.014649148099124432,
0.084336057305336,
-0.038843609392642975,
0.08436983078718185,
0.22932079434394836,
0.1647924929857254,
0.08942126482725143,
0.01882110722362995,
-0.12917836010456085,
-0.0023474295157939196,
-0.011311021633446217,
-0.10053244233131409,
0.024649174883961678,
0.04614276438951492,
-0.013864611275494099,
0.22008158266544342,
-0.14064128696918488,
0.07704424858093262,
-0.03439465910196304,
-0.07222159206867218,
-0.012857179157435894,
0.1294853687286377,
0.028842836618423462,
0.0008696936420165002,
-0.05985334888100624,
-0.01993536949157715,
0.1336567997932434,
-0.005761185195297003,
0.04200289770960808,
0.03006163239479065,
-0.1883256882429123,
-0.01922312192618847,
-0.1279476433992386,
-0.015758797526359558,
0.165841743350029,
0.09829951822757721,
-0.08899380266666412,
-0.08471298962831497,
-0.05005861073732376,
0.12479662895202637,
0.00660239951685071,
0.009281743317842484,
-0.03441306948661804,
-0.014305361546576023,
-0.013464237563312054,
0.09079410880804062,
-0.04582037776708603,
-0.078483946621418,
-0.06176293268799782,
0.09759844839572906,
0.01691255159676075,
0.11849338561296463,
0.010635334067046642,
0.033982012420892715,
-0.0761430487036705,
-0.03971785306930542,
-0.004736731294542551,
-0.040034979581832886,
-0.12899500131607056,
-0.11442014575004578,
-0.027048753574490547,
0.12337974458932877,
0.1003841832280159,
0.15980331599712372,
-0.042153146117925644,
-0.07332069426774979,
-0.05204799771308899,
0.04277270287275314,
0.07306712120771408,
0.04200929030776024,
-0.06683818995952606,
0.09964806586503983,
0.031648606061935425,
-0.08863329887390137,
-0.05051771178841591,
0.02273634821176529,
-0.019108407199382782,
0.018878011032938957,
0.0007999604567885399,
0.10009285062551498,
-0.0973605215549469,
-0.02384636551141739,
0.00826624408364296,
-0.0100789749994874,
0.0978531464934349,
-0.023955145850777626,
-0.08804505318403244,
-0.04216938838362694,
-0.09395333379507065,
-0.08638310432434082,
-0.02950376272201538,
0.04162810742855072,
0.0412311889231205,
0.05681728199124336,
-0.06168872117996216,
0.028624925762414932,
-0.018458301201462746,
-0.17941278219223022,
-0.10839830338954926,
0.007125748321413994,
0.09622959047555923,
-0.07331538945436478,
-0.16826660931110382,
-0.032160546630620956,
0.020347928628325462,
-0.007404358591884375,
-0.04806394875049591,
-0.033411797136068344,
-0.12389124929904938,
-0.06699293851852417,
-0.004257779102772474,
0.15649740397930145,
-0.06228078156709671,
0.017027804628014565,
-0.09034857898950577,
0.051060330122709274,
-0.1415221393108368,
-0.019179539754986763,
-0.12897904217243195,
-0.04082721099257469,
-0.13138709962368011,
0.07538282871246338,
-0.045098815113306046,
0.2846040725708008,
-0.020404651761054993,
-0.07496853172779083,
0.06316602975130081,
0.015443366952240467,
-0.016940928995609283,
0.0895901694893837,
-0.11725422739982605,
0.060721538960933685,
0.10060178488492966,
-0.130919948220253,
-0.07094470411539078,
0.07826246321201324,
-0.15131573379039764,
0.19203540682792664,
0.0974954143166542,
0.21211689710617065,
-0.030728643760085106,
-0.035073332488536835,
0.16389501094818115,
-0.025550615042448044,
-0.14462591707706451,
-0.047908227890729904,
-0.00903474073857069,
0.014016355387866497,
-0.23488885164260864,
0.02302524633705616,
0.08638496696949005,
0.03721919655799866,
-0.07748067378997803,
-0.07905200123786926,
-0.061352189630270004,
-0.08877816796302795,
-0.12801267206668854,
0.06308043748140335,
0.09654415398836136,
-0.11948364973068237,
0.12126421183347702,
0.06480935961008072,
0.14006464183330536,
0.04159773886203766,
-0.11573280394077301,
-0.014322124421596527,
-0.12967197597026825,
-0.02725457400083542,
-0.030755652114748955,
-0.11495424807071686,
0.0750214233994484,
0.035120800137519836,
0.12081746011972427,
0.05917294695973396,
0.053265053778886795,
0.012110459618270397,
0.11661986261606216,
0.02911960892379284,
-0.029580818489193916,
0.05412185937166214,
0.02632058411836624,
0.03154495730996132,
-0.11400628089904785,
0.09148888289928436,
-0.04567079618573189,
-0.10083907842636108,
-0.29321977496147156,
-0.032112590968608856,
-0.2015089988708496,
0.019799845293164253,
0.02114180102944374,
-0.0413430817425251,
-0.004013971891254187,
0.00866804737597704,
-0.050053250044584274,
-0.07990679144859314,
0.04857966676354408,
0.004223786760121584,
-0.031656909734010696,
0.05693906173110008,
0.009295331314206123,
0.1742348074913025,
0.05722854658961296,
-0.013080814853310585,
-0.17960506677627563,
0.13934028148651123,
-0.0872989371418953,
0.006882814224809408,
-0.13695450127124786,
-0.029505595564842224,
0.05803762003779411,
-0.10253338515758514,
0.07679159939289093,
-0.08323294669389725,
0.024633072316646576,
-0.022940820083022118,
0.04757010191679001,
0.13505780696868896,
0.15864968299865723,
0.14147640764713287,
-0.3515852093696594,
0.03682171553373337,
-0.15220308303833008,
0.08054086565971375,
0.10583578795194626,
-0.11479319632053375,
-0.04828443005681038,
-0.0239347442984581,
0.13522863388061523,
-0.003750745439901948,
0.12017562240362167,
0.00023166679602582008,
0.051427558064460754,
0.009810649789869785,
0.056752126663923264,
0.01069361437112093,
-0.09920182824134827,
-0.051394082605838776,
0.02073097601532936,
0.014533651061356068,
-0.14826609194278717,
0.045621830970048904,
0.017828015610575676,
0.11762037128210068,
-0.10882490873336792,
-0.24292582273483276,
-0.03685412555932999,
0.005172425415366888,
-0.03703455999493599,
0.15103814005851746,
0.07183805108070374,
0.05394844338297844,
-0.09905848652124405,
0.05910996347665787,
0.034293100237846375,
0.011934244073927402,
0.059008125215768814,
-0.00023321622575167567,
-0.0878395065665245,
-0.10312594473361969,
0.005949867889285088,
-0.10296900570392609,
-0.026329027488827705,
-0.10269617289304733,
0.022093458101153374,
0.026718460023403168,
-0.08962807059288025,
-0.008846297860145569,
-0.08010563254356384,
0.017815427854657173,
0.06226859614253044,
-0.08757853507995605,
0.0696510300040245,
0.024835841730237007,
-0.0521383211016655,
-0.0373038724064827,
-0.001530332025140524,
0.3264894485473633,
0.011560192331671715,
-0.06421753019094467,
0.011072144843637943,
0.0035823574289679527,
-0.04863084480166435,
0.16044829785823822,
0.029583878815174103,
-0.20809653401374817,
0.08372586220502853,
-0.03977435082197189,
-0.0798378735780716,
-0.20234562456607819,
-0.09267383813858032,
0.03444208204746246,
0.06742202490568161,
0.15805624425411224,
0.024012859910726547,
-0.0038115165662020445,
0.04240819066762924,
0.019857365638017654,
0.00389349227771163,
-0.010698680765926838,
0.015573293901979923,
-0.1257556676864624,
0.0006573406280949712,
0.1266518086194992,
-0.06898579001426697,
-0.06563714146614075,
0.07564697414636612,
-0.27308177947998047,
0.2568036615848541,
0.0634208619594574,
-0.00243501178920269,
0.07039213180541992,
0.06484319269657135,
-0.010836662724614143,
0.15804682672023773,
0.010362314060330391,
-0.0621068961918354,
-0.024802271276712418,
0.017732342705130577,
0.10138478875160217,
0.04326329752802849,
0.013288947753608227,
0.08304505795240402,
-0.037950530648231506,
-0.1498885452747345,
-0.011974454857409,
0.12629911303520203,
0.06306060403585434,
-0.24486428499221802,
-0.04390363767743111,
-0.006237060762941837,
-0.10337415337562561,
-0.06561300903558731,
0.07015430182218552,
0.15265430510044098,
-0.06700438261032104,
-0.06297775357961655,
0.056777480989694595,
0.16747184097766876,
0.08448673784732819,
-0.011734943836927414,
-0.28147637844085693,
0.02440813183784485,
-0.0369378887116909,
0.08573957532644272,
-0.09656307846307755,
0.15274809300899506,
-0.013951142318546772,
0.10887008905410767,
0.014992534182965755,
-0.07035573571920395,
0.10447322577238083,
0.0263241995126009,
0.10987678915262222,
0.03542928397655487,
-0.2126598358154297,
-0.14022941887378693,
-0.1075611263513565,
-0.0181230790913105,
-0.06488003581762314,
-0.023999400436878204,
-0.019989579916000366,
0.0231480672955513,
0.047391414642333984,
0.056013867259025574,
0.013137837871909142,
-0.14488300681114197,
0.05829111114144325,
-0.1610572338104248,
0.06074650213122368,
0.0609327107667923,
0.012690553441643715,
-0.04434247314929962,
-0.001950419507920742,
0.14601318538188934,
0.15898971259593964,
0.01758325845003128,
-0.03816822171211243,
0.06329718232154846,
0.09077838063240051,
0.07014598697423935,
0.006572600919753313,
0.00008827362762531266,
-0.009508035145699978,
0.03391646593809128,
-0.08480896800756454,
0.11650227755308151,
-0.058341361582279205,
0.007252216804772615,
-0.020120248198509216,
0.055992625653743744,
0.12217842042446136,
0.04610511660575867,
0.02155766636133194,
0.05139954388141632,
-0.05836276710033417,
-0.18969076871871948,
-0.03755248710513115,
-0.0613776259124279,
0.04852394759654999,
0.23269368708133698,
-0.09468059241771698,
-0.049907129257917404,
-0.051830142736434937,
-0.09316527843475342,
0.14701710641384125,
0.18674352765083313,
-0.10798394680023193,
0.0098831532523036,
-0.007036380935460329,
-0.048782020807266235,
-0.11619633436203003,
0.07398440688848495,
-0.012749952264130116,
0.07614319026470184,
0.02971743606030941,
-0.0476725697517395,
0.1618792563676834,
0.06171875447034836,
0.00004895677193417214,
0.13085515797138214,
-0.20542022585868835,
-0.14272725582122803,
0.19413140416145325,
0.1237657219171524,
0.38644370436668396,
0.002540036803111434,
-0.01568804495036602,
-0.06572888046503067,
0.07698028534650803,
0.20951028168201447,
-0.07935789227485657,
0.0496264286339283,
-0.018188226968050003,
0.05430077761411667,
0.020147614181041718,
-0.02272244356572628,
0.14672274887561798,
0.03288869559764862,
0.2056383639574051,
-0.007400468457490206,
0.11032082140445709,
-0.078964963555336,
-0.02293522283434868,
0.15367044508457184,
0.09311384707689285,
0.14484328031539917,
-0.018457137048244476,
-0.026706963777542114,
-0.03783643990755081,
0.06926357001066208,
0.03248554468154907,
-0.042891550809144974,
-0.19460974633693695,
0.0020397938787937164,
0.0467202328145504,
-0.029845664277672768,
0.011030522175133228,
0.001533334027044475,
0.1935422271490097,
-0.05775771290063858,
-0.08416067063808441,
-0.06967802345752716,
0.05553881451487541,
0.014239129610359669,
-0.006961353588849306,
0.108394093811512,
-0.13598798215389252,
0.022397270426154137,
0.19881050288677216,
0.0797034204006195,
0.13330654799938202,
0.03152783587574959,
-0.03372387960553169,
-0.03946278989315033,
-0.03838559612631798,
-0.13085034489631653,
-0.10089270025491714,
0.03283736854791641,
-0.03608636558055878,
0.12424129992723465,
-0.0356491357088089,
-0.01172728557139635,
-0.10548356920480728,
0.03401299566030502,
-0.015115614980459213,
-0.07596885412931442,
0.011959027498960495,
0.1899740993976593,
-0.007649283856153488,
0.04740508273243904,
-0.15774765610694885,
0.022732648998498917,
-0.04069928824901581,
0.10536103695631027,
-0.03340044990181923,
-0.09077262878417969,
-0.08211825042963028,
-0.0025688139721751213,
0.0789015144109726,
0.18809917569160461,
-0.008046877570450306,
-0.08314638584852219,
-0.08506949990987778,
-0.08674252033233643,
0.10133018344640732,
0.2652466297149658,
0.1457320600748062,
0.03475327417254448,
0.04971016198396683,
-0.09414457529783249,
-0.04283669963479042,
-0.039257124066352844,
-0.010041910223662853,
0.011559667065739632,
-0.06833401322364807,
0.05273641273379326,
0.0685919001698494,
-0.06849873811006546,
-0.051036570221185684,
-0.05893685296177864,
-0.10465613007545471,
0.013406503014266491,
0.0034138758201152086,
0.09528623521327972,
-0.04736842215061188,
0.05148927867412567,
0.03403428941965103,
-0.00844850018620491,
-0.022881848737597466,
0.04105059802532196,
-0.09117546677589417,
0.01477479562163353,
0.060840681195259094,
0.06503909826278687,
0.009513956494629383,
-0.04117617756128311,
0.017411785200238228,
-0.024363795295357704,
-0.040072813630104065,
0.04548614099621773,
-0.015433377586305141,
0.06713736057281494,
-0.07180105149745941,
-0.08416131883859634,
0.14944452047348022,
0.03673906624317169,
0.0530695766210556,
-0.15078169107437134,
-0.0119949234649539,
0.08599326759576797,
0.034187670797109604,
0.052778761833906174,
-0.051749806851148605,
-0.09287412464618683,
-0.18806898593902588,
0.025820180773735046,
-0.08100812882184982,
-0.016021598130464554,
-0.11411049216985703,
0.035091739147901535,
0.11673986911773682,
0.21975581347942352,
-0.034357573837041855,
-0.010049374774098396,
-0.10398704558610916,
-0.0182100348174572,
-0.07183349877595901,
-0.12990278005599976,
0.014063783921301365,
0.06859060376882553,
0.006871997844427824,
-0.03914752975106239,
0.2724217474460602,
-0.11520294100046158,
0.04159476235508919,
0.00626114197075367,
0.06331130117177963,
0.0010199041571468115,
0.013074260205030441,
0.23589906096458435,
0.03429342433810234,
-0.04271869361400604,
-0.029400058090686798,
0.06706371903419495,
0.10187698900699615,
0.11479850858449936,
0.020555581897497177,
0.10220273584127426,
-0.09909091144800186,
-0.05079309642314911,
-0.02148432470858097,
-0.031007694080471992,
0.11804361641407013,
-0.02311495691537857,
0.05815974995493889,
0.027274783700704575,
0.11594406515359879,
0.048243336379528046,
0.15908564627170563,
-0.06612109392881393,
0.047531940042972565,
0.003426837967708707,
-0.06073538586497307,
-0.11888933926820755,
0.0899411141872406,
-0.07113764435052872,
0.006710856221616268,
0.060685887932777405,
-0.041182104498147964,
0.009617121890187263,
0.17481911182403564,
0.06472565978765488,
-0.03425980359315872,
-0.018411271274089813,
0.00942389015108347,
-0.05323399230837822,
0.029792435467243195,
-0.09593728184700012,
-0.14768266677856445,
-0.04270775243639946,
-0.0285854022949934,
0.03719307482242584,
-0.06436707079410553,
-0.009550034068524837,
-0.03677278384566307,
-0.05741587281227112,
0.0022840951569378376,
-0.08080722391605377,
0.011625119484961033,
-0.014189834706485271,
0.03682086989283562,
-0.041255269199609756,
-0.004233173094689846,
0.14281858503818512,
-0.052375540137290955,
0.0404660589993,
0.22050605714321136,
0.01558148954063654,
-0.05537642538547516,
-0.16484972834587097,
0.28240808844566345,
0.04328259825706482,
0.03003474324941635,
0.007918968796730042,
0.03722545504570007,
-0.0081753209233284,
0.05982892960309982,
0.024031849578022957,
-0.026422439143061638,
-0.021287070587277412,
-0.10232008993625641,
-0.05932730808854103,
-0.023628544062376022,
0.11266487836837769,
-0.02037561871111393,
0.02847251668572426,
-0.01474377978593111,
-0.043626949191093445,
-0.14852578938007355,
-0.029454227536916733,
0.009508727118372917,
-0.05201566964387894,
0.09389971941709518,
-0.02550020068883896,
-0.12335442006587982,
0.07071269303560257,
-0.1313164234161377,
-0.10271566361188889,
0.04065696895122528,
0.041798241436481476,
-0.11720594763755798,
-0.0613257922232151,
-0.13356980681419373,
-0.0139082670211792,
0.050632644444704056,
-0.09102370589971542,
0.08967724442481995,
-0.22566524147987366,
-0.05136679857969284,
-0.12272681295871735,
-0.1802176833152771,
0.01999742165207863,
0.06316263228654861,
0.0882701426744461,
0.018468305468559265,
0.10646597295999527,
0.007399541791528463,
-0.012651569209992886,
-0.0832451656460762,
0.17985160648822784,
-0.08178240805864334,
0.028992654755711555,
0.01501898281276226,
0.11225104331970215,
-0.009847059845924377,
0.09877102822065353,
0.007901269942522049,
-0.21105130016803741,
-0.032460108399391174,
-0.11166255921125412,
-0.10487621277570724,
-0.09021277725696564,
0.010864733718335629,
-0.010110151953995228,
0.04721543565392494,
0.0808032751083374,
-0.01621244288980961,
0.06641844660043716,
-0.07079420983791351,
0.08859679847955704,
-0.0004063387750647962,
-0.15216784179210663,
-0.08202189207077026,
-0.2175520360469818,
-0.002144325291737914,
0.01620703563094139,
-0.019266197457909584,
-0.21775031089782715,
-0.036455027759075165,
-0.09146864712238312,
-0.04653015732765198,
0.03021019510924816,
0.06078400835394859,
0.024296456947922707,
0.042958322912454605,
0.0006012925296090543,
-0.15448778867721558,
-0.021425165235996246,
0.08167111873626709,
0.046420659869909286,
-0.1264447718858719
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# emotional_classification
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1401
- Accuracy: 0.5938
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 40 | 1.7535 | 0.3375 |
| No log | 2.0 | 80 | 1.5659 | 0.3875 |
| No log | 3.0 | 120 | 1.4480 | 0.4562 |
| No log | 4.0 | 160 | 1.3839 | 0.4938 |
| No log | 5.0 | 200 | 1.3246 | 0.5125 |
| No log | 6.0 | 240 | 1.3297 | 0.4875 |
| No log | 7.0 | 280 | 1.2665 | 0.5312 |
| No log | 8.0 | 320 | 1.2979 | 0.5625 |
| No log | 9.0 | 360 | 1.1959 | 0.5687 |
| No log | 10.0 | 400 | 1.2104 | 0.55 |
| No log | 11.0 | 440 | 1.2401 | 0.5687 |
| No log | 12.0 | 480 | 1.1960 | 0.5437 |
| 1.0885 | 13.0 | 520 | 1.1571 | 0.6188 |
| 1.0885 | 14.0 | 560 | 1.2241 | 0.575 |
| 1.0885 | 15.0 | 600 | 1.2355 | 0.5625 |
| 1.0885 | 16.0 | 640 | 1.1830 | 0.6 |
| 1.0885 | 17.0 | 680 | 1.2906 | 0.5625 |
| 1.0885 | 18.0 | 720 | 1.2705 | 0.525 |
| 1.0885 | 19.0 | 760 | 1.2643 | 0.5563 |
| 1.0885 | 20.0 | 800 | 1.1538 | 0.5813 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "emotional_classification", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.59375, "name": "Accuracy"}]}]}]} | image-classification | Ghiffari4869/emotional_classification | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T04:32:49+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| emotional\_classification
=========================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1401
* Accuracy: 0.5938
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
86,
98,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.11862684786319733,
0.13607098162174225,
-0.0025763940066099167,
0.11910273134708405,
0.1404537558555603,
0.004346479661762714,
0.14077715575695038,
0.1390070766210556,
-0.07172218710184097,
0.08159811049699783,
0.1491062492132187,
0.1303545981645584,
0.030898649245500565,
0.18905162811279297,
-0.049535807222127914,
-0.22352102398872375,
0.02580658718943596,
0.0477079339325428,
-0.04870045557618141,
0.12126699090003967,
0.08815955370664597,
-0.1382121741771698,
0.11751259118318558,
0.025848114863038063,
-0.2047291398048401,
-0.007606162689626217,
0.029538599774241447,
-0.05819394066929817,
0.1168045625090599,
0.0373651385307312,
0.09160982817411423,
0.028289178386330605,
0.05270405858755112,
-0.1481442153453827,
0.010206367820501328,
0.07640063017606735,
-0.009214755147695541,
0.09723441302776337,
0.05622915178537369,
0.011492506600916386,
0.016050094738602638,
-0.09463026374578476,
0.04004139453172684,
0.025265377014875412,
-0.11202917993068695,
-0.23511426150798798,
-0.08598961681127548,
0.059083208441734314,
0.0774804875254631,
0.07061222195625305,
-0.002693967893719673,
0.1436288058757782,
-0.005592017434537411,
0.09797509014606476,
0.22986344993114471,
-0.27418267726898193,
-0.07741672545671463,
0.03757063299417496,
0.017696822062134743,
0.07755748927593231,
-0.1007639467716217,
0.012463548220694065,
0.059283606708049774,
0.013740353286266327,
0.15326596796512604,
-0.00546793220564723,
-0.013231445103883743,
-0.026213020086288452,
-0.12508971989154816,
-0.06421228498220444,
0.19508886337280273,
0.0898618996143341,
-0.0470237098634243,
-0.08200053870677948,
-0.08072874695062637,
-0.13877563178539276,
-0.046653974801301956,
-0.011338525451719761,
0.057744529098272324,
-0.03410860896110535,
-0.06401600688695908,
-0.03429725766181946,
-0.09819400310516357,
-0.06963552534580231,
-0.015037794597446918,
0.09685873240232468,
0.053985342383384705,
0.01292209792882204,
-0.021191341802477837,
0.0808539018034935,
-0.04242787882685661,
-0.14507076144218445,
-0.006704701576381922,
0.01800202764570713,
0.025464244186878204,
-0.03126758337020874,
-0.025375982746481895,
-0.11615971475839615,
0.020918212831020355,
0.10874377191066742,
-0.06972605735063553,
0.05691898241639137,
-0.02163911797106266,
0.05179855599999428,
-0.11123023927211761,
0.19115161895751953,
-0.04929012805223465,
0.0159612987190485,
0.04046659544110298,
0.1017889603972435,
0.05127325654029846,
-0.002425429644063115,
-0.1056673526763916,
0.017791470512747765,
0.12042375653982162,
0.0049453722313046455,
-0.03495030477643013,
0.08120119571685791,
-0.0614188052713871,
-0.029111526906490326,
0.07602670043706894,
-0.08666333556175232,
0.026919234544038773,
-0.006897526793181896,
-0.05354881286621094,
-0.0565594881772995,
0.0469067320227623,
-0.011913116089999676,
-0.013371805660426617,
0.04143775254487991,
-0.10228675603866577,
0.012035829946398735,
-0.06763049215078354,
-0.1080244854092598,
0.01311678346246481,
-0.11561828851699829,
0.015319262631237507,
-0.12210355699062347,
-0.1382761150598526,
-0.013023408129811287,
0.05989771708846092,
-0.029016714543104172,
-0.05163951590657234,
-0.04167177900671959,
-0.08057110011577606,
0.026785289868712425,
0.005231655668467283,
0.04709792509675026,
-0.05685161426663399,
0.0881868526339531,
0.044517483562231064,
0.07619098573923111,
-0.019790910184383392,
0.04638770967721939,
-0.0868847668170929,
0.058167941868305206,
-0.2046217918395996,
0.03671747073531151,
-0.05808434262871742,
0.08664451539516449,
-0.1191207617521286,
-0.08627723902463913,
0.0009071230888366699,
-0.020160868763923645,
0.06494573503732681,
0.1077149286866188,
-0.14049723744392395,
-0.05874790623784065,
0.17436181008815765,
-0.10219626873731613,
-0.15532821416854858,
0.11266045272350311,
-0.03060438670217991,
0.029268037527799606,
0.05617973208427429,
0.19773077964782715,
0.07850029319524765,
-0.10863172262907028,
-0.006727805361151695,
-0.031635742634534836,
0.0340501144528389,
-0.053646519780159,
0.07568536698818207,
-0.0005131050711497664,
-0.01108004990965128,
0.022279467433691025,
-0.09523792564868927,
0.06257777661085129,
-0.07312074303627014,
-0.08432256430387497,
-0.0668586865067482,
-0.08747415244579315,
0.041866235435009,
0.05933330953121185,
0.06495782732963562,
-0.1016748771071434,
-0.09083876758813858,
0.028826074674725533,
0.08167547732591629,
-0.09448417276144028,
0.016852281987667084,
-0.08169770985841751,
0.11140599846839905,
-0.1074780747294426,
0.0014938017120584846,
-0.13464124500751495,
-0.02949785627424717,
0.049237966537475586,
-0.0625208243727684,
-0.008478378877043724,
-0.03656590357422829,
0.07331328839063644,
0.06236502155661583,
-0.06268363445997238,
-0.07329478859901428,
-0.03986898064613342,
-0.0025519083719700575,
-0.09935712814331055,
-0.19413237273693085,
-0.023727186024188995,
-0.026893194764852524,
0.10660623013973236,
-0.2199222296476364,
0.04163808375597,
0.05292150005698204,
0.10208848863840103,
0.05913138389587402,
-0.031235113739967346,
0.0039437394589185715,
0.017344877123832703,
-0.03981004282832146,
-0.09011241048574448,
0.061082541942596436,
0.014722965657711029,
-0.06827579438686371,
0.0051209270022809505,
-0.10053195804357529,
0.17472368478775024,
0.13116171956062317,
-0.033463917672634125,
-0.06332863867282867,
-0.0043567162938416,
-0.04356212913990021,
-0.03498488664627075,
-0.03569559007883072,
0.008986911736428738,
0.08051126450300217,
-0.008868166245520115,
0.16240540146827698,
-0.10505981743335724,
-0.026039814576506615,
0.058241575956344604,
-0.02974027581512928,
-0.03810049220919609,
0.08953040093183517,
0.06744997948408127,
-0.13986307382583618,
0.14738419651985168,
0.1662409007549286,
-0.06822194904088974,
0.12521155178546906,
-0.04773518443107605,
-0.06236952543258667,
-0.024040281772613525,
0.04132981598377228,
0.03265652805566788,
0.1292601376771927,
-0.1198551282286644,
-0.01395948976278305,
0.024260707199573517,
0.0016625267453491688,
-0.008375790901482105,
-0.20100361108779907,
-0.008371683768928051,
0.038532670587301254,
-0.05972742661833763,
0.02609979175031185,
-0.005517373792827129,
-0.021567916497588158,
0.08489884436130524,
0.008348884992301464,
-0.042639680206775665,
0.047265421599149704,
0.011100099422037601,
-0.06991036236286163,
0.19499625265598297,
-0.08492761105298996,
-0.21661029756069183,
-0.13107283413410187,
-0.020954333245754242,
-0.08055935055017471,
0.021638698875904083,
0.05819288641214371,
-0.09382759034633636,
-0.057645127177238464,
-0.10397281497716904,
-0.015600989572703838,
0.028978293761610985,
0.03961782902479172,
0.041902970522642136,
-0.0019354389514774084,
0.1307423710823059,
-0.09929072856903076,
-0.007536566816270351,
-0.010077708400785923,
-0.023466931656003,
0.048148881644010544,
0.01983301155269146,
0.12009347230195999,
0.08664698898792267,
-0.027577845379710197,
0.03478600084781647,
-0.020831966772675514,
0.2411278486251831,
-0.07336857914924622,
-0.0025067345704883337,
0.15122878551483154,
0.019550248980522156,
0.06790269911289215,
0.13012559711933136,
0.03827866166830063,
-0.10251547396183014,
0.007758599240332842,
0.021663567051291466,
-0.02579859271645546,
-0.1871739774942398,
-0.0171548780053854,
-0.03924945369362831,
-0.00444507272914052,
0.152572363615036,
0.05523106828331947,
0.061344489455223083,
0.09337121248245239,
0.00033120723674073815,
0.09185243397951126,
-0.004542561247944832,
0.08808216452598572,
0.11049571633338928,
0.045895807445049286,
0.10933946818113327,
-0.0441078245639801,
-0.028400860726833344,
0.03270525485277176,
0.014624936506152153,
0.2257072478532791,
0.0014615242835134268,
0.1745476871728897,
0.04722040519118309,
0.1896134614944458,
0.017876673489809036,
0.05607917532324791,
-0.020971206948161125,
-0.02658970281481743,
-0.009364157915115356,
-0.05445526912808418,
-0.021531760692596436,
0.03677821531891823,
-0.050751328468322754,
0.0655994564294815,
-0.0925455167889595,
0.04166332259774208,
0.06377926468849182,
0.2635495066642761,
0.0365661159157753,
-0.3789684474468231,
-0.09498053789138794,
-0.0053971679881215096,
-0.014488224871456623,
-0.06512360274791718,
0.0023779887706041336,
0.14586958289146423,
-0.0612533763051033,
0.060258202254772186,
-0.10404929518699646,
0.08211296051740646,
-0.051383692771196365,
0.021347982808947563,
0.07492318749427795,
0.09016896039247513,
0.008379991166293621,
0.056661225855350494,
-0.2485174536705017,
0.2579330503940582,
0.01591283641755581,
0.06340377777814865,
-0.04800954461097717,
0.01297358050942421,
0.03521382436156273,
0.10639113932847977,
0.1099725291132927,
-0.005465359892696142,
-0.01662856712937355,
-0.17460858821868896,
-0.08823971450328827,
0.006351474206894636,
0.07203894853591919,
-0.045675501227378845,
0.08031121641397476,
-0.030152365565299988,
-0.023747151717543602,
0.05103715881705284,
-0.0034925774671137333,
-0.08945973217487335,
-0.09370698034763336,
-0.007539461366832256,
0.04352934658527374,
0.015408708713948727,
-0.09620650857686996,
-0.09712299704551697,
-0.10361526906490326,
0.13423673808574677,
-0.01791711524128914,
-0.0405256412923336,
-0.12018390744924545,
0.0892866775393486,
0.05816558748483658,
-0.09259811788797379,
0.08043588697910309,
-0.028549257665872574,
0.13836847245693207,
0.029281003400683403,
-0.062355563044548035,
0.10987292975187302,
-0.059276655316352844,
-0.17301121354103088,
-0.046683523803949356,
0.10513435304164886,
-0.01869458332657814,
0.024247588589787483,
0.0005111363134346902,
0.028401998803019524,
-0.011718365363776684,
-0.058764077723026276,
0.05756045877933502,
0.014515225775539875,
0.05889863893389702,
-0.014903100207448006,
-0.019676700234413147,
0.007737073581665754,
-0.06332728266716003,
-0.029787488281726837,
0.13461267948150635,
0.2437446564435959,
-0.09745744615793228,
0.004943002015352249,
0.018968096002936363,
-0.051279183477163315,
-0.19513830542564392,
0.048698753118515015,
0.06568527966737747,
0.0020221148151904345,
0.0303266029804945,
-0.15475165843963623,
0.07322143018245697,
0.08173877745866776,
-0.030024560168385506,
0.09476637840270996,
-0.265503466129303,
-0.13263669610023499,
0.08120943605899811,
0.1838640421628952,
0.06726694107055664,
-0.14426320791244507,
-0.05513838306069374,
-0.012923520989716053,
-0.09017108380794525,
0.09474195539951324,
-0.06171131134033203,
0.10445062071084976,
-0.02821234054863453,
0.003340694820508361,
0.006336088292300701,
-0.0574214793741703,
0.1290079802274704,
-0.033671990036964417,
0.10798531025648117,
-0.05707699805498123,
-0.009296839125454426,
0.07792694121599197,
-0.07718640565872192,
0.06401468813419342,
-0.09070459008216858,
0.06322236359119415,
-0.061469778418540955,
-0.01584113948047161,
-0.0700555294752121,
0.03382529690861702,
-0.018966028466820717,
-0.025605415925383568,
-0.05134887993335724,
0.02348378114402294,
0.05129716917872429,
-0.0009205437381751835,
0.20003315806388855,
0.05019812658429146,
0.08837173134088516,
0.13760314881801605,
0.04343097656965256,
-0.07744259387254715,
-0.09973973035812378,
-0.027537761256098747,
-0.026997331529855728,
0.0875159427523613,
-0.18562975525856018,
0.04973244294524193,
0.09580063819885254,
0.011054624803364277,
0.1439087837934494,
0.045920830219984055,
-0.03386397287249565,
0.017781836912035942,
0.070749931037426,
-0.15560059249401093,
-0.1623297780752182,
-0.031811706721782684,
-0.016942474991083145,
-0.11406322568655014,
0.06307488679885864,
0.11163705587387085,
-0.08484364300966263,
0.0035264091566205025,
-0.008415672928094864,
0.014919687993824482,
-0.002409477951005101,
0.16151992976665497,
0.08037012070417404,
0.044436246156692505,
-0.09206259250640869,
0.09767723828554153,
0.054202839732170105,
-0.1045539379119873,
0.023341206833720207,
0.025801705196499825,
-0.10466807335615158,
-0.03715038672089577,
0.06702449917793274,
0.14704498648643494,
0.0009470285149291158,
-0.05198730155825615,
-0.14375616610050201,
-0.09377666562795639,
0.057217106223106384,
0.12533320486545563,
0.09250355511903763,
0.01556249987334013,
-0.011633376590907574,
-0.0002801600785460323,
-0.10414283722639084,
0.11900807917118073,
0.03160611540079117,
0.09795945137739182,
-0.2185405194759369,
0.06070994958281517,
0.01890115812420845,
0.031268004328012466,
-0.019250933080911636,
0.029586996883153915,
-0.09804419428110123,
-0.01634339988231659,
-0.05997609347105026,
0.04208562150597572,
-0.036590032279491425,
0.005531745962798595,
-0.0064903125166893005,
-0.06879284232854843,
-0.06098901107907295,
0.04104362055659294,
-0.10035879909992218,
-0.046047866344451904,
0.03615729510784149,
0.07032033801078796,
-0.10205142945051193,
-0.029235344380140305,
0.025446485728025436,
-0.08039696514606476,
0.0790892168879509,
0.014095950871706009,
0.0005695505533367395,
0.023463815450668335,
-0.10042203217744827,
0.010635514743626118,
0.08415917307138443,
0.0029707292560487986,
0.030986838042736053,
-0.10393767058849335,
0.007057030685245991,
-0.0011036454234272242,
0.0009315675706602633,
-0.008648671209812164,
0.10397418588399887,
-0.13311968743801117,
-0.025813480839133263,
-0.037991661578416824,
-0.03324704244732857,
-0.05948195978999138,
0.06284357607364655,
0.08606432378292084,
-0.0030004456639289856,
0.1998845636844635,
-0.08585313707590103,
0.00010894424485741183,
-0.2236366719007492,
0.004054774064570665,
-0.004355728160589933,
-0.1370699256658554,
-0.12498512864112854,
-0.028259091079235077,
0.05320440232753754,
-0.07354100048542023,
0.09616898745298386,
0.016123060137033463,
0.005351166240870953,
0.03564183786511421,
0.0026460830122232437,
-0.0028193816542625427,
0.02624340169131756,
0.18615828454494476,
-0.007491840049624443,
-0.02064543217420578,
0.07138451188802719,
0.018578987568616867,
0.11744797974824905,
0.08343684673309326,
0.0985216423869133,
0.1616794615983963,
-0.04428549483418465,
0.10382276773452759,
0.049792271107435226,
-0.0221316646784544,
-0.1735774725675583,
0.10315366834402084,
-0.07480514794588089,
0.1442563533782959,
-0.013153218664228916,
0.16521982848644257,
0.12247242778539658,
-0.1585603505373001,
0.028127895668148994,
-0.028060633689165115,
-0.07330657541751862,
-0.0704883560538292,
-0.14566665887832642,
-0.11752930283546448,
-0.18573613464832306,
0.014560677111148834,
-0.09806596487760544,
0.007403009105473757,
0.07112178951501846,
-0.009295541793107986,
-0.02352297119796276,
0.20558007061481476,
0.05049857869744301,
-0.002510844962671399,
0.07032909989356995,
0.0015775273786857724,
-0.06872397661209106,
-0.061035364866256714,
-0.08496210724115372,
0.03848041966557503,
-0.00851019099354744,
0.03335035592317581,
-0.02992033213376999,
-0.005304316058754921,
0.0488789863884449,
-0.00015379609249066561,
-0.1098908856511116,
0.018044419586658478,
0.014951071701943874,
0.010534374043345451,
0.0008333100704476237,
0.004809625446796417,
0.006202142685651779,
-0.009944885037839413,
0.1820433884859085,
-0.05484237149357796,
-0.006836243439465761,
-0.11771633476018906,
0.12500759959220886,
0.027567386627197266,
-0.01616005413234234,
0.029098497703671455,
-0.07949063926935196,
0.026830408722162247,
0.21858848631381989,
0.14383293688297272,
-0.0167448278516531,
-0.0014522324781864882,
-0.00857983622699976,
-0.020643005147576332,
-0.03108217939734459,
0.09174125641584396,
0.09339619427919388,
-0.0447763167321682,
-0.05456433817744255,
-0.022962506860494614,
-0.04835779592394829,
-0.016245421022176743,
-0.03796777129173279,
0.039009418338537216,
0.01815023086965084,
0.01443538349121809,
-0.06322929263114929,
0.042721226811409,
0.02114632911980152,
-0.07337304949760437,
0.0894613191485405,
-0.19521470367908478,
-0.13894040882587433,
-0.03288603574037552,
0.10051017254590988,
-0.006018717773258686,
0.02896568924188614,
-0.02127797342836857,
0.015905743464827538,
0.06856148689985275,
-0.02353663370013237,
-0.08276108652353287,
-0.09917619824409485,
0.05052541568875313,
-0.1333807408809662,
0.24502243101596832,
-0.032482389360666275,
0.00661885691806674,
0.11178344488143921,
0.018475130200386047,
-0.11790914833545685,
0.05208421126008034,
0.025536421686410904,
-0.03645871579647064,
0.025177190080285072,
0.11177454143762589,
-0.020675083622336388,
0.10754010826349258,
0.034746766090393066,
-0.08897331357002258,
-0.01814214512705803,
-0.054646085947752,
-0.04100141301751137,
-0.05697661265730858,
-0.02364540658891201,
-0.06854301691055298,
0.12410563230514526,
0.173186793923378,
-0.04242303967475891,
-0.02637280523777008,
-0.06457078456878662,
0.037550926208496094,
0.09137038141489029,
0.016641056165099144,
-0.012749847024679184,
-0.2280997335910797,
0.017656221985816956,
0.024374619126319885,
-0.003917396999895573,
-0.2118307650089264,
-0.11007525026798248,
-0.017804253846406937,
-0.053288642317056656,
-0.08763647079467773,
0.08584819734096527,
0.11768825352191925,
0.04970311373472214,
-0.060780398547649384,
-0.04441050440073013,
-0.06915197521448135,
0.1602003425359726,
-0.12230600416660309,
-0.08478182554244995
] |
null | null | transformers | # OmniCorso-7B
## Code Example
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("macadeliccc/OmniCorso-7B")
model = AutoModelForCausalLM.from_pretrained("macadeliccc/OmniCorso-7B")
messages = [
{"role": "system", "content": "Respond to the users request like a pirate"},
{"role": "user", "content": "Can you write me a quicksort algorithm?"}
]
gen_input = tokenizer.apply_chat_template(messages, return_tensors="pt")
```
The following models were included in the merge:
* [macadeliccc/MBX-7B-v3-DPO](https://huggingface.co/macadeliccc/MBX-7B-v3-DPO)
* [mlabonne/OmniBeagle-7B](https://huggingface.co/mlabonne/OmniBeagle-7B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: mlabonne/OmniBeagle-7B
layer_range: [0, 32]
- model: macadeliccc/MBX-7B-v3-DPO
layer_range: [0, 32]
merge_method: slerp
base_model: macadeliccc/MBX-7B-v3-DPO
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
```
## Quantizations
### GGUF
+ [iMatrix](https://huggingface.co/macadeliccc/OmniCorso-7B-GGUF)
### Exllamav2
Quants are available thanks to user bartowski, check them out [here](https://huggingface.co/bartowski/OmniCorso-7B-exl2)
| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
| [8_0](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| [6_5](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
| [5_0](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB | 9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
| [4_25](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
| [3_5](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
## Evaluations
<pre>----Benchmark Complete----
2024-02-11 15:34:40
Time taken: 178.3 mins
Prompt Format: ChatML
Model: macadeliccc/OmniCorso-7B
Score (v2): 73.75
Parseable: 167.0
---------------
Batch completed
Time taken: 178.3 mins
---------------
</pre>
| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
|---------------------------------------------------------------|------:|------:|---------:|-------:|------:|
|[OmniCorso-7B](https://huggingface.co/macadeliccc/OmniCorso-7B)| 45.89| 77.66| 74.12| 49.24| 61.73|
### AGIEval
| Task |Version| Metric |Value| |Stderr|
|------------------------------|------:|--------|----:|---|-----:|
|agieval_aqua_rat | 0|acc |29.13|± | 2.86|
| | |acc_norm|27.17|± | 2.80|
|agieval_logiqa_en | 0|acc |39.32|± | 1.92|
| | |acc_norm|39.63|± | 1.92|
|agieval_lsat_ar | 0|acc |23.91|± | 2.82|
| | |acc_norm|23.91|± | 2.82|
|agieval_lsat_lr | 0|acc |53.14|± | 2.21|
| | |acc_norm|53.92|± | 2.21|
|agieval_lsat_rc | 0|acc |66.54|± | 2.88|
| | |acc_norm|67.29|± | 2.87|
|agieval_sat_en | 0|acc |80.58|± | 2.76|
| | |acc_norm|80.58|± | 2.76|
|agieval_sat_en_without_passage| 0|acc |45.63|± | 3.48|
| | |acc_norm|43.69|± | 3.46|
|agieval_sat_math | 0|acc |33.18|± | 3.18|
| | |acc_norm|30.91|± | 3.12|
Average: 45.89%
### GPT4All
| Task |Version| Metric |Value| |Stderr|
|-------------|------:|--------|----:|---|-----:|
|arc_challenge| 0|acc |67.32|± | 1.37|
| | |acc_norm|68.43|± | 1.36|
|arc_easy | 0|acc |87.46|± | 0.68|
| | |acc_norm|83.50|± | 0.76|
|boolq | 1|acc |88.13|± | 0.57|
|hellaswag | 0|acc |68.47|± | 0.46|
| | |acc_norm|86.96|± | 0.34|
|openbookqa | 0|acc |38.80|± | 2.18|
| | |acc_norm|50.00|± | 2.24|
|piqa | 0|acc |83.03|± | 0.88|
| | |acc_norm|85.31|± | 0.83|
|winogrande | 0|acc |81.29|± | 1.10|
Average: 77.66%
### TruthfulQA
| Task |Version|Metric|Value| |Stderr|
|-------------|------:|------|----:|---|-----:|
|truthfulqa_mc| 1|mc1 |58.26|± | 1.73|
| | |mc2 |74.12|± | 1.43|
Average: 74.12%
### Bigbench
| Task |Version| Metric |Value| |Stderr|
|------------------------------------------------|------:|---------------------|----:|---|-----:|
|bigbench_causal_judgement | 0|multiple_choice_grade|56.84|± | 3.60|
|bigbench_date_understanding | 0|multiple_choice_grade|63.41|± | 2.51|
|bigbench_disambiguation_qa | 0|multiple_choice_grade|49.22|± | 3.12|
|bigbench_geometric_shapes | 0|multiple_choice_grade|23.96|± | 2.26|
| | |exact_str_match | 1.39|± | 0.62|
|bigbench_logical_deduction_five_objects | 0|multiple_choice_grade|34.20|± | 2.12|
|bigbench_logical_deduction_seven_objects | 0|multiple_choice_grade|23.71|± | 1.61|
|bigbench_logical_deduction_three_objects | 0|multiple_choice_grade|60.33|± | 2.83|
|bigbench_movie_recommendation | 0|multiple_choice_grade|49.00|± | 2.24|
|bigbench_navigate | 0|multiple_choice_grade|55.20|± | 1.57|
|bigbench_reasoning_about_colored_objects | 0|multiple_choice_grade|70.75|± | 1.02|
|bigbench_ruin_names | 0|multiple_choice_grade|55.80|± | 2.35|
|bigbench_salient_translation_error_detection | 0|multiple_choice_grade|36.97|± | 1.53|
|bigbench_snarks | 0|multiple_choice_grade|72.38|± | 3.33|
|bigbench_sports_understanding | 0|multiple_choice_grade|76.27|± | 1.36|
|bigbench_temporal_sequences | 0|multiple_choice_grade|54.50|± | 1.58|
|bigbench_tracking_shuffled_objects_five_objects | 0|multiple_choice_grade|23.12|± | 1.19|
|bigbench_tracking_shuffled_objects_seven_objects| 0|multiple_choice_grade|20.34|± | 0.96|
|bigbench_tracking_shuffled_objects_three_objects| 0|multiple_choice_grade|60.33|± | 2.83|
Average: 49.24%
Average score: 61.73%
Elapsed time: 02:20:06 | {"license": "cc", "tags": ["mergekit", "merge"], "base_model": ["macadeliccc/MBX-7B-v3-DPO", "mlabonne/OmniBeagle-7B"]} | text-generation | macadeliccc/OmniCorso-7B | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"base_model:macadeliccc/MBX-7B-v3-DPO",
"base_model:mlabonne/OmniBeagle-7B",
"license:cc",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T04:33:07+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #base_model-macadeliccc/MBX-7B-v3-DPO #base_model-mlabonne/OmniBeagle-7B #license-cc #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| OmniCorso-7B
============
!image/webp
Code Example
------------
The following models were included in the merge:
* macadeliccc/MBX-7B-v3-DPO
* mlabonne/OmniBeagle-7B
### Configuration
The following YAML configuration was used to produce this model:
Quantizations
-------------
### GGUF
* iMatrix
### Exllamav2
Quants are available thanks to user bartowski, check them out here
Evaluations
-----------
```
----Benchmark Complete----
2024-02-11 15:34:40
Time taken: 178.3 mins
Prompt Format: ChatML
Model: macadeliccc/OmniCorso-7B
Score (v2): 73.75
Parseable: 167.0
---------------
Batch completed
Time taken: 178.3 mins
---------------
```
### AGIEval
Average: 45.89%
### GPT4All
Average: 77.66%
### TruthfulQA
Average: 74.12%
### Bigbench
Average: 49.24%
Average score: 61.73%
Elapsed time: 02:20:06
| [
"### Configuration\n\n\nThe following YAML configuration was used to produce this model:\n\n\nQuantizations\n-------------",
"### GGUF\n\n\n* iMatrix",
"### Exllamav2\n\n\nQuants are available thanks to user bartowski, check them out here\n\n\n\nEvaluations\n-----------\n\n\n\n```\n----Benchmark Complete----\n2024-02-11 15:34:40\nTime taken: 178.3 mins\nPrompt Format: ChatML\nModel: macadeliccc/OmniCorso-7B\nScore (v2): 73.75\nParseable: 167.0\n---------------\nBatch completed\nTime taken: 178.3 mins\n---------------\n\n```",
"### AGIEval\n\n\n\nAverage: 45.89%",
"### GPT4All\n\n\n\nAverage: 77.66%",
"### TruthfulQA\n\n\n\nAverage: 74.12%",
"### Bigbench\n\n\n\nAverage: 49.24%\n\n\nAverage score: 61.73%\n\n\nElapsed time: 02:20:06"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #mergekit #merge #base_model-macadeliccc/MBX-7B-v3-DPO #base_model-mlabonne/OmniBeagle-7B #license-cc #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Configuration\n\n\nThe following YAML configuration was used to produce this model:\n\n\nQuantizations\n-------------",
"### GGUF\n\n\n* iMatrix",
"### Exllamav2\n\n\nQuants are available thanks to user bartowski, check them out here\n\n\n\nEvaluations\n-----------\n\n\n\n```\n----Benchmark Complete----\n2024-02-11 15:34:40\nTime taken: 178.3 mins\nPrompt Format: ChatML\nModel: macadeliccc/OmniCorso-7B\nScore (v2): 73.75\nParseable: 167.0\n---------------\nBatch completed\nTime taken: 178.3 mins\n---------------\n\n```",
"### AGIEval\n\n\n\nAverage: 45.89%",
"### GPT4All\n\n\n\nAverage: 77.66%",
"### TruthfulQA\n\n\n\nAverage: 74.12%",
"### Bigbench\n\n\n\nAverage: 49.24%\n\n\nAverage score: 61.73%\n\n\nElapsed time: 02:20:06"
] | [
93,
22,
9,
102,
11,
12,
11,
26
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #mergekit #merge #base_model-macadeliccc/MBX-7B-v3-DPO #base_model-mlabonne/OmniBeagle-7B #license-cc #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Configuration\n\n\nThe following YAML configuration was used to produce this model:\n\n\nQuantizations\n-------------### GGUF\n\n\n* iMatrix### Exllamav2\n\n\nQuants are available thanks to user bartowski, check them out here\n\n\n\nEvaluations\n-----------\n\n\n\n```\n----Benchmark Complete----\n2024-02-11 15:34:40\nTime taken: 178.3 mins\nPrompt Format: ChatML\nModel: macadeliccc/OmniCorso-7B\nScore (v2): 73.75\nParseable: 167.0\n---------------\nBatch completed\nTime taken: 178.3 mins\n---------------\n\n```### AGIEval\n\n\n\nAverage: 45.89%### GPT4All\n\n\n\nAverage: 77.66%### TruthfulQA\n\n\n\nAverage: 74.12%### Bigbench\n\n\n\nAverage: 49.24%\n\n\nAverage score: 61.73%\n\n\nElapsed time: 02:20:06"
] | [
-0.14338967204093933,
0.12657882273197174,
-0.005326959304511547,
0.035183925181627274,
0.030405091121792793,
0.0011311100097373128,
0.04508936032652855,
0.09044288843870163,
-0.015904610976576805,
0.1426657736301422,
0.10687056928873062,
0.04661673307418823,
0.08218561112880707,
0.17261424660682678,
-0.07031021267175674,
-0.14012134075164795,
0.029219824820756912,
0.005707728676497936,
0.0019841021858155727,
0.1216617077589035,
0.11178523302078247,
-0.08795958012342453,
0.0794060230255127,
0.01173012051731348,
-0.03633818030357361,
-0.022747065871953964,
-0.03567643463611603,
-0.05645166337490082,
0.08313686400651932,
0.07092755287885666,
-0.027513928711414337,
0.04714765027165413,
-0.014147785492241383,
-0.1447751820087433,
0.012603219598531723,
-0.003782691201195121,
-0.003291534027084708,
0.04685797914862633,
0.06018392741680145,
0.03648170456290245,
0.12304249405860901,
-0.06567026674747467,
0.003409146796911955,
0.047931358218193054,
-0.14127211272716522,
-0.14081381261348724,
-0.11639904975891113,
-0.003023503115400672,
0.13918636739253998,
0.05313334986567497,
-0.06420743465423584,
0.15058183670043945,
-0.08407730609178543,
0.06464287638664246,
0.24438129365444183,
-0.32134634256362915,
-0.055591143667697906,
0.10295990109443665,
0.05683039128780365,
-0.0425046943128109,
-0.08897648751735687,
0.03315069153904915,
0.08908378332853317,
0.0009587750537320971,
0.07116787880659103,
-0.02798820659518242,
0.15637165307998657,
0.01368644554167986,
-0.14117737114429474,
-0.04465748742222786,
0.1638745367527008,
0.0802651047706604,
-0.06717260181903839,
-0.11382747441530228,
-0.02319611981511116,
-0.12296149879693985,
-0.029461894184350967,
-0.042548809200525284,
0.039679884910583496,
-0.03464847058057785,
-0.010862681083381176,
0.09161937236785889,
-0.07350480556488037,
-0.026096269488334656,
-0.02950465865433216,
0.07011491805315018,
0.018429066985845566,
-0.004980679135769606,
-0.011348751373589039,
0.048821985721588135,
-0.18120267987251282,
-0.16432905197143555,
-0.08912450820207596,
0.04174380749464035,
-0.07419712096452713,
-0.050492703914642334,
-0.032975077629089355,
-0.014740794897079468,
0.06940890103578568,
0.21423660218715668,
-0.10164482891559601,
0.027891680598258972,
0.06688597053289413,
-0.011160535737872124,
0.017892874777317047,
0.16663601994514465,
-0.07234524935483932,
-0.19587206840515137,
-0.01787395402789116,
0.028039272874593735,
0.05168291553854942,
0.03120238333940506,
-0.00918788556009531,
-0.01724162884056568,
0.11141204833984375,
0.06630568951368332,
-0.00974242202937603,
0.012800545431673527,
-0.058266524225473404,
-0.025952380150556564,
0.19294287264347076,
-0.08560299128293991,
0.006804139818996191,
0.01800977624952793,
-0.10248451679944992,
-0.025094572454690933,
-0.03583531826734543,
-0.0036733578890562057,
-0.03518950939178467,
0.06480472534894943,
-0.07129370421171188,
-0.0609140545129776,
-0.03811490908265114,
-0.07487723231315613,
0.04643503576517105,
-0.01406518742442131,
-0.00473097525537014,
-0.10323657095432281,
-0.12542729079723358,
-0.08921868354082108,
-0.01285277958959341,
-0.08904395997524261,
-0.04659930244088173,
-0.0598798543214798,
-0.0603574775159359,
0.06008395925164223,
-0.03736855462193489,
0.09769227355718613,
-0.060305576771497726,
0.0627746507525444,
0.06234157457947731,
0.09099413454532623,
0.07147104293107986,
0.02595069818198681,
-0.11904587596654892,
0.03742808848619461,
-0.11501730978488922,
0.014328151009976864,
-0.0035967633593827486,
0.04830760508775711,
-0.16685965657234192,
-0.05915704742074013,
-0.02613937295973301,
-0.0009685991099104285,
0.09992966800928116,
0.1811106950044632,
-0.1268254816532135,
-0.043405432254076004,
0.12843206524848938,
-0.05781330168247223,
-0.16236567497253418,
0.14788100123405457,
0.041645292192697525,
-0.004107606131583452,
0.07541713118553162,
0.13873547315597534,
0.02479637786746025,
-0.09987788647413254,
-0.06865694373846054,
-0.0870327353477478,
0.08791878074407578,
0.02950039692223072,
0.11874677240848541,
-0.0295418594032526,
0.0962328314781189,
0.03048950806260109,
-0.046249307692050934,
-0.006802783813327551,
-0.07421135902404785,
-0.04967868700623512,
-0.006173391826450825,
-0.07999042421579361,
0.01518391352146864,
-0.011206415481865406,
0.014865530654788017,
-0.09811911731958389,
-0.07275882363319397,
-0.08411263674497604,
0.09386860579252243,
0.04029833525419235,
-0.0011440619127824903,
-0.09071876108646393,
0.09804970771074295,
-0.023808300495147705,
0.019080257043242455,
-0.08416356146335602,
0.023321514949202538,
0.04398653283715248,
-0.03242804855108261,
-0.03144840896129608,
-0.03309190645813942,
0.051835961639881134,
0.011687226593494415,
-0.026510924100875854,
-0.0502486415207386,
0.05860499292612076,
-0.0371299609541893,
-0.07721403241157532,
-0.12494886666536331,
0.004542477894574404,
-0.042772676795721054,
0.05442648380994797,
-0.16029487550258636,
0.0054369131103158,
0.06371446698904037,
0.1051008552312851,
0.009195281192660332,
-0.05955323949456215,
0.03389366716146469,
-0.005065278150141239,
-0.03955727070569992,
-0.03786830976605415,
-0.0057858978398144245,
0.014082366600632668,
-0.07588791847229004,
0.1286724954843521,
-0.19115222990512848,
0.09900091588497162,
0.07028696686029434,
0.07038624584674835,
-0.08386299759149551,
-0.03057156503200531,
-0.00633218651637435,
-0.03180234134197235,
-0.026828153058886528,
-0.036671314388513565,
0.08120861649513245,
0.04199628159403801,
0.10170170664787292,
-0.08866432309150696,
-0.07102633267641068,
0.027176449075341225,
-0.027773777022957802,
-0.05800492316484451,
0.18291692435741425,
-0.040897469967603683,
-0.19140365719795227,
0.06313955783843994,
0.15528754889965057,
0.05329453945159912,
0.1263798624277115,
-0.00784260779619217,
-0.07367943972349167,
-0.08810196816921234,
0.06696685403585434,
0.022032449021935463,
0.10007975250482559,
-0.12576663494110107,
-0.004839209374040365,
0.02912289649248123,
0.0400298573076725,
-0.014176479540765285,
-0.0713384822010994,
0.007837693206965923,
0.05220162123441696,
-0.04471632465720177,
0.03897453844547272,
0.061263374984264374,
-0.03946930170059204,
0.10379824787378311,
0.05348227545619011,
-0.016550427302718163,
-0.053949907422065735,
-0.01803087256848812,
-0.09656751900911331,
0.24048732221126556,
-0.034550730139017105,
-0.17402029037475586,
-0.0656944215297699,
0.007145260460674763,
-0.030212687328457832,
-0.0037095840089023113,
0.07634534686803818,
-0.0946982353925705,
-0.06937918066978455,
-0.07333066314458847,
0.10852872580289841,
0.02272467128932476,
0.02765447460114956,
0.06342601031064987,
-0.04152875393629074,
0.03623105213046074,
-0.10254600644111633,
-0.01828189566731453,
-0.015797650441527367,
-0.052051544189453125,
0.05594863370060921,
-0.01794842816889286,
0.11212339252233505,
0.11183514446020126,
0.04093194380402565,
0.008214055560529232,
-0.013436398468911648,
0.24041643738746643,
-0.09262031316757202,
-0.01025433000177145,
0.14679589867591858,
0.09006168693304062,
0.01756173186004162,
0.11547404527664185,
0.0004431096895132214,
-0.11061543971300125,
0.018075354397296906,
0.05216581001877785,
-0.04360446706414223,
-0.19421637058258057,
-0.07039517164230347,
-0.03462347760796547,
0.0451292060315609,
0.09394970536231995,
0.046264536678791046,
-0.042886193841695786,
0.00396809121593833,
-0.07039143145084381,
-0.010926523245871067,
0.012806984595954418,
0.05963787063956261,
0.06127634271979332,
0.012619107961654663,
0.09284518659114838,
-0.003180621424689889,
0.019283032044768333,
0.09887238591909409,
-0.02940499596297741,
0.08794521540403366,
0.008149291388690472,
0.18519188463687897,
0.05056212842464447,
0.0749119445681572,
-0.02953951060771942,
0.006887476891279221,
-0.007594414055347443,
-0.049217477440834045,
-0.005026808939874172,
-0.0731777623295784,
-0.0070944856852293015,
0.06116272881627083,
-0.019726216793060303,
0.030146390199661255,
-0.12451257556676865,
0.03809027001261711,
0.08366385847330093,
0.1894809603691101,
0.17104944586753845,
-0.25898048281669617,
-0.11278530955314636,
0.02459564432501793,
-0.0309273824095726,
-0.054587412625551224,
0.015492531470954418,
-0.0076970565132796764,
-0.07172362506389618,
0.09127578139305115,
-0.0004423299978952855,
0.10048682242631912,
-0.02847900241613388,
0.009195960126817226,
-0.0018577792216092348,
0.021018533036112785,
-0.025211386382579803,
0.016886895522475243,
-0.23937582969665527,
0.24546155333518982,
0.03404320403933525,
0.06773604452610016,
-0.0324651338160038,
-0.03146380931138992,
0.0027405438013374805,
0.008697324432432652,
0.12030484527349472,
0.004362309817224741,
-0.0597866028547287,
-0.12832611799240112,
-0.08732964843511581,
0.0011358297197148204,
0.031001372262835503,
-0.05902538076043129,
0.11040093749761581,
0.010176559910178185,
0.01069650799036026,
-0.007675813976675272,
0.020245620980858803,
-0.08581413328647614,
0.012949454598128796,
0.03690536320209503,
0.05796192213892937,
0.018504971638321877,
-0.06652349978685379,
-0.03802439197897911,
-0.13286526501178741,
0.19052444398403168,
-0.007099017966538668,
-0.04554763808846474,
-0.0862022191286087,
0.06916040927171707,
0.11422647535800934,
-0.1272430121898651,
0.005461021326482296,
-0.0006484537152573466,
0.10660255700349808,
0.008813084103167057,
-0.03836052119731903,
0.09276466816663742,
-0.061366040259599686,
-0.14905990660190582,
-0.030642688274383545,
0.14339835941791534,
0.020457740873098373,
0.04366901516914368,
0.023150987923145294,
0.04368775710463524,
-0.020038986578583717,
-0.06679844111204147,
0.04358475282788277,
-0.01199965737760067,
-0.007361469324678183,
0.03831569850444794,
0.04432493820786476,
-0.03342720493674278,
-0.04497704654932022,
-0.09632004797458649,
0.06758569180965424,
0.3622662127017975,
-0.0538947768509388,
0.03285425156354904,
0.125419482588768,
-0.03355194255709648,
-0.18905416131019592,
-0.03239181265234947,
0.02332223393023014,
0.058596570044755936,
0.028202863410115242,
-0.05595584586262703,
0.024667713791131973,
0.09251897782087326,
-0.041563451290130615,
0.06191292032599449,
-0.31945258378982544,
-0.13708257675170898,
0.10428120940923691,
0.01601787470281124,
0.10721264779567719,
-0.20492355525493622,
-0.08209292590618134,
0.0022566679399460554,
-0.1687757521867752,
-0.01400699745863676,
-0.02457193098962307,
0.0699642226099968,
-0.0517432801425457,
0.06177293136715889,
0.04365987330675125,
-0.051666293293237686,
0.1554897576570511,
-0.017111560329794884,
0.03159363195300102,
-0.08148131519556046,
-0.000299373350571841,
-0.002133241854608059,
-0.08746723085641861,
0.11302163451910019,
-0.07707756757736206,
0.052509330213069916,
-0.09341365844011307,
-0.02163538709282875,
-0.07712119072675705,
0.030554048717021942,
-0.054431915283203125,
-0.03290005400776863,
-0.09327838569879532,
0.07090692222118378,
0.03607219457626343,
-0.019218824803829193,
0.08490384370088577,
-0.030897537246346474,
0.07574786245822906,
0.14831723272800446,
0.02651364542543888,
-0.1020449846982956,
-0.04882432892918587,
0.01605895347893238,
0.010549862869083881,
0.053824204951524734,
-0.14319567382335663,
0.03381859138607979,
0.11793175339698792,
0.06668642908334732,
0.11163125932216644,
-0.013174223713576794,
-0.0906129851937294,
0.026524489745497704,
0.053641580045223236,
-0.11882463842630386,
-0.12219458818435669,
-0.018422216176986694,
0.02902892976999283,
-0.0924152061343193,
0.03600139915943146,
0.1613859236240387,
-0.026493530720472336,
-0.003158885519951582,
-0.005919689312577248,
0.09489213675260544,
-0.014773814007639885,
0.25385206937789917,
-0.048539966344833374,
0.07269038259983063,
-0.09519853442907333,
0.07932411134243011,
0.04797685891389847,
-0.06944398581981659,
0.022222008556127548,
0.07425066083669662,
-0.06760679930448532,
-0.057451799511909485,
0.016396619379520416,
0.030352549627423286,
-0.12059146910905838,
-0.02484091930091381,
-0.11258268356323242,
-0.10692098736763,
0.07726138085126877,
0.07611934840679169,
0.0873529240489006,
0.04198794439435005,
0.0557086318731308,
-0.03335932269692421,
-0.01718982495367527,
0.07433347404003143,
0.12157381325960159,
0.04217370226979256,
-0.06825016438961029,
0.07312856614589691,
-0.05836588144302368,
0.002615240402519703,
-0.010686271823942661,
-0.009762968868017197,
-0.12321848422288895,
0.01956602931022644,
-0.09948278963565826,
0.005172268021851778,
-0.10806272178888321,
0.007759836968034506,
-0.04704919457435608,
-0.02355712279677391,
-0.06801876425743103,
0.0260931346565485,
-0.05649586766958237,
-0.05389174818992615,
-0.03806987404823303,
0.06888986378908157,
-0.11761967837810516,
-0.04079504311084747,
0.02575705014169216,
-0.061970677226781845,
0.08324184268712997,
-0.006486746482551098,
0.03528520092368126,
-0.0034210821613669395,
-0.12617476284503937,
0.04361362010240555,
0.03966302052140236,
-0.024161823093891144,
0.021740544587373734,
-0.17173068225383759,
-0.008001245558261871,
0.005194212310016155,
-0.028913745656609535,
0.03846070170402527,
-0.013508455827832222,
-0.10476570576429367,
-0.08122430741786957,
-0.06672888249158859,
0.009863552637398243,
-0.0326068215072155,
0.04829256609082222,
0.0409226268529892,
0.0336112380027771,
0.09625771641731262,
-0.06295950710773468,
-0.00501469848677516,
-0.19964563846588135,
0.001632573315873742,
-0.013517074286937714,
-0.0478474460542202,
-0.0764257088303566,
0.02421688288450241,
0.08096295595169067,
-0.038096338510513306,
0.06547433882951736,
-0.05108553171157837,
0.019042298197746277,
0.05822329595685005,
-0.0032845218665897846,
0.026805780827999115,
0.000155608679051511,
0.16567394137382507,
-0.0007173820631578565,
-0.013993789441883564,
-0.0344318225979805,
0.07875771820545197,
0.05128485709428787,
0.04935072734951973,
0.0946483388543129,
0.16304662823677063,
0.05250975489616394,
0.09504937380552292,
-0.02709590084850788,
-0.10435795038938522,
-0.08719176799058914,
0.042160872370004654,
-0.08538483828306198,
0.10662117600440979,
0.013914148323237896,
0.09273945540189743,
0.17289867997169495,
-0.19107545912265778,
0.027325278148055077,
-0.06766410917043686,
-0.024243414402008057,
-0.07914227247238159,
-0.11137555539608002,
-0.12477163225412369,
-0.09441822022199631,
0.007718970999121666,
-0.12587787210941315,
0.08143488317728043,
-0.020243074744939804,
0.060016173869371414,
0.0018692531157284975,
0.10802239179611206,
0.0008014341001398861,
-0.053874626755714417,
0.13318435847759247,
0.007667966187000275,
-0.03633067011833191,
0.028243068605661392,
0.023107819259166718,
0.03892166167497635,
-0.00661664642393589,
0.049627307802438736,
-0.0009510844247415662,
-0.03495419770479202,
0.04185657948255539,
-0.0015371949411928654,
-0.08719930797815323,
-0.01225755549967289,
0.0350133441388607,
0.06872602552175522,
0.08671291172504425,
0.058572687208652496,
0.010332494974136353,
-0.005498302634805441,
0.18202972412109375,
-0.0361478365957737,
-0.009617937728762627,
-0.10724281519651413,
0.11545218527317047,
0.04847157001495361,
0.028131410479545593,
0.0006441646255552769,
-0.06953798979520798,
0.0395178496837616,
0.16162756085395813,
0.09555727243423462,
0.00971230398863554,
-0.02619534730911255,
-0.035557497292757034,
0.0057603828608989716,
0.024793526157736778,
0.03231753036379814,
0.04733880236744881,
0.17356497049331665,
-0.05534154549241066,
0.014132912270724773,
-0.05077415704727173,
-0.03740527853369713,
0.006393895018845797,
0.10494746267795563,
0.01252297218888998,
0.023711886256933212,
-0.03596194460988045,
0.09353763610124588,
0.0037138222251087427,
-0.11689868569374084,
-0.012486412189900875,
-0.1717919558286667,
-0.13092587888240814,
-0.029059510678052902,
0.019514312967658043,
0.039002399891614914,
0.08535393327474594,
-0.012491008266806602,
0.003251368412747979,
0.023722844198346138,
-0.01347406581044197,
-0.06799213588237762,
-0.16080112755298615,
0.04768231138586998,
0.04479018226265907,
0.22481665015220642,
0.0024173674173653126,
0.021365802735090256,
0.14039230346679688,
0.008950339630246162,
-0.12114129960536957,
0.03833848983049393,
0.07740392535924911,
-0.07367108762264252,
0.07195725291967392,
0.08327405899763107,
-0.022279849275946617,
0.10532303899526596,
0.09428036957979202,
-0.10240694135427475,
-0.0030364729464054108,
-0.0035600527189671993,
0.012493442744016647,
-0.12123400717973709,
0.08910761028528214,
-0.03617622330784798,
0.14937588572502136,
0.1491071581840515,
-0.0723835751414299,
-0.01796574518084526,
-0.024564649909734726,
0.08894006907939911,
0.007265838794410229,
0.0904000997543335,
0.014282550662755966,
-0.2287159264087677,
0.08888086676597595,
0.039034780114889145,
0.03417333588004112,
-0.25468772649765015,
-0.08631183952093124,
0.01063064206391573,
-0.016128946095705032,
-0.013249044306576252,
0.15912534296512604,
0.07952431589365005,
0.007778014987707138,
-0.044936083257198334,
-0.13127191364765167,
-0.02586459182202816,
0.1393776684999466,
-0.1042022705078125,
-0.12359867990016937
] |
null | null | transformers |
# komt : korean multi task instruction tuning model
Recently, due to the success of ChatGPT, numerous large language models have emerged in an attempt to catch up with ChatGPT's capabilities.
However, when it comes to Korean language performance, it has been observed that many models still struggle to provide accurate answers or generate Korean text effectively.
This study addresses these challenges by introducing a multi-task instruction technique that leverages supervised datasets from various tasks to create training data for Large Language Models (LLMs).
## Model Details
LDCC/LDCC-SOLAR-10.7B 모델을 base로 komt 데이터셋으로 sft학습한 모델입니다.
현재 최종 완료버전의 모델은 아니며, 다양한 데이터셋으로 성능 튜닝중입니다.
* **Model Developers** : davidkim(changyeon kim)
* **Repository** : https://github.com/davidkim205/komt
* **base mode** : LDCC/LDCC-SOLAR-10.7B
| {"language": ["ko"], "license": "cc-by-4.0"} | text-generation | davidkim205/komt-solar-10.7b-v1 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"ko",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T04:36:12+00:00 | [] | [
"ko"
] | TAGS
#transformers #safetensors #llama #text-generation #ko #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# komt : korean multi task instruction tuning model
!multi task instruction URL
Recently, due to the success of ChatGPT, numerous large language models have emerged in an attempt to catch up with ChatGPT's capabilities.
However, when it comes to Korean language performance, it has been observed that many models still struggle to provide accurate answers or generate Korean text effectively.
This study addresses these challenges by introducing a multi-task instruction technique that leverages supervised datasets from various tasks to create training data for Large Language Models (LLMs).
## Model Details
LDCC/LDCC-SOLAR-10.7B 모델을 base로 komt 데이터셋으로 sft학습한 모델입니다.
현재 최종 완료버전의 모델은 아니며, 다양한 데이터셋으로 성능 튜닝중입니다.
* Model Developers : davidkim(changyeon kim)
* Repository : URL
* base mode : LDCC/LDCC-SOLAR-10.7B
| [
"# komt : korean multi task instruction tuning model\n!multi task instruction URL\n\nRecently, due to the success of ChatGPT, numerous large language models have emerged in an attempt to catch up with ChatGPT's capabilities. \nHowever, when it comes to Korean language performance, it has been observed that many models still struggle to provide accurate answers or generate Korean text effectively. \nThis study addresses these challenges by introducing a multi-task instruction technique that leverages supervised datasets from various tasks to create training data for Large Language Models (LLMs).",
"## Model Details\n\nLDCC/LDCC-SOLAR-10.7B 모델을 base로 komt 데이터셋으로 sft학습한 모델입니다.\n현재 최종 완료버전의 모델은 아니며, 다양한 데이터셋으로 성능 튜닝중입니다. \n\n* Model Developers : davidkim(changyeon kim)\n* Repository : URL\n* base mode : LDCC/LDCC-SOLAR-10.7B"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #ko #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# komt : korean multi task instruction tuning model\n!multi task instruction URL\n\nRecently, due to the success of ChatGPT, numerous large language models have emerged in an attempt to catch up with ChatGPT's capabilities. \nHowever, when it comes to Korean language performance, it has been observed that many models still struggle to provide accurate answers or generate Korean text effectively. \nThis study addresses these challenges by introducing a multi-task instruction technique that leverages supervised datasets from various tasks to create training data for Large Language Models (LLMs).",
"## Model Details\n\nLDCC/LDCC-SOLAR-10.7B 모델을 base로 komt 데이터셋으로 sft학습한 모델입니다.\n현재 최종 완료버전의 모델은 아니며, 다양한 데이터셋으로 성능 튜닝중입니다. \n\n* Model Developers : davidkim(changyeon kim)\n* Repository : URL\n* base mode : LDCC/LDCC-SOLAR-10.7B"
] | [
58,
127,
90
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #ko #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# komt : korean multi task instruction tuning model\n!multi task instruction URL\n\nRecently, due to the success of ChatGPT, numerous large language models have emerged in an attempt to catch up with ChatGPT's capabilities. \nHowever, when it comes to Korean language performance, it has been observed that many models still struggle to provide accurate answers or generate Korean text effectively. \nThis study addresses these challenges by introducing a multi-task instruction technique that leverages supervised datasets from various tasks to create training data for Large Language Models (LLMs).## Model Details\n\nLDCC/LDCC-SOLAR-10.7B 모델을 base로 komt 데이터셋으로 sft학습한 모델입니다.\n현재 최종 완료버전의 모델은 아니며, 다양한 데이터셋으로 성능 튜닝중입니다. \n\n* Model Developers : davidkim(changyeon kim)\n* Repository : URL\n* base mode : LDCC/LDCC-SOLAR-10.7B"
] | [
0.03533271327614784,
-0.1053159236907959,
-0.0013875272125005722,
0.00013627047883346677,
0.11845850199460983,
0.006769007537513971,
0.08999821543693542,
0.036550164222717285,
0.03281797096133232,
0.01389355305582285,
0.07353650778532028,
0.08107855916023254,
0.04469359293580055,
0.014485110528767109,
-0.028626782819628716,
-0.25837573409080505,
0.058064404875040054,
-0.05400160700082779,
0.041600413620471954,
0.005254663992673159,
0.09081267565488815,
-0.007294479291886091,
0.08432689309120178,
-0.019102556630969048,
-0.1084338128566742,
-0.02530434913933277,
-0.07639248669147491,
-0.054652485996484756,
0.03376109153032303,
-0.004737706854939461,
0.01800522953271866,
0.03899729251861572,
-0.00985462311655283,
0.00955392885953188,
0.007040979340672493,
-0.008870438672602177,
0.05503704026341438,
0.027040353044867516,
-0.09226333349943161,
0.1420017033815384,
0.25278156995773315,
-0.09796861559152603,
-0.020667729899287224,
-0.04224838316440582,
0.026257993653416634,
0.07835117727518082,
-0.021227503195405006,
-0.039664313197135925,
0.2329898327589035,
0.05703963711857796,
0.007151610683649778,
0.15162870287895203,
-0.11743097007274628,
0.07763620465993881,
-0.11777165532112122,
-0.28910699486732483,
-0.06976914405822754,
0.2998509407043457,
0.07687310874462128,
0.09105238318443298,
-0.0176391638815403,
0.06743567436933517,
0.09852153807878494,
0.01868215575814247,
-0.08472955226898193,
-0.08597432076931,
-0.11011002957820892,
-0.0031533665023744106,
-0.07060259580612183,
0.0201713927090168,
0.34655502438545227,
0.016090143471956253,
-0.026198090985417366,
-0.1891268938779831,
-0.022053750231862068,
0.11353640258312225,
-0.011076949536800385,
-0.02014787122607231,
-0.019873885437846184,
0.0023915984202176332,
0.0265142023563385,
-0.1328083872795105,
-0.010393127799034119,
-0.11456624418497086,
-0.06191236525774002,
0.0644887313246727,
0.05550336837768555,
0.03902477025985718,
-0.05228883773088455,
0.09580681473016739,
-0.09407540410757065,
-0.0786762610077858,
-0.06559497117996216,
-0.10882805287837982,
-0.0874948501586914,
0.006668696179986,
0.0006601136410608888,
-0.06176299229264259,
0.05847598612308502,
0.009742341004312038,
0.12185568362474442,
0.10293567925691605,
-0.06008239462971687,
0.03444701433181763,
0.05350659415125847,
0.1480543613433838,
-0.0744197890162468,
0.040719665586948395,
0.044646091759204865,
0.034643951803445816,
0.0567963607609272,
-0.019255205988883972,
-0.11194068193435669,
-0.05999906361103058,
-0.04261472821235657,
0.055741097778081894,
-0.02730534039437771,
0.1452329307794571,
0.015092626214027405,
0.021021423861384392,
0.12446349114179611,
-0.02713349461555481,
-0.03751378878951073,
-0.01126756053417921,
-0.06693536043167114,
0.14157958328723907,
0.03164859488606453,
0.03160615265369415,
-0.012471565045416355,
-0.060330916196107864,
-0.011382185854017735,
-0.07757826149463654,
-0.06366396695375443,
-0.06272470951080322,
-0.0014684665948152542,
-0.027023503556847572,
0.052858617156744,
-0.06425455957651138,
-0.2277144342660904,
-0.021309351548552513,
-0.016519328579306602,
-0.10137888044118881,
-0.047742489725351334,
-0.08950349688529968,
-0.15032437443733215,
0.011995918117463589,
-0.04116953909397125,
0.10910628736019135,
-0.006457747425884008,
-0.032277464866638184,
-0.03023645468056202,
0.05757100135087967,
-0.023887230083346367,
0.006097002420574427,
-0.049452222883701324,
0.02737876959145069,
-0.13170069456100464,
0.15172117948532104,
-0.1201004832983017,
-0.017749734222888947,
-0.0787961333990097,
-0.012542029842734337,
-0.05247695371508598,
0.03796776384115219,
0.029410863295197487,
0.18989035487174988,
-0.11010617017745972,
0.04960460960865021,
0.06741888076066971,
-0.011060514487326145,
-0.10007009655237198,
0.11381012201309204,
0.01844659447669983,
0.11391013115644455,
0.06455834954977036,
0.07420054823160172,
0.060777146369218826,
-0.02508772909641266,
-0.019309548661112785,
0.15815852582454681,
-0.04416390135884285,
0.04130122438073158,
0.026764359325170517,
0.04890794679522514,
-0.14639754593372345,
0.062435805797576904,
-0.07716161012649536,
0.029416663572192192,
-0.04994026944041252,
0.0077109914273023605,
-0.07442198693752289,
-0.013258898630738258,
-0.06768058985471725,
0.02794177457690239,
0.15225817263126373,
-0.024235408753156662,
-0.03204834833741188,
0.03695806488394737,
0.1143045574426651,
-0.029346173629164696,
-0.04980694502592087,
-0.11225209385156631,
-0.044972632080316544,
-0.01685069128870964,
0.05024486407637596,
-0.001835235976614058,
-0.11899721622467041,
0.08685547858476639,
0.18910007178783417,
-0.03280964493751526,
0.09021752327680588,
0.040389809757471085,
-0.02410387434065342,
0.02260507643222809,
0.018934251740574837,
0.04409879446029663,
0.016285423189401627,
-0.025606628507375717,
-0.08686500042676926,
0.0015577907906845212,
-0.03526662290096283,
0.145372211933136,
-0.11384189128875732,
-0.037763096392154694,
-0.06406423449516296,
0.12836764752864838,
-0.06679989397525787,
0.0217093788087368,
0.10058476775884628,
0.039148978888988495,
-0.014718026854097843,
-0.05816895514726639,
-0.008071798831224442,
0.021559743210673332,
-0.10588440299034119,
0.15183448791503906,
0.03911511227488518,
-0.19388705492019653,
0.09983891993761063,
0.09101694077253342,
-0.019825764000415802,
0.058716461062431335,
0.020521875470876694,
-0.05615972727537155,
0.0003389637276995927,
-0.08512631803750992,
0.1901492178440094,
-0.04004111886024475,
0.12022075802087784,
-0.07325556129217148,
0.058501776307821274,
-0.02048775553703308,
-0.014385475777089596,
0.0030882172286510468,
0.12167900800704956,
0.1129545122385025,
-0.1353314220905304,
0.018692107871174812,
-0.11122254282236099,
-0.0515628457069397,
0.1939135491847992,
-0.035532113164663315,
-0.024099063128232956,
0.007516104727983475,
0.0996866300702095,
-0.05728590115904808,
0.028168510645627975,
-0.14811189472675323,
-0.0021602697670459747,
0.04247459024190903,
0.037014495581388474,
0.0795883908867836,
-0.07548648864030838,
-0.01203511469066143,
-0.065422922372818,
-0.03499292954802513,
-0.007967280223965645,
0.14731520414352417,
0.03886684402823448,
0.04355059191584587,
0.009854788891971111,
-0.061331361532211304,
0.0002269303222419694,
-0.04707442224025726,
-0.06259369105100632,
0.12867829203605652,
-0.09205030649900436,
-0.06739885360002518,
-0.04915332794189453,
0.15978077054023743,
-0.08243593573570251,
-0.047924358397722244,
-0.033661819994449615,
-0.07659997045993805,
-0.05560781806707382,
-0.09128778427839279,
0.012127354741096497,
-0.09725204855203629,
-0.07744010537862778,
0.0838722214102745,
-0.003764654044061899,
-0.18001244962215424,
-0.1251126080751419,
-0.020565621554851532,
-0.022506967186927795,
-0.17332544922828674,
0.08502408117055893,
-0.19193561375141144,
-0.023238904774188995,
0.08345608413219452,
0.07140735536813736,
-0.002681209472939372,
-0.006170220673084259,
0.14631502330303192,
-0.11129818856716156,
0.07005365192890167,
0.1253364086151123,
0.06384570896625519,
-0.02279413305222988,
0.07372954487800598,
-0.016443844884634018,
-0.048729974776506424,
0.057694584131240845,
-0.022633135318756104,
-0.08055415749549866,
-0.22436870634555817,
-0.08701927959918976,
-0.09478490054607391,
0.04690340533852577,
-0.09548865258693695,
0.03634124621748924,
-0.004992031957954168,
0.09473767131567001,
-0.007041687145829201,
0.07793448865413666,
0.04389270395040512,
0.026044493541121483,
0.11145196855068207,
0.0025267365854233503,
0.036078862845897675,
-0.09364108741283417,
-0.0414801649749279,
0.04569719731807709,
-0.008320672437548637,
0.19683341681957245,
-0.03309084475040436,
0.011875181458890438,
0.04420304298400879,
0.10634052008390427,
0.014139707200229168,
0.04125918820500374,
-0.0748923048377037,
-0.0507647842168808,
-0.05566312000155449,
-0.06646928191184998,
-0.030155392363667488,
0.07896705716848373,
0.042104125022888184,
-0.06536432355642319,
-0.03295690193772316,
0.14671145379543304,
0.018747905269265175,
0.08761714398860931,
0.030712420120835304,
-0.1489442139863968,
-0.030528824776411057,
0.079783596098423,
0.004227036144584417,
-0.06884041428565979,
0.07625395804643631,
0.19223958253860474,
-0.17518076300621033,
0.07498306781053543,
0.019904732704162598,
0.0756305456161499,
-0.03723996877670288,
-0.013560736551880836,
-0.10281281173229218,
0.06334205716848373,
0.026854803785681725,
0.10603062063455582,
-0.1846531182527542,
0.10746577382087708,
0.006211567670106888,
0.08568336069583893,
-0.13333451747894287,
0.037128351628780365,
-0.00281731178984046,
0.09290264546871185,
0.09444333612918854,
0.003886580467224121,
-0.029911017045378685,
0.06320875138044357,
-0.10683414340019226,
0.09006401896476746,
0.03800045698881149,
0.11101436614990234,
0.0012612100690603256,
0.009082489646971226,
-0.012263432145118713,
0.023218845948576927,
-0.14753197133541107,
-0.15686935186386108,
-0.022536935284733772,
0.018191255629062653,
0.07367296516895294,
-0.03965633362531662,
0.008022996596992016,
-0.0001664621231611818,
-0.04424843192100525,
0.179669588804245,
0.11587753146886826,
-0.12473920732736588,
-0.029697874560952187,
-0.0945441797375679,
0.1987495869398117,
-0.011705853044986725,
-0.026894360780715942,
-0.056398384273052216,
-0.035441480576992035,
0.06871667504310608,
-0.09026876091957092,
0.017214184626936913,
-0.08952346444129944,
-0.04361928999423981,
0.040471889078617096,
0.06452202051877975,
-0.04534948244690895,
-0.0037926470395177603,
0.046615950763225555,
-0.023379908874630928,
-0.04821900650858879,
-0.18212513625621796,
-0.02232099138200283,
0.12560157477855682,
-0.002996425610035658,
0.160400852560997,
-0.08319346606731415,
0.06002894043922424,
0.05019952729344368,
-0.05852819234132767,
0.04965239390730858,
0.17180003225803375,
-0.0364987775683403,
0.030953042209148407,
-0.015134191140532494,
-0.02840271033346653,
-0.17257556319236755,
-0.02962327003479004,
0.05216868594288826,
0.07900190353393555,
-0.06469009816646576,
-0.10121992230415344,
0.020896201953291893,
-0.019033728167414665,
-0.008008511736989021,
-0.09807281196117401,
-0.35872045159339905,
-0.07945379614830017,
0.06611704081296921,
-0.04182298481464386,
0.22436706721782684,
-0.08603360503911972,
-0.05157317966222763,
0.0015536911087110639,
-0.18005059659481049,
0.0826278105378151,
-0.1110096275806427,
0.11259809881448746,
-0.021177072077989578,
0.10659443587064743,
0.057938240468502045,
-0.042294472455978394,
0.14188700914382935,
-0.0038546009454876184,
0.02631187066435814,
-0.02967861108481884,
-0.012995565310120583,
-0.012429222464561462,
0.00650835782289505,
0.2527821660041809,
0.018756024539470673,
0.10783389955759048,
-0.17332489788532257,
-0.013935280032455921,
-0.10378193110227585,
0.017616597935557365,
0.00569574348628521,
-0.048974890261888504,
-0.1292295902967453,
0.03442944958806038,
-0.01981395296752453,
0.01887623220682144,
0.10390477627515793,
0.04621939733624458,
-0.04464119300246239,
-0.017128899693489075,
0.161537304520607,
0.0012700195657089353,
0.13137230277061462,
0.03067096322774887,
0.026450393721461296,
0.08392584323883057,
-0.1633600890636444,
-0.017231037840247154,
0.07736699283123016,
-0.0024002003483474255,
0.046144742518663406,
0.02690267004072666,
-0.07718659192323685,
0.031827960163354874,
0.002366555854678154,
-0.05745508894324303,
-0.17090179026126862,
-0.05216846987605095,
-0.026408778503537178,
0.18458439409732819,
0.07375352829694748,
0.08149007707834244,
-0.12146357446908951,
0.02752724289894104,
0.003252557013183832,
-0.004682214464992285,
-0.002369361463934183,
0.029574185609817505,
-0.00085305399261415,
0.024600647389888763,
-0.06124373897910118,
0.093585304915905,
-0.02266811579465866,
0.10447733849287033,
0.10559946298599243,
0.015160751529037952,
-0.13179181516170502,
-0.010129579342901707,
-0.07490174472332001,
0.039780765771865845,
0.047260843217372894,
-0.05668231099843979,
-0.05526014044880867,
-0.08233394473791122,
-0.04539738968014717,
-0.0996842235326767,
0.024629293009638786,
0.01948799192905426,
-0.04749811068177223,
-0.0023625085595995188,
-0.10663127154111862,
-0.02064109593629837,
-0.05279427021741867,
0.024374570697546005,
-0.12467654049396515,
0.044185880571603775,
0.0550469234585762,
0.1280864030122757,
-0.09021732956171036,
-0.02826429158449173,
-0.12637931108474731,
0.03326381742954254,
-0.08321770280599594,
-0.06749614328145981,
-0.105270154774189,
-0.08233077824115753,
0.02497856877744198,
-0.09231030941009521,
-0.0797288790345192,
0.029246268793940544,
-0.03900850564241409,
0.06017543375492096,
-0.05547015741467476,
0.09257352352142334,
0.002945643849670887,
-0.01795499585568905,
0.060129404067993164,
-0.0833885446190834,
0.06974875926971436,
0.07832223176956177,
-0.030781561508774757,
0.03637010604143143,
-0.09470253437757492,
0.05038056895136833,
0.04676687344908714,
0.08467155694961548,
0.016725119203329086,
0.03060189262032509,
0.017164697870612144,
0.05430800840258598,
0.0971466600894928,
0.004376518540084362,
-0.008305076509714127,
-0.07297233492136002,
-0.10583499819040298,
-0.08554993569850922,
-0.015551322139799595,
-0.06334605813026428,
0.08528443425893784,
0.05648063123226166,
0.11353842169046402,
0.059082113206386566,
-0.05060826241970062,
-0.04482247680425644,
-0.005124795250594616,
-0.06435943394899368,
-0.03359972685575485,
-0.05879829823970795,
0.08665020763874054,
-0.0027903160080313683,
0.08714425563812256,
-0.041520655155181885,
0.23842956125736237,
0.0028283384162932634,
-0.1279284656047821,
-0.038539160043001175,
0.006532891653478146,
0.07448836416006088,
-0.012306299060583115,
0.1461644023656845,
0.11162929981946945,
0.09084007889032364,
-0.05264872685074806,
-0.04342752695083618,
0.006626503076404333,
-0.04633093252778053,
0.010489230044186115,
0.015931017696857452,
-0.03997394070029259,
0.11922397464513779,
0.11341766268014908,
-0.08898600190877914,
0.012045136652886868,
-0.0032070092856884003,
-0.09674729406833649,
0.0805174708366394,
-0.12323319911956787,
0.010715009644627571,
0.05349363759160042,
-0.03988219052553177,
0.0202535018324852,
-0.059816449880599976,
-0.10161319375038147,
-0.1043306216597557,
0.018151631578803062,
-0.09854824841022491,
-0.1628563553094864,
0.055515728890895844,
-0.16026504337787628,
0.013065204955637455,
0.09730850905179977,
0.09125160425901413,
-0.06072191521525383,
0.08300750702619553,
-0.015433529391884804,
-0.08634582161903381,
0.11416357755661011,
-0.07150305062532425,
0.0684824138879776,
-0.07353810220956802,
-0.0770263597369194,
-0.038602616637945175,
0.020934659987688065,
-0.015472078695893288,
0.060100290924310684,
0.011888442561030388,
0.007401375100016594,
-0.0017041057581081986,
0.016607603058218956,
-0.07031766325235367,
0.03289205580949783,
0.020752910524606705,
-0.017372991889715195,
0.06585422158241272,
-0.09060325473546982,
-0.0017371389549225569,
0.199083149433136,
-0.034210532903671265,
-0.12648805975914001,
-0.14251382648944855,
0.16234958171844482,
-0.06460773199796677,
-0.028041698038578033,
0.05141095444560051,
-0.01640254072844982,
-0.08304009586572647,
0.2265956550836563,
0.12476042658090591,
-0.08638826757669449,
-0.053193774074316025,
-0.03448730707168579,
-0.023137865588068962,
-0.023840073496103287,
0.18448704481124878,
0.059385884553194046,
0.13597732782363892,
0.0015099103329703212,
0.006275323685258627,
-0.042251456528902054,
-0.005366278346627951,
-0.08560876548290253,
0.022111525759100914,
0.019637277349829674,
-0.0896262377500534,
-0.006690440699458122,
0.08547190576791763,
-0.10976199060678482,
-0.059373725205659866,
-0.07884608209133148,
-0.04518502950668335,
-0.1683049350976944,
0.011064188554883003,
0.017875419929623604,
-0.004598966799676418,
0.05115705356001854,
-0.07288163155317307,
0.054077763110399246,
0.0210662130266428,
0.013269635848701,
0.04062887281179428,
-0.005322896409779787,
0.05761228874325752,
0.029926275834441185,
0.07714290916919708,
0.03237808495759964,
0.16057884693145752,
0.05764472857117653,
-0.012789681553840637,
-0.0754072442650795,
0.07809939235448837,
0.08032318204641342,
-0.05141482874751091,
0.07224463671445847,
0.06779474765062332,
-0.048386383801698685,
0.09262176603078842,
0.04699452221393585,
-0.026584936305880547,
0.0189441479742527,
0.07767580449581146,
0.0385531485080719,
-0.15665268898010254,
0.035386040806770325,
-0.1366211324930191,
0.14381375908851624,
0.1477980762720108,
-0.061965327709913254,
-0.012594149447977543,
-0.04402017965912819,
0.10231245309114456,
-0.044843610376119614,
0.0651451051235199,
-0.046127695590257645,
-0.14545536041259766,
0.0028334297239780426,
0.09349286556243896,
0.09413060545921326,
-0.08851952850818634,
0.01765754260122776,
-0.07662405073642731,
-0.01134193129837513,
-0.021903440356254578,
0.0476602204144001,
0.0744481086730957,
-0.016757821664214134,
-0.000915137876290828,
-0.14306800067424774,
-0.024587025865912437,
0.021768420934677124,
-0.08974158763885498,
-0.0792936310172081
] |
null | null | transformers | ## G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German
This model developed a contextualized German Science Education BERT (G-SciEdBERT),
an innovative large language model tailored for scoring German-written responses to science tasks.
Using G-BERT, we pre-trained G-SciEdBERT on a corpus of 50K German written science responses with 5M tokens to the Programme for International Student Assessment (PISA) 2015.
We fine-tuned G-SciEdBERT on 59 assessment items and examined the scoring accuracy. We then compared its performance with G-BERT.
Our findings reveal a substantial improvement in scoring accuracy with G-SciEdBERT, demonstrating a 10% increase of quadratic weighted kappa compared to G-BERT
(mean accuracy difference = 0.096, SD = 0.024). These insights underline the significance of specialized language models like G-SciEdBERT,
which is trained to enhance the accuracy of automated scoring, offering a substantial contribution to the field of AI in education.
## Dataset
It is a pre-trained German science education BERT for written German science assessments of the PISA test.
PISA is an international test to monitor education trends led by OECD (Organisation for Economic Co-operation and Development).
PISA items are developed to assess scientific literacy, highlighting real-world problem-solving skills and the needs of future workforce.
This study analyzed data collected for 59 construct response science assessment items in German at the middle school level.
A total of 6,116 German students from 257 schools participated in PISA 2015.
Given the geographical diversity of participants, PISA data reflect the general German students' science literacy.
The PISA items selected require either short (around one sentence) or extended (up to five sentences) responses.
The minimum score for all items is 0, with the maximum being 3 or 4 for short responses and 4 or 5 for extended responses.
Student responses have 20 words on average. Our pre-training dataset contains more than 50,000 student-written German responses,
which means approximately 1,000 human-scored student responses per item for contextual learning through fine-tuning.
More than 10 human raters scored each response in the training dataset organized by OECD.
The responses were graded irrespective of the student's ethnicity, race, or gender to ensure fairness.
## Architecture
The model is pre-trained on [G-BERT](https://huggingface.co/dbmdz/bert-base-german-uncased?text=Ich+mag+dich.+Ich+liebe+%5BMASK%5D) and the pre-trainig method can be seen as:
## Evaluation Results
The table below compares the outcomes between G-BERT and G-SciEdBERT for randomly picked five PISA assessment items and the average accuracy (QWK)
reported for all datasets combined. It shows that G-SciEdBERT significantly outperformed G-BERT on automatic scoring of student written responses.
Based on the QWK values, the percentage differences in accuracy vary from 4.2% to 13.6%, with an average increase of 10.0% in average (from .7136 to .8137).
Especially for item S268Q02, which saw the largest improvement at 13.6% (from .761 to .852), this improvement is noteworthy.
These findings demonstrate that G-SciEdBERT is more effective than G-BERT at comprehending and assessing complex science-related writings.
The results of our analysis strongly support the adoption of G-SciEdBERT for the automatic scoring of German-written science responses in large-scale
assessments such as PISA, given its superior accuracy over the general-purpose G-BERT model.
| Item | Training Samples | Testing Samples | Labels | G-BERT | G-SciEdBERT |
|---------|------------------|-----------------|--------------|--------|-------------|
| S131Q02 | 487 | 122 | 5 | 0.761 | **0.852** |
| S131Q04 | 478 | 120 | 5 | 0.683 | **0.725** |
| S268Q02 | 446 | 112 | 2 | 0.757 | **0.893** |
| S269Q01 | 508 | 127 | 2 | 0.837 | **0.953** |
| S269Q03 | 500 | 126 | 4 | 0.702 | **0.802** |
| Average | 665.95 | 166.49 | 2-5 (min-max) | 0.7136 | **0.8137** |
## Usage
With Transformers >= 2.3 our German BERT models can be loaded like this:
```python
from transformers import AutoModel, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("ai4stem-uga/G-SciEdBERT")
model = AutoModel.from_pretrained("ai4stem-uga/G-SciEdBERT")
```
# Acknowledgments
This project is supported by the Alexender von Humboldt Foundation (PI Xiaoming Zhai, [email protected]).
## Citation
```bibtex
@InProceedings{Latif_2024_G-SciEdBERT,
author = {Latif, Ehsan and Lee, Gyeong-Geon and Neuman, Knut and Kastorff, Tamara and Zhai, Xiaoming},
title = {G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German},
journal = {arXiv preprint arXiv:2301.12031},
year = {2024}
pages = {1-9}
}
```
*This model is trained and shared by Ehsan Latif, Ph.D ([email protected]) | {"language": ["de"], "license": "mit", "library_name": "transformers", "tags": ["Science"], "metrics": ["accuracy"], "pipeline_tag": "text-classification"} | text-classification | ai4stem-uga/G-SciEdBERT | [
"transformers",
"safetensors",
"bert",
"fill-mask",
"Science",
"text-classification",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T04:52:49+00:00 | [] | [
"de"
] | TAGS
#transformers #safetensors #bert #fill-mask #Science #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us
| G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German
------------------------------------------------------------------------
This model developed a contextualized German Science Education BERT (G-SciEdBERT),
an innovative large language model tailored for scoring German-written responses to science tasks.
Using G-BERT, we pre-trained G-SciEdBERT on a corpus of 50K German written science responses with 5M tokens to the Programme for International Student Assessment (PISA) 2015.
We fine-tuned G-SciEdBERT on 59 assessment items and examined the scoring accuracy. We then compared its performance with G-BERT.
Our findings reveal a substantial improvement in scoring accuracy with G-SciEdBERT, demonstrating a 10% increase of quadratic weighted kappa compared to G-BERT
(mean accuracy difference = 0.096, SD = 0.024). These insights underline the significance of specialized language models like G-SciEdBERT,
which is trained to enhance the accuracy of automated scoring, offering a substantial contribution to the field of AI in education.
Dataset
-------
It is a pre-trained German science education BERT for written German science assessments of the PISA test.
PISA is an international test to monitor education trends led by OECD (Organisation for Economic Co-operation and Development).
PISA items are developed to assess scientific literacy, highlighting real-world problem-solving skills and the needs of future workforce.
This study analyzed data collected for 59 construct response science assessment items in German at the middle school level.
A total of 6,116 German students from 257 schools participated in PISA 2015.
Given the geographical diversity of participants, PISA data reflect the general German students' science literacy.
The PISA items selected require either short (around one sentence) or extended (up to five sentences) responses.
The minimum score for all items is 0, with the maximum being 3 or 4 for short responses and 4 or 5 for extended responses.
Student responses have 20 words on average. Our pre-training dataset contains more than 50,000 student-written German responses,
which means approximately 1,000 human-scored student responses per item for contextual learning through fine-tuning.
More than 10 human raters scored each response in the training dataset organized by OECD.
The responses were graded irrespective of the student's ethnicity, race, or gender to ensure fairness.
Architecture
------------
The model is pre-trained on G-BERT and the pre-trainig method can be seen as:
!architecture
Evaluation Results
------------------
The table below compares the outcomes between G-BERT and G-SciEdBERT for randomly picked five PISA assessment items and the average accuracy (QWK)
reported for all datasets combined. It shows that G-SciEdBERT significantly outperformed G-BERT on automatic scoring of student written responses.
Based on the QWK values, the percentage differences in accuracy vary from 4.2% to 13.6%, with an average increase of 10.0% in average (from .7136 to .8137).
Especially for item S268Q02, which saw the largest improvement at 13.6% (from .761 to .852), this improvement is noteworthy.
These findings demonstrate that G-SciEdBERT is more effective than G-BERT at comprehending and assessing complex science-related writings.
The results of our analysis strongly support the adoption of G-SciEdBERT for the automatic scoring of German-written science responses in large-scale
assessments such as PISA, given its superior accuracy over the general-purpose G-BERT model.
Usage
-----
With Transformers >= 2.3 our German BERT models can be loaded like this:
Acknowledgments
===============
This project is supported by the Alexender von Humboldt Foundation (PI Xiaoming Zhai, URL@URL).
\*This model is trained and shared by Ehsan Latif, Ph.D (URL@URL)
| [] | [
"TAGS\n#transformers #safetensors #bert #fill-mask #Science #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us \n"
] | [
51
] | [
"passage: TAGS\n#transformers #safetensors #bert #fill-mask #Science #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us \n"
] | [
0.008027449250221252,
0.0584193617105484,
-0.0062279184348881245,
-0.021521855145692825,
0.08351507782936096,
0.025674041360616684,
0.17150896787643433,
0.09411556273698807,
0.13062120974063873,
-0.030856706202030182,
0.18219713866710663,
0.17979486286640167,
-0.026651885360479355,
0.19012761116027832,
-0.1143655851483345,
-0.24485796689987183,
0.10688406229019165,
-0.021488675847649574,
-0.009786565788090229,
0.08122812956571579,
0.09374265372753143,
-0.07302995026111603,
0.051279257982969284,
-0.05962010845541954,
-0.009557057172060013,
-0.005873154848814011,
0.1045902669429779,
-0.1464214324951172,
0.15494294464588165,
0.028715983033180237,
0.1850363314151764,
0.07298566401004791,
-0.03502175956964493,
-0.18965519964694977,
0.045774396508932114,
-0.014217475429177284,
-0.09286104887723923,
0.0740007758140564,
-0.012769998051226139,
-0.05238340049982071,
0.03609892353415489,
-0.011731944046914577,
0.05874915048480034,
0.103996641933918,
-0.16183410584926605,
-0.12394355982542038,
-0.026519399136304855,
-0.0346437469124794,
0.01976315677165985,
0.02162216790020466,
0.01228745374828577,
0.1519847810268402,
-0.05471602454781532,
0.08220281451940536,
0.07863575965166092,
-0.31387075781822205,
0.006371511612087488,
0.1078641265630722,
0.12645868957042694,
0.03250054270029068,
-0.06638175249099731,
0.130232572555542,
0.0712595209479332,
-0.03632790222764015,
0.07353458553552628,
-0.055141206830739975,
0.011068488471210003,
0.018388457596302032,
-0.06627227365970612,
-0.010676278732717037,
0.16380751132965088,
-0.05286634340882301,
-0.009197888895869255,
-0.08027255535125732,
-0.0843144953250885,
-0.012801521457731724,
-0.023028334602713585,
-0.01412867195904255,
0.028026333078742027,
0.05876107141375542,
0.04241737723350525,
0.028644392266869545,
-0.12499956786632538,
0.02389226108789444,
-0.188015416264534,
0.24650369584560394,
-0.01724928431212902,
0.052566368132829666,
-0.14489540457725525,
-0.0007666274905204773,
0.001719469903036952,
-0.11886604130268097,
-0.003237574128434062,
-0.10536070913076401,
0.05383965000510216,
-0.04208758473396301,
-0.04521457478404045,
-0.02697581984102726,
0.14333970844745636,
0.20212405920028687,
-0.02199610136449337,
0.04430406913161278,
-0.032282061874866486,
0.0895843505859375,
0.0437035858631134,
0.053920432925224304,
0.06654153019189835,
-0.023700127378106117,
0.06130572408437729,
-0.10790141671895981,
0.04443908855319023,
-0.07161359488964081,
-0.09801976382732391,
-0.02060476504266262,
0.008652412332594395,
0.1124303787946701,
0.01583235338330269,
0.05072223022580147,
-0.06521295756101608,
0.0703829750418663,
0.08744706213474274,
-0.04886132478713989,
0.0005133989034220576,
0.030514197424054146,
0.107540562748909,
0.01735423505306244,
0.007549846079200506,
0.00945432111620903,
0.0660538449883461,
0.09705428034067154,
-0.09407022595405579,
-0.05944221839308739,
-0.04694991186261177,
-0.09597203880548477,
0.05191653594374657,
-0.05811609700322151,
0.06941862404346466,
-0.18113265931606293,
-0.10363955050706863,
0.017704343423247337,
0.0635637566447258,
-0.014163990505039692,
0.027896078303456306,
0.028412438929080963,
-0.017930470407009125,
0.057295650243759155,
-0.041973430663347244,
-0.11025653034448624,
-0.09683900326490402,
0.08354734629392624,
-0.06428509950637817,
0.09661712497472763,
-0.1884731650352478,
0.0005163067253306508,
-0.09755207598209381,
0.0445474274456501,
-0.10820948332548141,
-0.050249211490154266,
-0.1020619124174118,
0.16800372302532196,
-0.016147950664162636,
-0.03783966973423958,
-0.054796066135168076,
0.04922918230295181,
-0.02566155605018139,
0.18034882843494415,
-0.12335635721683502,
-0.06367827206850052,
0.19508439302444458,
-0.11400525271892548,
-0.20722083747386932,
0.09142401069402695,
-0.04552081227302551,
0.10659389197826385,
0.0868266224861145,
0.1774606704711914,
0.038122013211250305,
-0.1181458905339241,
0.04684529826045036,
0.10796606540679932,
-0.0756043940782547,
-0.05112481489777565,
0.03082749992609024,
0.03521069884300232,
-0.1395450234413147,
0.019349971786141396,
0.07560216635465622,
0.06216100603342056,
-0.050961729139089584,
-0.0710071250796318,
-0.022109363228082657,
-0.008110425435006618,
0.11175572872161865,
-0.01267646811902523,
0.07286789268255234,
-0.15691639482975006,
0.008742330595850945,
-0.023875566199421883,
-0.02780243754386902,
0.030106045305728912,
0.016731178387999535,
-0.08529631793498993,
0.05020783096551895,
0.02689397521317005,
0.020528284832835197,
-0.11943633109331131,
-0.13261941075325012,
0.0018112898105755448,
0.025093022733926773,
-0.0018141118343919516,
0.09113167226314545,
0.0518939308822155,
-0.014234158210456371,
-0.029926171526312828,
-0.011860538274049759,
0.12912680208683014,
0.06834515929222107,
-0.0407995879650116,
-0.14045025408267975,
0.09826911240816116,
-0.07452992349863052,
-0.0170650165528059,
-0.08859539031982422,
0.044276162981987,
0.05944010615348816,
0.04811367392539978,
0.013047249987721443,
0.06418763101100922,
-0.04466957971453667,
0.01400124840438366,
-0.05936285853385925,
0.019134849309921265,
0.08912152051925659,
-0.01280660554766655,
-0.13383692502975464,
0.13767091929912567,
-0.1481451690196991,
0.341810941696167,
0.18165187537670135,
-0.2218010425567627,
-0.025466598570346832,
-0.009887030348181725,
-0.004466783255338669,
0.03941997513175011,
0.004033640958368778,
-0.004847164731472731,
-0.009255185723304749,
-0.012500427663326263,
0.11551966518163681,
-0.03559252247214317,
-0.010405264794826508,
0.01078162994235754,
-0.07126616686582565,
-0.06674576550722122,
0.052266448736190796,
0.06905993819236755,
-0.25130999088287354,
0.1758711040019989,
0.2973836362361908,
0.07296139001846313,
0.16641978919506073,
-0.01043193880468607,
0.025275560095906258,
0.031290777027606964,
-0.07154190540313721,
-0.0005460779648274183,
0.06612637639045715,
-0.10505568981170654,
-0.006431960966438055,
0.08168613165616989,
-0.010511983186006546,
0.025901587679982185,
-0.12637819349765778,
-0.06635566055774689,
0.013020160607993603,
0.03776108846068382,
-0.11168509721755981,
0.08611465990543365,
-0.03405417501926422,
0.12951354682445526,
-0.01134923379868269,
-0.09481044858694077,
0.09891153872013092,
-0.01508333720266819,
-0.10689355432987213,
0.20123310387134552,
-0.11446978896856308,
-0.2766004204750061,
-0.17380225658416748,
-0.13386918604373932,
0.05292407423257828,
0.07213205844163895,
0.07723578810691833,
-0.05723871663212776,
-0.09252038598060608,
0.007174080237746239,
-0.062200918793678284,
0.0006237967172637582,
0.052968580275774,
-0.050835639238357544,
0.08294208347797394,
-0.024697326123714447,
-0.08555679023265839,
-0.08024436980485916,
0.01652660220861435,
0.039793990552425385,
0.15907613933086395,
-0.07465711236000061,
0.1015213206410408,
0.09981949627399445,
-0.05349728465080261,
-0.027059001848101616,
-0.05916706100106239,
0.20959733426570892,
-0.11295145004987717,
0.011044628918170929,
0.16163606941699982,
-0.05234820023179054,
0.049627285450696945,
0.2118244618177414,
0.05570691451430321,
-0.09199591726064682,
0.05684465542435646,
-0.0880519449710846,
-0.11121253669261932,
-0.27259689569473267,
-0.09344513714313507,
-0.06773696839809418,
0.07618312537670135,
0.003518254728987813,
0.04652939736843109,
0.16454000771045685,
0.08873733133077621,
0.017682284116744995,
-0.040154214948415756,
0.026049891486763954,
0.08216492831707001,
0.18506747484207153,
-0.028499601408839226,
0.1488867551088333,
-0.06774922460317612,
-0.1052926704287529,
0.05907231196761131,
0.02327996864914894,
0.05573710426688194,
0.2119131237268448,
0.06964153051376343,
0.04270991310477257,
-0.0019384167389944196,
0.14318430423736572,
0.1614004671573639,
0.07696419954299927,
-0.05737673491239548,
-0.035355109721422195,
-0.020381083711981773,
-0.058419790118932724,
0.09289964288473129,
-0.04960327222943306,
-0.11307736486196518,
-0.0317886620759964,
-0.1186186671257019,
0.09363233298063278,
0.052876342087984085,
0.06041331589221954,
-0.17818352580070496,
-0.03307555988430977,
0.15958723425865173,
0.00047389959217980504,
-0.086715467274189,
0.0935312956571579,
0.02266737073659897,
-0.08352412283420563,
0.11489109694957733,
-0.020322160795331,
0.07216159999370575,
0.08052750676870346,
0.10459104925394058,
-0.06367187201976776,
-0.17272698879241943,
-0.017507562413811684,
0.08039408922195435,
-0.296528160572052,
0.27488866448402405,
0.0029113146010786295,
-0.02455766126513481,
-0.04938851296901703,
-0.022622739896178246,
0.0324552096426487,
0.2385861873626709,
0.17799904942512512,
-0.0026410508435219526,
-0.19382481276988983,
-0.1001887321472168,
-0.01961476169526577,
0.03021448291838169,
0.10437005758285522,
-0.012787516228854656,
0.004033777397125959,
-0.043216463178396225,
-0.010622702538967133,
0.010126696899533272,
0.03739184886217117,
-0.07273218780755997,
-0.10160943865776062,
0.06427467614412308,
0.033766284584999084,
0.08641378581523895,
-0.03666026517748833,
-0.04383707046508789,
-0.14327296614646912,
0.15745894610881805,
-0.14059922099113464,
-0.05568595230579376,
-0.11492893844842911,
-0.13716527819633484,
0.028065405786037445,
-0.047088686376810074,
0.07525435090065002,
-0.0414273776113987,
0.021536942571401596,
-0.09884114563465118,
-0.1783503293991089,
0.19129645824432373,
-0.1267106533050537,
-0.08080971240997314,
-0.1067168116569519,
0.091006338596344,
-0.07578817009925842,
0.06933167576789856,
0.029370637610554695,
0.06389901041984558,
-0.07962804287672043,
-0.08453559875488281,
0.05565560236573219,
-0.06128744035959244,
0.04234592989087105,
-0.00862567313015461,
-0.12734347581863403,
-0.13636407256126404,
0.014133618213236332,
-0.013724214397370815,
0.213974729180336,
0.3359299600124359,
-0.048334456980228424,
0.15387386083602905,
0.20614342391490936,
-0.07563740760087967,
-0.37143388390541077,
-0.05097278952598572,
-0.20713937282562256,
-0.029706764966249466,
0.01582436077296734,
-0.1254541128873825,
0.09038935601711273,
0.015636375173926353,
-0.0799034982919693,
0.09062755852937698,
-0.06651628762483597,
-0.13474951684474945,
0.20029711723327637,
0.033422473818063736,
0.3992924094200134,
-0.18396992981433868,
-0.0681871548295021,
-0.1362954080104828,
-0.10248380154371262,
0.15265031158924103,
-0.08892250806093216,
0.06301752477884293,
0.0026019271463155746,
-0.020532192662358284,
0.0009038009447976947,
-0.08277302980422974,
0.15984202921390533,
-0.0892365351319313,
0.05479986593127251,
-0.07915844768285751,
-0.09147754311561584,
0.08359245210886002,
0.020051967352628708,
0.013360075652599335,
-0.04009106755256653,
0.00038122860132716596,
-0.009621825069189072,
-0.027434032410383224,
-0.04188118875026703,
0.11113905161619186,
-0.013965374790132046,
-0.11599214375019073,
-0.04339141026139259,
0.010192635469138622,
0.005329045467078686,
-0.028273995965719223,
0.3131045997142792,
-0.07222719490528107,
0.19879114627838135,
0.06107184663414955,
0.17353832721710205,
-0.12465735524892807,
0.12031343579292297,
0.012573805637657642,
-0.10453221946954727,
0.061253756284713745,
-0.11242230236530304,
0.034429922699928284,
0.09542763978242874,
-0.05015737935900688,
0.0767037570476532,
0.12603417038917542,
0.03866775333881378,
-0.010120078921318054,
0.14929242432117462,
-0.20973564684391022,
-0.06994130462408066,
-0.011908364482223988,
0.04319848492741585,
0.031236547976732254,
0.072115957736969,
0.12300385534763336,
0.0020357337780296803,
-0.027846723794937134,
-0.027003711089491844,
0.038372114300727844,
-0.04260243475437164,
0.05060547962784767,
0.08666261285543442,
0.04280688986182213,
-0.08399364352226257,
-0.01978672482073307,
0.0023733084090054035,
-0.13190826773643494,
0.0018874184461310506,
0.0610971674323082,
-0.1013575866818428,
-0.10908395797014236,
-0.02194143272936344,
0.09458839893341064,
-0.0930773988366127,
-0.07451068609952927,
-0.07106012105941772,
-0.18266178667545319,
0.023767024278640747,
0.30082008242607117,
0.0841161236166954,
0.06985297799110413,
-0.00225120154209435,
-0.03900846838951111,
0.056040287017822266,
0.022705210372805595,
-0.13810424506664276,
0.05504615977406502,
-0.06245201453566551,
0.01699742116034031,
-0.07645803689956665,
0.0616888701915741,
-0.12524409592151642,
0.007135157473385334,
-0.1967763602733612,
-0.004538957495242357,
-0.07134122401475906,
-0.0032628411427140236,
-0.07288290560245514,
-0.04698255658149719,
0.009426348842680454,
-0.06996150314807892,
-0.040504906326532364,
-0.059636782854795456,
-0.10396425426006317,
0.023772262036800385,
0.005662160459905863,
0.07416534423828125,
-0.08211105316877365,
-0.04283446446061134,
0.11804281920194626,
-0.04938225448131561,
0.07688266038894653,
0.0472942553460598,
-0.04482370242476463,
0.07547829300165176,
-0.25798776745796204,
-0.03961896523833275,
0.11919726431369781,
0.015951763838529587,
0.017639663070440292,
-0.01836433634161949,
-0.015042444691061974,
0.05915416032075882,
-0.0005701431073248386,
0.08829226344823837,
-0.00876880344003439,
-0.08429063111543655,
0.040238797664642334,
-0.000898705271538347,
-0.15836885571479797,
0.008163750171661377,
-0.12162745743989944,
0.09864228218793869,
-0.08051947504281998,
0.16777145862579346,
-0.06597651541233063,
0.028901508077979088,
-0.06603274494409561,
0.04068167135119438,
-0.005788228940218687,
-0.18226350843906403,
-0.10201575607061386,
-0.07884770631790161,
-0.004763610661029816,
-0.01656295172870159,
0.29738306999206543,
0.022374983876943588,
-0.04159734770655632,
0.10555337369441986,
0.06071971729397774,
0.017960431054234505,
0.07597526162862778,
0.2660529315471649,
0.08462110161781311,
-0.049293402582407,
-0.11585190147161484,
0.03320794552564621,
0.02157861553132534,
-0.0965149849653244,
0.14579561352729797,
0.12480460852384567,
-0.05124993249773979,
0.0840083584189415,
-0.018654877319931984,
0.05565354600548744,
-0.03403399884700775,
-0.11329922080039978,
-0.005730758421123028,
0.011098713614046574,
0.019943589344620705,
0.01860537938773632,
0.15838561952114105,
-0.08356472104787827,
0.032954100519418716,
-0.09145661443471909,
-0.036420997232198715,
-0.2004496455192566,
-0.04718828201293945,
-0.0984918475151062,
-0.02966405265033245,
0.013936380855739117,
-0.08017443120479584,
-0.03274175524711609,
0.02896115370094776,
0.043544430285692215,
-0.04469311609864235,
0.10282383114099503,
-0.0692053735256195,
0.03143451735377312,
0.03897257149219513,
0.008953052572906017,
0.02219434641301632,
-0.0717206597328186,
-0.0740615501999855,
-0.11776813864707947,
-0.017086004838347435,
-0.0562472939491272,
0.020785154774785042,
-0.05558919534087181,
0.009463837370276451,
-0.10871043056249619,
-0.10780809074640274,
-0.04219897463917732,
0.04350961372256279,
-0.04035067930817604,
0.09583888202905655,
0.006933656521141529,
0.019391346722841263,
0.09087862819433212,
0.16264542937278748,
-0.03476546332240105,
-0.09083375334739685,
-0.03841104358434677,
0.21097297966480255,
0.03496459871530533,
0.1416316032409668,
-0.023723334074020386,
-0.007306064944714308,
-0.04690701141953468,
0.22011038661003113,
0.29547402262687683,
-0.0649961605668068,
0.06312350183725357,
-0.015939420089125633,
0.037783119827508926,
0.10010876506567001,
0.14926914870738983,
0.0570315457880497,
0.19941549003124237,
-0.07391124218702316,
-0.022915882989764214,
-0.01785414107143879,
-0.019168773666024208,
-0.11193503439426422,
0.06754907965660095,
0.03395141288638115,
-0.045210205018520355,
-0.06262354552745819,
0.10646896064281464,
-0.1265367567539215,
0.057825930416584015,
0.02691481076180935,
-0.1847505122423172,
-0.024837268516421318,
-0.02265128865838051,
0.13289089500904083,
-0.05160841345787048,
0.06443808227777481,
-0.030208256095647812,
-0.0881449431180954,
-0.016472818329930305,
0.028175048530101776,
-0.14656732976436615,
0.03012712672352791,
0.06966671347618103,
-0.01675448939204216,
0.15886825323104858,
0.011614791117608547,
0.043270159512758255,
0.08955240249633789,
0.0046804905869066715,
-0.020147252827882767,
0.11270394176244736,
0.04721668362617493,
-0.04372960701584816,
-0.0028619312215596437,
-0.009735151194036007,
-0.000026712634280556813,
-0.05433421581983566,
0.09216395020484924,
-0.15651117265224457,
0.06981925666332245,
-0.039509523659944534,
-0.15319685637950897,
-0.015634313225746155,
0.08162657916545868,
-0.0836251750588417,
0.06552617996931076,
0.03208652883768082,
-0.008365045301616192,
-0.011523973196744919,
-0.03349579498171806,
0.0011173657840117812,
0.04289637878537178,
-0.14685627818107605,
-0.0891580805182457,
-0.09075985848903656,
-0.0432417131960392,
0.060333576053380966,
0.036479394882917404,
-0.24918551743030548,
-0.016438713297247887,
-0.12312301993370056,
0.10030651837587357,
-0.16740812361240387,
0.015175988897681236,
0.08739731460809708,
-0.013024689629673958,
-0.01878262497484684,
-0.14279775321483612,
0.05608732998371124,
0.05249975249171257,
-0.05926375836133957,
-0.09987760335206985
] |
null | null | peft |
# Model Card for Model ID
The model is a variant of Llama-2 finetuned on Intel Cloud with a dataset of 120k pubmed articles to best summarize each article.
## Model Details
### Model Description
- **Developed by:** Infogenesis
- **Funded by [optional]:** Hacklytics 2024, Intel
- **Model type:** Large Language Model
- **Language(s) (NLP):** English
- **License:** Apache 2.0
- **Finetuned from model [optional]:** Llama-2-7b-chat-hf
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/ShivanshSharma04/HacklyticsProject
## Uses
This model is fine-tuned on the summarization and analysis of schoarly medical articles, and as such, it should primarily be used for the summarization and analysis of said models.
### Direct Use
This model is intended solely for the summarization and analysis of schoarly medical articles.
Here is the code to run the model directly:
```
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
peft_model_id = "AndyYu25/hacklytics24-medsummarizer"
model_id = "NousResearch/Llama-2-7b-chat-hf"
model = AutoModelForCausalLM.from_pretrained(model_id)
model.load_adapter(peft_model_id)
pipe = pipeline(task="text-generation", model=model)
result = pipe(f"<s>[INST] PROMPT [/INST]")
print(result)
```
### Downstream Use [optional]
Fine-tuned variations of this model can probably be extrapolated to parse non-medical scholarly articles and perform a broader set of tasks that merely summarization.
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
The model, regardless of finetuning, should not be used to generate medical advice without Prediction Guard API, as it may hallucinate false medical information, something can be detrimental to the health of anyone that makes medical decisions based on the model.
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
The model has not been fine-tuned outside the scope of medical journals published in the United States, so it may have an American-centric slant when interpreting or summarizing articles.
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
The model can be implemented the same way as Llama-2
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
The AI was trained on 120,000 open-access PubMed articles provided by the National Institute of Health. Information about accessing the API for PubMed can be found here: https://www.ncbi.nlm.nih.gov/books/NBK25499/
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
Each paper in the dataset was split into the main body and the abstract, where the abstract would be a hypothetical summary that the model was asked to create.
#### Training Hyperparameters
- **Training regime:** fp16
Learning rate: 2e-4
Batch size: 4
## Evaluation
Evaluation was based on a 80-10-10 train-test-validate split.
### Testing Data, Factors & Metrics
#### Testing Data
The testing data was a randomly selected sample of ~12,000 articles from the general dataset.
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** Intel Max Series GPU (4 GPUs with 4th Gen CPU, 2 sockets, 256 GB memory, 2 TB disk with OneAPI base kit and tooling)
- **Hours used:** 1 hour
- **Cloud Provider:** Intel
- **Compute Region:** us-region-1
- **Carbon Emitted:** <0.1 kg CO2
## Model Card Contact
[email protected]
### Framework versions
- PEFT 0.8.2 | {"library_name": "peft", "base_model": "NousResearch/Llama-2-7b-chat-hf"} | null | AndyYu25/hacklytics24-medsummarizer | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:NousResearch/Llama-2-7b-chat-hf",
"region:us"
] | 2024-02-11T04:54:21+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #safetensors #arxiv-1910.09700 #base_model-NousResearch/Llama-2-7b-chat-hf #region-us
|
# Model Card for Model ID
The model is a variant of Llama-2 finetuned on Intel Cloud with a dataset of 120k pubmed articles to best summarize each article.
## Model Details
### Model Description
- Developed by: Infogenesis
- Funded by [optional]: Hacklytics 2024, Intel
- Model type: Large Language Model
- Language(s) (NLP): English
- License: Apache 2.0
- Finetuned from model [optional]: Llama-2-7b-chat-hf
### Model Sources [optional]
- Repository: URL
## Uses
This model is fine-tuned on the summarization and analysis of schoarly medical articles, and as such, it should primarily be used for the summarization and analysis of said models.
### Direct Use
This model is intended solely for the summarization and analysis of schoarly medical articles.
Here is the code to run the model directly:
### Downstream Use [optional]
Fine-tuned variations of this model can probably be extrapolated to parse non-medical scholarly articles and perform a broader set of tasks that merely summarization.
### Out-of-Scope Use
The model, regardless of finetuning, should not be used to generate medical advice without Prediction Guard API, as it may hallucinate false medical information, something can be detrimental to the health of anyone that makes medical decisions based on the model.
## Bias, Risks, and Limitations
The model has not been fine-tuned outside the scope of medical journals published in the United States, so it may have an American-centric slant when interpreting or summarizing articles.
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
The model can be implemented the same way as Llama-2
## Training Details
### Training Data
The AI was trained on 120,000 open-access PubMed articles provided by the National Institute of Health. Information about accessing the API for PubMed can be found here: URL
### Training Procedure
#### Preprocessing [optional]
Each paper in the dataset was split into the main body and the abstract, where the abstract would be a hypothetical summary that the model was asked to create.
#### Training Hyperparameters
- Training regime: fp16
Learning rate: 2e-4
Batch size: 4
## Evaluation
Evaluation was based on a 80-10-10 train-test-validate split.
### Testing Data, Factors & Metrics
#### Testing Data
The testing data was a randomly selected sample of ~12,000 articles from the general dataset.
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: Intel Max Series GPU (4 GPUs with 4th Gen CPU, 2 sockets, 256 GB memory, 2 TB disk with OneAPI base kit and tooling)
- Hours used: 1 hour
- Cloud Provider: Intel
- Compute Region: us-region-1
- Carbon Emitted: <0.1 kg CO2
## Model Card Contact
ayu303@URL
### Framework versions
- PEFT 0.8.2 | [
"# Model Card for Model ID\n\nThe model is a variant of Llama-2 finetuned on Intel Cloud with a dataset of 120k pubmed articles to best summarize each article.",
"## Model Details",
"### Model Description\n\n\n- Developed by: Infogenesis\n- Funded by [optional]: Hacklytics 2024, Intel\n- Model type: Large Language Model\n- Language(s) (NLP): English\n- License: Apache 2.0\n- Finetuned from model [optional]: Llama-2-7b-chat-hf",
"### Model Sources [optional]\n\n\n\n- Repository: URL",
"## Uses\n\nThis model is fine-tuned on the summarization and analysis of schoarly medical articles, and as such, it should primarily be used for the summarization and analysis of said models.",
"### Direct Use\n\n\nThis model is intended solely for the summarization and analysis of schoarly medical articles. \n\nHere is the code to run the model directly:",
"### Downstream Use [optional]\n\nFine-tuned variations of this model can probably be extrapolated to parse non-medical scholarly articles and perform a broader set of tasks that merely summarization.",
"### Out-of-Scope Use\n\n\n\nThe model, regardless of finetuning, should not be used to generate medical advice without Prediction Guard API, as it may hallucinate false medical information, something can be detrimental to the health of anyone that makes medical decisions based on the model.",
"## Bias, Risks, and Limitations\n\n\n\nThe model has not been fine-tuned outside the scope of medical journals published in the United States, so it may have an American-centric slant when interpreting or summarizing articles.",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nThe model can be implemented the same way as Llama-2",
"## Training Details",
"### Training Data\n\n\n\nThe AI was trained on 120,000 open-access PubMed articles provided by the National Institute of Health. Information about accessing the API for PubMed can be found here: URL",
"### Training Procedure",
"#### Preprocessing [optional]\n\nEach paper in the dataset was split into the main body and the abstract, where the abstract would be a hypothetical summary that the model was asked to create.",
"#### Training Hyperparameters\n\n- Training regime: fp16\n\nLearning rate: 2e-4\nBatch size: 4",
"## Evaluation\n\nEvaluation was based on a 80-10-10 train-test-validate split.",
"### Testing Data, Factors & Metrics",
"#### Testing Data\n\nThe testing data was a randomly selected sample of ~12,000 articles from the general dataset.",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: Intel Max Series GPU (4 GPUs with 4th Gen CPU, 2 sockets, 256 GB memory, 2 TB disk with OneAPI base kit and tooling)\n- Hours used: 1 hour\n- Cloud Provider: Intel\n- Compute Region: us-region-1\n- Carbon Emitted: <0.1 kg CO2",
"## Model Card Contact\n\nayu303@URL",
"### Framework versions\n\n- PEFT 0.8.2"
] | [
"TAGS\n#peft #safetensors #arxiv-1910.09700 #base_model-NousResearch/Llama-2-7b-chat-hf #region-us \n",
"# Model Card for Model ID\n\nThe model is a variant of Llama-2 finetuned on Intel Cloud with a dataset of 120k pubmed articles to best summarize each article.",
"## Model Details",
"### Model Description\n\n\n- Developed by: Infogenesis\n- Funded by [optional]: Hacklytics 2024, Intel\n- Model type: Large Language Model\n- Language(s) (NLP): English\n- License: Apache 2.0\n- Finetuned from model [optional]: Llama-2-7b-chat-hf",
"### Model Sources [optional]\n\n\n\n- Repository: URL",
"## Uses\n\nThis model is fine-tuned on the summarization and analysis of schoarly medical articles, and as such, it should primarily be used for the summarization and analysis of said models.",
"### Direct Use\n\n\nThis model is intended solely for the summarization and analysis of schoarly medical articles. \n\nHere is the code to run the model directly:",
"### Downstream Use [optional]\n\nFine-tuned variations of this model can probably be extrapolated to parse non-medical scholarly articles and perform a broader set of tasks that merely summarization.",
"### Out-of-Scope Use\n\n\n\nThe model, regardless of finetuning, should not be used to generate medical advice without Prediction Guard API, as it may hallucinate false medical information, something can be detrimental to the health of anyone that makes medical decisions based on the model.",
"## Bias, Risks, and Limitations\n\n\n\nThe model has not been fine-tuned outside the scope of medical journals published in the United States, so it may have an American-centric slant when interpreting or summarizing articles.",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nThe model can be implemented the same way as Llama-2",
"## Training Details",
"### Training Data\n\n\n\nThe AI was trained on 120,000 open-access PubMed articles provided by the National Institute of Health. Information about accessing the API for PubMed can be found here: URL",
"### Training Procedure",
"#### Preprocessing [optional]\n\nEach paper in the dataset was split into the main body and the abstract, where the abstract would be a hypothetical summary that the model was asked to create.",
"#### Training Hyperparameters\n\n- Training regime: fp16\n\nLearning rate: 2e-4\nBatch size: 4",
"## Evaluation\n\nEvaluation was based on a 80-10-10 train-test-validate split.",
"### Testing Data, Factors & Metrics",
"#### Testing Data\n\nThe testing data was a randomly selected sample of ~12,000 articles from the general dataset.",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: Intel Max Series GPU (4 GPUs with 4th Gen CPU, 2 sockets, 256 GB memory, 2 TB disk with OneAPI base kit and tooling)\n- Hours used: 1 hour\n- Cloud Provider: Intel\n- Compute Region: us-region-1\n- Carbon Emitted: <0.1 kg CO2",
"## Model Card Contact\n\nayu303@URL",
"### Framework versions\n\n- PEFT 0.8.2"
] | [
43,
39,
3,
72,
15,
45,
34,
50,
62,
53,
42,
22,
3,
41,
5,
42,
25,
20,
12,
25,
99,
10,
11
] | [
"passage: TAGS\n#peft #safetensors #arxiv-1910.09700 #base_model-NousResearch/Llama-2-7b-chat-hf #region-us \n# Model Card for Model ID\n\nThe model is a variant of Llama-2 finetuned on Intel Cloud with a dataset of 120k pubmed articles to best summarize each article.## Model Details### Model Description\n\n\n- Developed by: Infogenesis\n- Funded by [optional]: Hacklytics 2024, Intel\n- Model type: Large Language Model\n- Language(s) (NLP): English\n- License: Apache 2.0\n- Finetuned from model [optional]: Llama-2-7b-chat-hf### Model Sources [optional]\n\n\n\n- Repository: URL## Uses\n\nThis model is fine-tuned on the summarization and analysis of schoarly medical articles, and as such, it should primarily be used for the summarization and analysis of said models.### Direct Use\n\n\nThis model is intended solely for the summarization and analysis of schoarly medical articles. \n\nHere is the code to run the model directly:### Downstream Use [optional]\n\nFine-tuned variations of this model can probably be extrapolated to parse non-medical scholarly articles and perform a broader set of tasks that merely summarization.### Out-of-Scope Use\n\n\n\nThe model, regardless of finetuning, should not be used to generate medical advice without Prediction Guard API, as it may hallucinate false medical information, something can be detrimental to the health of anyone that makes medical decisions based on the model.## Bias, Risks, and Limitations\n\n\n\nThe model has not been fine-tuned outside the scope of medical journals published in the United States, so it may have an American-centric slant when interpreting or summarizing articles.### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nThe model can be implemented the same way as Llama-2## Training Details"
] | [
-0.04774529114365578,
0.014418615028262138,
-0.0031361388973891735,
-0.04043159261345863,
0.08297774940729141,
0.03514338657259941,
0.0810292437672615,
0.058407340198755264,
0.05520203709602356,
0.10400009155273438,
-0.00866077933460474,
0.01975180022418499,
0.06562500447034836,
0.08401592820882797,
0.076780766248703,
-0.20741277933120728,
0.052042074501514435,
-0.08390134572982788,
0.08534357696771622,
0.03858467563986778,
0.07860048115253448,
-0.035048361867666245,
0.037565700709819794,
0.014263506047427654,
0.03867798298597336,
-0.018604835495352745,
0.046416595578193665,
0.031154926866292953,
0.08080076426267624,
0.08341402560472488,
0.03913550823926926,
-0.009982071816921234,
0.0732424408197403,
-0.21132245659828186,
-0.006173771806061268,
0.06254873424768448,
0.00929188821464777,
0.039420586079359055,
0.03759511932730675,
-0.04471513628959656,
0.19009283185005188,
-0.06627601385116577,
0.0963260680437088,
0.060984622687101364,
-0.07992187142372131,
-0.09225583076477051,
-0.08586038649082184,
0.08462821692228317,
0.10973697155714035,
0.10956760495901108,
-0.025608159601688385,
0.08334138989448547,
-0.01026624720543623,
0.03140638396143913,
-0.013020120561122894,
-0.13775135576725006,
-0.025736011564731598,
0.06436988711357117,
-0.003923267126083374,
0.07923101633787155,
-0.003863588673993945,
0.021924316883087158,
-0.017404381185770035,
0.025435298681259155,
0.0444972962141037,
-0.007597182411700487,
0.09213283658027649,
-0.02831302396953106,
-0.12228671461343765,
-0.03620997071266174,
0.16627247631549835,
-0.05650901049375534,
-0.03994474560022354,
-0.16838297247886658,
-0.022478029131889343,
0.09902800619602203,
-0.0028796351980417967,
-0.04154989495873451,
0.05098212510347366,
0.0033575354609638453,
0.19360700249671936,
-0.08923409134149551,
-0.0807623341679573,
-0.05469965934753418,
-0.041556842625141144,
0.05969666317105293,
0.007474824786186218,
0.044749028980731964,
-0.0026398366317152977,
0.11188235133886337,
-0.13156326115131378,
-0.03877430409193039,
-0.05349248647689819,
-0.06194264441728592,
-0.1798127442598343,
-0.058355916291475296,
-0.04542325437068939,
-0.10676316916942596,
-0.003637588582932949,
0.11803001165390015,
0.008956125006079674,
0.031479332596063614,
0.021339261904358864,
0.01982213743031025,
0.11182433366775513,
0.004670209717005491,
-0.10824024677276611,
0.01913636550307274,
-0.0025924064684659243,
0.08629756420850754,
0.07432156056165695,
0.014743275940418243,
0.013205638155341148,
0.06990792602300644,
-0.06789234280586243,
0.052589286118745804,
-0.01717926748096943,
0.005650967825204134,
-0.0766369104385376,
-0.06819722801446915,
0.15395085513591766,
-0.11923704296350479,
-0.07099022716283798,
-0.020204603672027588,
0.03207603842020035,
0.03924010321497917,
0.09910603612661362,
0.01081713568419218,
-0.045037537813186646,
0.08803965151309967,
-0.09787005931138992,
0.009345749393105507,
-0.09372182190418243,
-0.038011327385902405,
0.003097931621596217,
0.107521653175354,
-0.05716488137841225,
-0.07182266563177109,
-0.11618245393037796,
-0.08585295081138611,
0.05334240198135376,
-0.06655949354171753,
0.009611792862415314,
0.020218543708324432,
0.0029924495611339808,
-0.04242540895938873,
0.040123362094163895,
-0.006267277989536524,
-0.025792792439460754,
0.004416182637214661,
-0.08343043178319931,
0.03671853244304657,
-0.028727591037750244,
-0.00872245617210865,
-0.09762050211429596,
0.07543971389532089,
-0.2847023904323578,
0.0879707932472229,
-0.10445653647184372,
-0.02886541560292244,
-0.09726828336715698,
0.027987465262413025,
-0.08863987773656845,
0.024890899658203125,
0.032574839890003204,
0.0962347462773323,
-0.20911790430545807,
0.00640914449468255,
0.16025559604167938,
-0.16787226498126984,
-0.10977009683847427,
0.07942546159029007,
-0.04050923138856888,
0.1890995353460312,
0.061110664159059525,
0.13169947266578674,
0.08769281208515167,
-0.15325921773910522,
-0.02391699329018593,
-0.05537965148687363,
-0.0351986363530159,
0.1712845116853714,
0.059463806450366974,
-0.0930473655462265,
-0.052730534225702286,
0.023401664569973946,
-0.08576557040214539,
-0.0412113331258297,
-0.014649178832769394,
-0.04076491296291351,
-0.0024532091338187456,
-0.09298587590456009,
-0.03895948827266693,
-0.03249795362353325,
-0.02265380695462227,
0.02423124946653843,
-0.04968744516372681,
0.057661913335323334,
0.14710325002670288,
-0.017253495752811432,
-0.03352627530694008,
-0.0820547342300415,
-0.0472213514149189,
0.0019673758652061224,
0.01848427578806877,
-0.18038997054100037,
-0.1285434514284134,
0.01355401985347271,
-0.13579702377319336,
0.07985369116067886,
0.02847406268119812,
-0.0310031957924366,
0.05449838191270828,
-0.06028810515999794,
0.03940639644861221,
0.01413996983319521,
0.02473832294344902,
-0.06228873133659363,
-0.13250312209129333,
-0.012417018413543701,
-0.05481288209557533,
0.2203831821680069,
-0.17608197033405304,
0.05572910234332085,
-0.0755121186375618,
0.07640451192855835,
0.0267487745732069,
-0.0696471706032753,
0.04919895529747009,
-0.015545614063739777,
0.021365856751799583,
0.002225724747404456,
0.029037510976195335,
-0.02411757782101631,
-0.05604192987084389,
0.02204500138759613,
-0.20936501026153564,
-0.11434271186590195,
0.022157523781061172,
0.04265201464295387,
-0.12217207252979279,
-0.07775390893220901,
0.0015024802414700389,
-0.048525694757699966,
-0.10825685411691666,
-0.15630243718624115,
0.10016826540231705,
0.05908328667283058,
0.06242604926228523,
-0.05913618952035904,
-0.01860048621892929,
-0.006515673827379942,
-0.030719509348273277,
-0.001455592573620379,
0.021653493866324425,
0.1384107768535614,
-0.22682614624500275,
-0.021234402433037758,
0.04670317843556404,
0.034420810639858246,
0.11539442092180252,
0.04028759151697159,
-0.08732226490974426,
-0.05278521403670311,
-0.03160926699638367,
0.0008887473377399147,
0.08236409723758698,
-0.07228785753250122,
0.03965325653553009,
0.04657084494829178,
0.0055597578175365925,
0.05292970687150955,
-0.03421042114496231,
0.03803156316280365,
0.0068459343165159225,
0.01827460341155529,
-0.05346444994211197,
-0.008770833723247051,
-0.04976345971226692,
0.10927130281925201,
-0.006200570147484541,
0.10990240424871445,
-0.000744618650060147,
-0.03792956843972206,
-0.144499272108078,
0.1041645035147667,
-0.06567882746458054,
-0.1808146834373474,
-0.13018351793289185,
0.14737476408481598,
-0.019620228558778763,
0.009499282576143742,
-0.019061826169490814,
0.006576173938810825,
-0.08775881677865982,
-0.13548272848129272,
0.004663635510951281,
0.03430134057998657,
-0.1423986256122589,
-0.04925287514925003,
0.031123310327529907,
0.06867043673992157,
-0.05771429091691971,
-0.012038213200867176,
-0.0506051629781723,
-0.06221895292401314,
0.00004609352254192345,
0.007435910403728485,
0.0482352152466774,
0.16089579463005066,
0.06698532402515411,
-0.03765580803155899,
0.009161541238427162,
0.18442268669605255,
-0.06787090003490448,
0.11110172420740128,
0.17805857956409454,
-0.002353177173063159,
0.05417478457093239,
0.1402541995048523,
0.0640711858868599,
-0.08369544893503189,
0.06406411528587341,
0.08626201748847961,
-0.032588280737400055,
-0.22425009310245514,
-0.13298016786575317,
-0.05036722123622894,
-0.0976826399564743,
-0.010073601268231869,
0.01907997392117977,
-0.03270857408642769,
0.05487978830933571,
-0.05799465253949165,
-0.01938449591398239,
0.025743888691067696,
0.07040635496377945,
0.2018321305513382,
-0.03556085377931595,
0.1286192089319229,
-0.03879808634519577,
0.03556766360998154,
0.10090482234954834,
-0.050185732543468475,
0.20455056428909302,
0.024177374318242073,
0.09510413557291031,
0.0962214395403862,
-0.026682784780859947,
0.009552527219057083,
0.040150031447410583,
0.01733778975903988,
0.01596459373831749,
-0.032908469438552856,
-0.08097043633460999,
-0.09783035516738892,
0.105899877846241,
-0.04860740154981613,
-0.09142741560935974,
0.0036495423410087824,
0.05939343199133873,
0.03659072145819664,
0.10789576172828674,
0.00800597295165062,
-0.044331878423690796,
-0.07172565907239914,
0.060952190309762955,
-0.039983104914426804,
-0.07238691300153732,
0.01907435804605484,
0.13098882138729095,
-0.0874536857008934,
0.05237665772438049,
-0.011644475162029266,
0.06269960850477219,
-0.05577667057514191,
0.056555721908807755,
0.0068960245698690414,
-0.000006650210252701072,
-0.017705563455820084,
0.09677845984697342,
-0.05166112259030342,
0.07741598784923553,
0.01567339152097702,
0.044837359338998795,
-0.09339015930891037,
0.028233211487531662,
0.04141274467110634,
0.09396450221538544,
0.13753953576087952,
0.03028230555355549,
-0.07943902164697647,
-0.030476311221718788,
-0.03605113551020622,
0.016713550314307213,
0.0736910030245781,
-0.12022925913333893,
0.059101756662130356,
-0.03671533614397049,
0.02482948638498783,
-0.05043676495552063,
-0.007360612507909536,
-0.16905130445957184,
-0.18116037547588348,
0.13078823685646057,
-0.10160273313522339,
0.008280434645712376,
-0.06484212726354599,
-0.001898550195619464,
-0.01109363418072462,
0.15534190833568573,
-0.09520396590232849,
-0.10037057846784592,
-0.13396917283535004,
-0.02503877691924572,
0.14240077137947083,
-0.05223210155963898,
0.02194131910800934,
0.018035512417554855,
0.07817394286394119,
-0.012004371732473373,
-0.08252286911010742,
0.008492578752338886,
-0.11158959567546844,
-0.13496410846710205,
-0.06218905746936798,
0.12876559793949127,
0.07854882627725601,
0.04675191640853882,
0.0015377647941932082,
0.053463201969861984,
0.019151877611875534,
-0.12031085789203644,
0.035312190651893616,
0.21472503244876862,
0.0331575907766819,
0.07758498936891556,
-0.15713773667812347,
-0.0397007092833519,
-0.06960224360227585,
-0.08432649075984955,
-0.01501534041017294,
0.2192825973033905,
-0.04124470427632332,
0.12672704458236694,
0.14873884618282318,
-0.11117929965257645,
-0.2001216560602188,
-0.05728056654334068,
0.05059906467795372,
-0.00281333620660007,
0.14453865587711334,
-0.2521156668663025,
0.10849295556545258,
0.1231442540884018,
-0.014643213711678982,
0.030872328206896782,
-0.15317004919052124,
-0.1264115571975708,
0.024469736963510513,
0.027452096343040466,
0.03747046738862991,
-0.08041828870773315,
-0.0776616707444191,
0.024392427876591682,
-0.077339306473732,
0.09774836897850037,
-0.14814336597919464,
0.059318143874406815,
0.016463864594697952,
0.01808459497988224,
0.06362105160951614,
-0.03161067143082619,
0.14701484143733978,
0.017967868596315384,
0.057147204875946045,
-0.045888617634773254,
-0.01082090474665165,
0.0717870220541954,
-0.03281687945127487,
0.15740495920181274,
0.08235380053520203,
0.04537389799952507,
-0.020160125568509102,
-0.06844377517700195,
-0.07782738655805588,
-0.06425344944000244,
-0.049514684826135635,
-0.06525782495737076,
-0.06037959083914757,
0.10729049891233444,
0.0490221343934536,
-0.010305712930858135,
-0.03988317400217056,
-0.17481520771980286,
-0.03512469679117203,
0.14900238811969757,
0.21457885205745697,
-0.0037307527381926775,
-0.05021673068404198,
0.014080436900258064,
-0.051069486886262894,
0.042131226509809494,
-0.11118914932012558,
0.06232306733727455,
0.06676970422267914,
0.02600932866334915,
0.10079679638147354,
-0.009954441338777542,
-0.12877467274665833,
-0.026440339162945747,
0.03719070553779602,
-0.11345139890909195,
-0.248117133975029,
-0.027844537049531937,
0.14898157119750977,
-0.1489119678735733,
-0.0595758818089962,
0.1492374837398529,
-0.02172962576150894,
0.0044828373938798904,
-0.014436920173466206,
0.060647476464509964,
-0.014822323806583881,
0.115566685795784,
-0.03375540301203728,
0.025906601920723915,
-0.04773126170039177,
0.02583378180861473,
0.12118425965309143,
-0.08145435899496078,
0.017364731058478355,
0.06986761093139648,
-0.0996323749423027,
-0.10526827722787857,
-0.1604890525341034,
0.10392463207244873,
-0.02836747094988823,
-0.0462920181453228,
0.018147695809602737,
-0.0681796446442604,
-0.008800260722637177,
0.11160829663276672,
-0.01706545613706112,
0.016840102151036263,
-0.05283224582672119,
-0.008636675775051117,
-0.04813686013221741,
0.07755916565656662,
0.02001986838877201,
0.022097790613770485,
0.02567819133400917,
0.04598011076450348,
0.01854369044303894,
0.015759818255901337,
-0.038226522505283356,
-0.005036083050072193,
-0.0761454775929451,
-0.04203873127698898,
-0.1562044471502304,
-0.010469247587025166,
-0.029242895543575287,
-0.04336828365921974,
0.03971296176314354,
0.015392959117889404,
0.01375446654856205,
-0.012332919985055923,
-0.03857654705643654,
-0.022833149880170822,
-0.004818978253751993,
0.09173199534416199,
-0.10121943056583405,
0.015308143571019173,
0.07712672650814056,
-0.0714450478553772,
0.09197010844945908,
-0.016889538615942,
0.010852799750864506,
-0.011927682906389236,
-0.05056304484605789,
0.06365425884723663,
-0.05469426512718201,
0.07049290835857391,
-0.03946283832192421,
-0.17311635613441467,
-0.025180943310260773,
-0.012435659766197205,
-0.06634931266307831,
0.03364260122179985,
0.005333282984793186,
-0.07276489585638046,
0.04257524013519287,
0.09710483253002167,
-0.03444746881723404,
-0.06828299909830093,
-0.026197845116257668,
-0.027538472786545753,
0.021162746474146843,
0.08895290642976761,
-0.03604859858751297,
0.012528735212981701,
-0.16458117961883545,
-0.013880722224712372,
0.01851663924753666,
0.07709607481956482,
0.04239528626203537,
-0.08041921257972717,
0.042902760207653046,
0.03122214414179325,
0.16202011704444885,
-0.04207289218902588,
-0.0033037313260138035,
0.058990102261304855,
0.060555923730134964,
0.05958312377333641,
-0.0063682557083666325,
-0.002274621743708849,
0.019208991900086403,
0.015478427521884441,
-0.07063629478216171,
-0.0234351959079504,
-0.06176474317908287,
-0.04479919746518135,
0.14795330166816711,
0.024758880957961082,
0.07763759791851044,
-0.07622618973255157,
0.0009342905250377953,
-0.06627455353736877,
-0.0752246230840683,
0.014189423993229866,
0.007788591552525759,
-0.04454505071043968,
-0.052839528769254684,
-0.017240440472960472,
0.1365831196308136,
-0.1313105821609497,
0.12704631686210632,
-0.05850468575954437,
-0.07813472300767899,
-0.0458255410194397,
-0.1949339509010315,
0.01471047941595316,
0.00268270424567163,
-0.049758072942495346,
-0.09298066794872284,
0.05134700983762741,
0.12955732643604279,
0.000559188483748585,
0.00451253168284893,
0.17418034374713898,
-0.17933975160121918,
-0.03918905556201935,
-0.005642740987241268,
-0.003044489538297057,
0.008010500110685825,
-0.049570661038160324,
0.03215675801038742,
0.024799641221761703,
0.026649225503206253,
0.013931836001574993,
0.08201581984758377,
0.056853312999010086,
-0.05258823186159134,
0.022480523213744164,
-0.04957084357738495,
0.01806478388607502,
-0.026477621868252754,
-0.03637784346938133,
0.2046710103750229,
0.07288113981485367,
-0.011271703988313675,
-0.005889424588531256,
0.19804933667182922,
-0.036931466311216354,
-0.11273827403783798,
-0.16788221895694733,
0.23895664513111115,
-0.034230027347803116,
0.004112256690859795,
-0.018983852118253708,
-0.1010265052318573,
0.06323547661304474,
0.20283356308937073,
0.09593502432107925,
-0.10179123282432556,
-0.02131808176636696,
-0.012904651463031769,
0.011685875244438648,
0.015936966985464096,
0.09384258836507797,
-0.011765627190470695,
0.2297212928533554,
-0.06076284497976303,
0.16085676848888397,
-0.04401608929038048,
-0.03170699626207352,
-0.0805671289563179,
0.0723300650715828,
0.004321311600506306,
0.018758071586489677,
-0.013155858963727951,
0.08212500065565109,
-0.02897079661488533,
-0.1452944427728653,
-0.0032805127557367086,
0.01296218205243349,
-0.03896477073431015,
-0.029930151998996735,
-0.016459165140986443,
-0.046622078865766525,
0.02229594811797142,
-0.027132563292980194,
-0.004010620526969433,
0.2522672712802887,
-0.01355737540870905,
-0.03170545771718025,
-0.08049590140581131,
0.08110181242227554,
-0.03228170424699783,
0.17949089407920837,
0.025045735761523247,
0.08305323123931885,
0.05613289400935173,
-0.024830833077430725,
-0.06007176637649536,
0.1357344686985016,
-0.02472781389951706,
-0.04304841160774231,
0.03165804594755173,
0.141048863530159,
0.0358925499022007,
0.15394257009029388,
0.03463384509086609,
-0.10971788316965103,
0.02159099094569683,
0.04759099334478378,
-0.0549536757171154,
-0.03202388435602188,
0.144406259059906,
-0.08347117900848389,
0.15901096165180206,
0.12506774067878723,
-0.010352980345487595,
0.031154369935393333,
-0.033837661147117615,
0.07850626111030579,
0.006606729235500097,
0.10723669081926346,
-0.015665670856833458,
-0.14108996093273163,
0.061785247176885605,
0.014366033487021923,
0.04999271035194397,
-0.2705479860305786,
-0.08857354521751404,
0.05193628743290901,
0.024525178596377373,
0.0013742240844294429,
0.06342583149671555,
0.06306890398263931,
0.011309582740068436,
-0.04721716046333313,
-0.11560141295194626,
0.02141682058572769,
0.07811542600393295,
-0.05789291858673096,
-0.04156713932752609
] |
null | null | ml-agents |
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
- A *longer tutorial* to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
### Resume the training
```bash
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser**
1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: shazzz/ppo-Huggy
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
| {"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]} | reinforcement-learning | shazzz/ppo-Huggy | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | 2024-02-11T04:58:49+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your
browser: URL
- A *longer tutorial* to understand how works ML-Agents:
URL
### Resume the training
### Watch your Agent play
You can watch your agent playing directly in your browser
1. If the environment is part of ML-Agents official environments, go to URL
2. Step 1: Find your model_id: shazzz/ppo-Huggy
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play
| [
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: shazzz/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
"TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n",
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: shazzz/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
44,
198
] | [
"passage: TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: shazzz/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
0.01955466717481613,
0.016960162669420242,
-0.0041845147497951984,
0.02458176016807556,
0.13255807757377625,
-0.006191249005496502,
0.1537739485502243,
0.12263892590999603,
0.11885589361190796,
0.09642521291971207,
0.07130469381809235,
0.04990912228822708,
0.052812278270721436,
0.20471353828907013,
0.07168804109096527,
-0.2212149053812027,
-0.007934375666081905,
-0.079442098736763,
0.03635306656360626,
0.08788816630840302,
0.046835873275995255,
-0.03391210734844208,
0.06788214296102524,
0.0270024873316288,
-0.04677128419280052,
-0.024134881794452667,
-0.08778552711009979,
-0.021028079092502594,
0.04761705920100212,
0.005550215486437082,
-0.024112194776535034,
-0.019205890595912933,
0.06450019031763077,
-0.23075203597545624,
0.031923893839120865,
0.060025326907634735,
-0.006190949119627476,
0.015429575927555561,
0.11067036539316177,
0.05307841673493385,
0.11959044635295868,
-0.06967690587043762,
0.05621863529086113,
0.06564613431692123,
-0.0653916597366333,
0.003552692709490657,
-0.123075932264328,
0.050634466111660004,
0.23269391059875488,
0.08833149075508118,
0.002422721590846777,
0.0931980088353157,
-0.08861733973026276,
0.02816242352128029,
0.19956611096858978,
-0.2422017604112625,
-0.07134588807821274,
0.08379039168357849,
0.07315333932638168,
-0.01009010337293148,
-0.052350129932165146,
0.04280342534184456,
-0.021476782858371735,
0.042661696672439575,
0.08045196533203125,
-0.023704146966338158,
0.22187621891498566,
-0.009562348015606403,
-0.08286898583173752,
-0.06728469580411911,
0.02937706932425499,
0.0738174319267273,
-0.056641630828380585,
-0.22602832317352295,
0.027816448360681534,
0.13509614765644073,
-0.029915709048509598,
0.0031395195983350277,
0.06820368766784668,
-0.017787637189030647,
-0.05432827025651932,
-0.11107275635004044,
-0.04917238652706146,
-0.06296128034591675,
0.07957472652196884,
0.15967589616775513,
0.0001257945114048198,
-0.03723030164837837,
0.0793820470571518,
0.0670652687549591,
0.043214455246925354,
-0.028644749894738197,
-0.02098339982330799,
-0.03289467841386795,
-0.1212446317076683,
0.008687564171850681,
-0.002853740006685257,
0.07631930708885193,
0.058601465076208115,
0.1313210278749466,
0.031266432255506516,
0.01551262941211462,
0.03532348573207855,
0.05812032148241997,
-0.019291382282972336,
0.12810659408569336,
0.023004190996289253,
0.029397329315543175,
0.03288448974490166,
0.06023988500237465,
0.05743502452969551,
-0.05760565027594566,
-0.09703329205513,
0.07048378139734268,
-0.10559806227684021,
0.09564454853534698,
0.08827463537454605,
0.023724345490336418,
-0.06679005920886993,
-0.030680369585752487,
0.018017049878835678,
-0.12462861090898514,
0.07673858851194382,
0.0549587607383728,
-0.04257852956652641,
-0.12086217850446701,
-0.012461291626095772,
0.011298321187496185,
-0.07366634160280228,
0.02145787514746189,
-0.02308029867708683,
0.04264925792813301,
-0.003009037347510457,
-0.03240197151899338,
0.09989163279533386,
-0.07193680852651596,
-0.028236590325832367,
-0.16172435879707336,
-0.08274811506271362,
-0.05440953001379967,
0.05513087287545204,
-0.05181685462594032,
-0.12547436356544495,
-0.04950903728604317,
0.019592883065342903,
-0.09351537376642227,
-0.006297097075730562,
-0.01982637122273445,
-0.05797216668725014,
-0.0032916513737291098,
-0.03812199458479881,
0.06951398402452469,
0.17677730321884155,
0.036843542009592056,
-0.013069778680801392,
0.08224166184663773,
-0.182368203997612,
0.10531920194625854,
-0.10985264927148819,
0.17564871907234192,
-0.06307169049978256,
0.014707081019878387,
0.02661116234958172,
0.010417734272778034,
0.0246658306568861,
0.17622074484825134,
-0.05263051763176918,
-0.11537045985460281,
0.12236889451742172,
-0.03238926827907562,
-0.11774483323097229,
0.059231847524642944,
0.029021652415394783,
0.07636435329914093,
0.022947583347558975,
0.2675936818122864,
0.09325508773326874,
-0.2733699083328247,
0.05622567608952522,
0.042844273149967194,
-0.1420048475265503,
0.019296957179903984,
0.14268633723258972,
-0.05701052397489548,
0.0026861506048589945,
-0.0027328156866133213,
-0.16077081859111786,
0.09405771642923355,
-0.012975793331861496,
-0.0356840081512928,
0.04911648482084274,
-0.036328401416540146,
-0.016196344047784805,
-0.005273368209600449,
0.00941944494843483,
-0.03803446516394615,
-0.08916819095611572,
-0.06771577894687653,
0.08116620033979416,
-0.013823975808918476,
0.07425972819328308,
-0.06008389964699745,
0.12469303607940674,
0.03285515680909157,
0.05548487603664398,
-0.0823930948972702,
-0.09860366582870483,
0.014125626534223557,
0.001297368318773806,
0.09400327503681183,
-0.10237739235162735,
0.05476580932736397,
0.07263106852769852,
0.005599032621830702,
-0.07558926939964294,
-0.10028780251741409,
-0.013837323524057865,
-0.0792320966720581,
-0.10430499911308289,
-0.0730573907494545,
-0.06120097264647484,
0.13674691319465637,
-0.1039125993847847,
0.0639723464846611,
-0.1102232038974762,
0.03796634078025818,
-0.013193228282034397,
-0.03626612573862076,
0.05556023120880127,
-0.004913941025733948,
0.02736697532236576,
-0.06794877350330353,
0.10940904170274734,
0.04056413844227791,
-0.0899328961968422,
0.08466003090143204,
-0.04856289178133011,
-0.07531806081533432,
0.08434131741523743,
0.043899789452552795,
-0.012810607440769672,
-0.05623651668429375,
-0.09902561455965042,
0.009023447521030903,
-0.07393348962068558,
0.008452747948467731,
0.1360788196325302,
0.11006130278110504,
0.11792910844087601,
-0.07403340935707092,
-0.07135900855064392,
-0.019694818183779716,
-0.10954228788614273,
-0.05702758580446243,
0.15930809080600739,
0.02285880781710148,
0.08176080137491226,
0.04678148776292801,
0.06315819174051285,
0.0756390392780304,
0.0820825919508934,
0.015979129821062088,
-0.11351297050714493,
-0.012955575250089169,
0.07166627049446106,
0.05123676732182503,
0.004800283350050449,
0.039833735674619675,
-0.01076468639075756,
0.024434391409158707,
-0.04139936715364456,
-0.0037738040555268526,
-0.13893698155879974,
-0.07984679937362671,
0.002041247207671404,
-0.03965866565704346,
0.04111878201365471,
-0.012900223955512047,
-0.05315769463777542,
0.05382421985268593,
0.10380745679140091,
0.02727104164659977,
0.0013259927509352565,
-0.049402229487895966,
-0.11826548725366592,
0.06464220583438873,
-0.0839308425784111,
-0.3001224100589752,
-0.12291020154953003,
-0.11344161629676819,
-0.07125439494848251,
0.023586176335811615,
0.05716545134782791,
-0.1632985770702362,
-0.01000969484448433,
-0.1051488071680069,
-0.034582946449518204,
0.05064423382282257,
-0.07107829302549362,
0.1868787407875061,
0.10830220580101013,
0.019494375213980675,
-0.06762032955884933,
-0.013672750443220139,
0.006385789252817631,
-0.03566005080938339,
0.04084819555282593,
0.02263929694890976,
0.06914564967155457,
0.1260683387517929,
0.07665955275297165,
0.050237081944942474,
-0.025697173550724983,
0.0764605849981308,
-0.07394982874393463,
-0.01285574585199356,
0.12010373175144196,
-0.018677368760108948,
0.08337237685918808,
0.04087665304541588,
0.027347484603524208,
-0.025637494400143623,
0.04739993065595627,
0.006115861237049103,
-0.07028114050626755,
-0.18490926921367645,
-0.10527440905570984,
-0.02628188766539097,
0.22073349356651306,
0.0869249626994133,
0.0887628123164177,
-0.06367002427577972,
-0.031143590807914734,
-0.000032320982427336276,
-0.060235634446144104,
0.1490509808063507,
0.12396107614040375,
-0.05404526740312576,
-0.0726078525185585,
-0.003787518013268709,
-0.038754697889089584,
0.014454773627221584,
0.08947071433067322,
-0.00006439830758608878,
0.0771140530705452,
0.0357031375169754,
0.02452053315937519,
0.02940988540649414,
-0.04503604397177696,
-0.06599975377321243,
0.06325867772102356,
0.03786022216081619,
-0.007642372976988554,
-0.035827185958623886,
-0.08532532304525375,
-0.03027225285768509,
0.10527573525905609,
0.12047740072011948,
-0.07537998259067535,
-0.09401687234640121,
0.05512547865509987,
0.10602570325136185,
0.11258183419704437,
0.01643385924398899,
-0.12598523497581482,
-0.046394024044275284,
0.01198007632046938,
-0.13371887803077698,
0.02744317054748535,
-0.011198204010725021,
0.031224209815263748,
-0.18312406539916992,
0.07122696191072464,
0.018347878009080887,
0.12316517531871796,
0.07385251671075821,
0.009704111143946648,
0.019305501133203506,
0.08206778764724731,
-0.012411732226610184,
0.07744135707616806,
-0.1837945133447647,
0.07012981921434402,
-0.013935936614871025,
0.07298468798398972,
-0.048161499202251434,
-0.0022600528318434954,
0.086726114153862,
-0.026318233460187912,
0.17916299402713776,
0.04002339392900467,
0.053553901612758636,
-0.07695312052965164,
-0.1672312319278717,
-0.042681436985731125,
-0.0003641160437837243,
-0.09671829640865326,
0.07014984637498856,
-0.0006116968579590321,
-0.039143193513154984,
-0.10218167304992676,
0.16257400810718536,
0.01593051292002201,
-0.06149065122008324,
-0.003908722195774317,
-0.06991688907146454,
0.011006556451320648,
-0.05989162623882294,
-0.028564054518938065,
-0.03935018554329872,
0.2064933329820633,
0.114037424325943,
-0.010901488363742828,
-0.08773081749677658,
-0.056119926273822784,
-0.044122420251369476,
-0.02384662628173828,
-0.020128458738327026,
-0.005360202398151159,
0.1436661034822464,
-0.09570512175559998,
-0.042283207178115845,
-0.020676426589488983,
-0.10564757883548737,
-0.1190672218799591,
-0.005878407973796129,
0.23633813858032227,
-0.009267812594771385,
0.09691859036684036,
-0.023858919739723206,
0.01729343831539154,
-0.008039691485464573,
-0.0846179872751236,
0.1455199122428894,
0.17095579206943512,
0.01780400425195694,
0.038835931569337845,
-0.11201581358909607,
0.07132375240325928,
-0.1212918683886528,
-0.032208118587732315,
0.19682016968727112,
0.32517972588539124,
-0.03699471056461334,
0.21068795025348663,
0.08387564867734909,
-0.055608056485652924,
-0.22018980979919434,
-0.08757032454013824,
0.051022969186306,
-0.007816456258296967,
0.1358935534954071,
-0.1465950608253479,
0.021402833983302116,
0.032384518533945084,
-0.019780674949288368,
0.0060111042112112045,
-0.1415139138698578,
-0.08876324445009232,
-0.007369888946413994,
0.05834699049592018,
0.009516295045614243,
-0.10397639125585556,
-0.05381186306476593,
-0.038481589406728745,
-0.06634785234928131,
0.07546979933977127,
-0.1485690474510193,
0.08231887221336365,
0.0020105212461203337,
0.02843773178756237,
0.05051750689744949,
-0.032415423542261124,
0.1410907357931137,
-0.06114696338772774,
-0.04149448126554489,
-0.08398852497339249,
-0.00919515360146761,
-0.0029431760776787996,
-0.1205417588353157,
0.07225566357374191,
-0.0629904568195343,
-0.058813758194446564,
-0.18071389198303223,
-0.04086092859506607,
-0.03975223749876022,
0.05157467722892761,
-0.007657610345631838,
-0.014961072243750095,
-0.011693761684000492,
0.07378152012825012,
0.08627181500196457,
0.04897910729050636,
0.07081907242536545,
-0.019791044294834137,
-0.0016345662297680974,
0.1063402071595192,
0.07303767651319504,
0.02152150496840477,
-0.07697760313749313,
-0.04223113879561424,
-0.040555667132139206,
-0.022290999069809914,
-0.09017923474311829,
-0.0007419188041239977,
0.03483907878398895,
0.01968301273882389,
0.06103534251451492,
0.0515267588198185,
-0.10285093635320663,
-0.029275422915816307,
0.08008549362421036,
-0.10029212385416031,
-0.13130836188793182,
-0.05704570561647415,
-0.08568358421325684,
-0.05391444265842438,
-0.07725372910499573,
0.02829328179359436,
-0.02902476117014885,
-0.00011645424092421308,
0.04779989272356033,
0.045391637831926346,
-0.07368490844964981,
0.04016239196062088,
-0.007000102195888758,
0.027011092752218246,
-0.05985626205801964,
0.14718399941921234,
0.017767010256648064,
-0.03966806083917618,
0.025657333433628082,
0.19993719458580017,
-0.06585491448640823,
-0.07576164603233337,
-0.04124956205487251,
0.04901472106575966,
0.16446684300899506,
-0.032050877809524536,
-0.03019334003329277,
-0.06903574615716934,
0.07267815619707108,
-0.10923720896244049,
0.00344378175213933,
-0.09759530425071716,
0.029465194791555405,
0.09525046497583389,
-0.10848481953144073,
0.09289775043725967,
0.005001483019441366,
-0.05581581965088844,
-0.11708135157823563,
0.10033868998289108,
0.05276535823941231,
0.18537314236164093,
-0.02456001564860344,
-0.03821208328008652,
-0.14933069050312042,
0.005704037379473448,
-0.013252968899905682,
-0.006000888999551535,
-0.17644734680652618,
-0.01655859313905239,
-0.022888818755745888,
0.053101446479558945,
-0.013025691732764244,
0.027566345408558846,
-0.057011399418115616,
-0.06889075040817261,
-0.06598760187625885,
0.08851714432239532,
-0.03145524114370346,
-0.03838815912604332,
0.02941855788230896,
-0.08407442271709442,
0.0964704304933548,
0.07486171275377274,
-0.017498794943094254,
-0.048222482204437256,
-0.0594126395881176,
-0.04301866143941879,
0.019957879558205605,
-0.03879363089799881,
0.028596211224794388,
-0.1804826408624649,
0.007017684169113636,
-0.048822980374097824,
-0.0987100899219513,
0.010543908923864365,
0.12218373268842697,
-0.07975177466869354,
0.05392557755112648,
-0.0007764527690596879,
-0.12875880300998688,
-0.08292295038700104,
0.006935426499694586,
-0.0035687964409589767,
0.07378096133470535,
0.07055550813674927,
-0.07050099968910217,
0.16853675246238708,
-0.12488028407096863,
-0.0076949456706643105,
0.0019529500277712941,
0.017147531732916832,
0.028741123154759407,
-0.09772362560033798,
0.028852494433522224,
-0.013748792000114918,
0.1277616173028946,
0.08361547440290451,
-0.03629084303975105,
0.027204040437936783,
0.010617001913487911,
0.10527262091636658,
0.002861744025722146,
0.02667180821299553,
-0.015396537259221077,
0.007473444100469351,
0.03887078911066055,
-0.006676777731627226,
0.0602976493537426,
-0.1332894116640091,
0.08754850924015045,
0.09215667843818665,
0.10192757099866867,
0.05515516549348831,
0.08104833215475082,
-0.1170617863535881,
-0.1660527139902115,
-0.011911880224943161,
-0.006738357245922089,
0.03461429104208946,
-0.06646227091550827,
0.2585539221763611,
0.11220378428697586,
-0.2208557426929474,
0.0618458054959774,
0.005022049881517887,
0.023744238540530205,
-0.08948557823896408,
-0.1235358789563179,
0.00022786291083320975,
-0.21814146637916565,
0.07558238506317139,
-0.04120386764407158,
0.00852615013718605,
-0.02769651636481285,
-0.03099326603114605,
-0.0042189983651041985,
0.06284817308187485,
-0.11745738238096237,
-0.06210619583725929,
0.08487646281719208,
-0.04336533322930336,
0.0029383772052824497,
-0.011941628530621529,
-0.017886685207486153,
-0.02193833701312542,
-0.07553797960281372,
0.0632324367761612,
0.056350067257881165,
0.009433301165699959,
0.06229132041335106,
-0.05528045445680618,
-0.06419753283262253,
0.03126288950443268,
-0.010908958502113819,
0.028426742181181908,
0.1197723001241684,
0.048456352204084396,
-0.10519638657569885,
-0.003594320034608245,
0.2045820653438568,
-0.05475914105772972,
-0.003341440809890628,
-0.09024307131767273,
0.1615975797176361,
-0.026949848979711533,
-0.05618948116898537,
-0.04817026108503342,
-0.09331181645393372,
-0.0908263623714447,
0.24163854122161865,
0.12501122057437897,
-0.060438644140958786,
0.013322573155164719,
-0.029407482594251633,
0.02538066729903221,
0.005185241345316172,
0.11880301684141159,
0.07530589401721954,
0.14396125078201294,
-0.06777438521385193,
-0.020489342510700226,
-0.013276270590722561,
-0.07132557034492493,
-0.1761368364095688,
0.005882475525140762,
0.02718605287373066,
-0.03502604365348816,
-0.03582616522908211,
0.055097825825214386,
-0.1187872588634491,
-0.12224796414375305,
0.08614329248666763,
-0.08993352204561234,
-0.07001039385795593,
-0.017077717930078506,
0.003214782802388072,
0.013561107218265533,
0.1285293698310852,
0.053249429911375046,
0.04008987545967102,
0.09149129688739777,
-0.028180379420518875,
-0.05217384546995163,
0.04200339689850807,
0.08827416598796844,
-0.08365552127361298,
0.19059297442436218,
-0.045543018728494644,
0.0347619354724884,
0.04716358706355095,
0.023790473118424416,
-0.13787947595119476,
0.07728385180234909,
0.02915918454527855,
-0.16275165975093842,
0.014974900521337986,
0.07707913219928741,
-0.06873700022697449,
-0.056865375488996506,
0.0806926041841507,
-0.04114248603582382,
-0.001354956766590476,
0.11760200560092926,
-0.011978743597865105,
-0.047973208129405975,
0.0858975201845169,
-0.15424776077270508,
0.09711740911006927,
0.1390594094991684,
-0.060689423233270645,
-0.0011154101230204105,
-0.05393579974770546,
0.03477559611201286,
0.0348907969892025,
0.07200074940919876,
-0.004098930861800909,
-0.1434333473443985,
0.012264229357242584,
-0.0012184338411316276,
0.02646826021373272,
-0.2962554097175598,
-0.11668255180120468,
-0.05168569087982178,
-0.03635098785161972,
-0.03910461440682411,
0.10926824063062668,
0.10972388833761215,
-0.014854773879051208,
-0.009737528860569,
-0.19944524765014648,
0.04289500415325165,
0.16034111380577087,
-0.08000962436199188,
-0.008725503459572792
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smolm-autoreg-bpe-counterfactual-babylm-only_indef_articles_with_pl_nouns_removal-1e-4
This model was trained from scratch on the kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4138
- Accuracy: 0.4080
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 32000
- num_epochs: 20.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0521 | 1.0 | 18600 | 4.2759 | 0.3096 |
| 3.567 | 2.0 | 37200 | 3.7516 | 0.3623 |
| 3.3864 | 3.0 | 55800 | 3.5931 | 0.3802 |
| 3.2901 | 4.0 | 74400 | 3.5232 | 0.3883 |
| 3.2176 | 5.0 | 93000 | 3.4594 | 0.3939 |
| 3.1641 | 6.0 | 111600 | 3.4612 | 0.3961 |
| 3.1229 | 7.0 | 130200 | 3.4155 | 0.4000 |
| 3.0932 | 8.0 | 148800 | 3.4064 | 0.4015 |
| 3.0577 | 9.0 | 167400 | 3.4074 | 0.4036 |
| 3.0285 | 10.0 | 186000 | 3.3945 | 0.4058 |
| 3.0042 | 11.0 | 204600 | 3.3962 | 0.4052 |
| 2.9833 | 12.0 | 223200 | 3.3878 | 0.4060 |
| 2.9614 | 13.0 | 241800 | 3.3943 | 0.4065 |
| 2.9382 | 14.0 | 260400 | 3.3899 | 0.4072 |
| 2.9179 | 15.0 | 279000 | 3.3926 | 0.4075 |
| 2.9009 | 16.0 | 297600 | 3.4043 | 0.4072 |
| 2.8878 | 17.0 | 316200 | 3.3955 | 0.4079 |
| 2.8705 | 18.0 | 334800 | 3.4079 | 0.4078 |
| 2.8533 | 19.0 | 353400 | 3.4119 | 0.4077 |
| 2.8352 | 20.0 | 372000 | 3.4138 | 0.4080 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
| {"tags": ["generated_from_trainer"], "datasets": ["kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal"], "metrics": ["accuracy"], "model-index": [{"name": "smolm-autoreg-bpe-counterfactual-babylm-only_indef_articles_with_pl_nouns_removal-1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal", "type": "kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal"}, "metrics": [{"type": "accuracy", "value": 0.4080045140970133, "name": "Accuracy"}]}]}]} | text-generation | kanishka/smolm-autoreg-bpe-counterfactual-babylm-only_indef_articles_with_pl_nouns_removal-1e-4 | [
"transformers",
"tensorboard",
"safetensors",
"opt",
"text-generation",
"generated_from_trainer",
"dataset:kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T04:59:14+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #opt #text-generation #generated_from_trainer #dataset-kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| smolm-autoreg-bpe-counterfactual-babylm-only\_indef\_articles\_with\_pl\_nouns\_removal-1e-4
============================================================================================
This model was trained from scratch on the kanishka/counterfactual-babylm-only\_indef\_articles\_with\_pl\_nouns\_removal dataset.
It achieves the following results on the evaluation set:
* Loss: 3.4138
* Accuracy: 0.4080
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 32
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 32000
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.37.2
* Pytorch 2.1.0+cu121
* Datasets 2.16.1
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 32000\n* num\\_epochs: 20.0\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #opt #text-generation #generated_from_trainer #dataset-kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 32000\n* num\\_epochs: 20.0\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
95,
132,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #opt #text-generation #generated_from_trainer #dataset-kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 32000\n* num\\_epochs: 20.0\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.16.1\n* Tokenizers 0.15.1"
] | [
-0.10366370528936386,
0.0990387424826622,
-0.003449301002547145,
0.05587097629904747,
0.10320647060871124,
0.033804524689912796,
0.16475717723369598,
0.14421743154525757,
-0.06369976699352264,
0.08515602350234985,
0.12840576469898224,
0.07483217120170593,
0.06566530466079712,
0.12226273864507675,
-0.054064780473709106,
-0.2790226936340332,
0.030460016801953316,
0.023066842928528786,
-0.09637881070375443,
0.12073929607868195,
0.08888508379459381,
-0.11490767449140549,
0.049033187329769135,
0.015554162673652172,
-0.11364199221134186,
-0.018519215285778046,
-0.010626794770359993,
-0.05104842036962509,
0.10690823942422867,
0.03645888715982437,
0.12717048823833466,
0.037480078637599945,
0.08175220340490341,
-0.2325374335050583,
0.01917913742363453,
0.07308541983366013,
0.020138606429100037,
0.0926898643374443,
0.090135857462883,
-0.022063609212636948,
0.11326431483030319,
-0.11326965689659119,
0.07215561717748642,
0.037688616663217545,
-0.10803551971912384,
-0.2485581636428833,
-0.06740717589855194,
0.0686950832605362,
0.10417311638593674,
0.07772316038608551,
-0.02204274944961071,
0.11663953214883804,
-0.033610910177230835,
0.0960937887430191,
0.2094537764787674,
-0.2229280322790146,
-0.09805304557085037,
-0.03483311086893082,
0.06833398342132568,
0.050028275698423386,
-0.11595133692026138,
-0.005080952309072018,
0.0305133368819952,
0.01600353606045246,
0.11836118251085281,
0.0019572386518120766,
0.04539462924003601,
-0.0218360535800457,
-0.13541901111602783,
-0.05196358636021614,
0.11729031801223755,
0.06928965449333191,
-0.03275066614151001,
-0.10236577689647675,
-0.05253727361559868,
-0.16171200573444366,
-0.0587124228477478,
0.005085699260234833,
0.0174774881452322,
-0.041113562881946564,
-0.0705457329750061,
-0.03636869415640831,
-0.09988255053758621,
-0.07635153084993362,
0.030463993549346924,
0.20679911971092224,
0.05321415513753891,
-0.030780067667365074,
-0.005797445774078369,
0.10791638493537903,
0.06461409479379654,
-0.14825975894927979,
-0.0036211663391441107,
0.022405298426747322,
-0.06387022882699966,
-0.03499189391732216,
-0.03162185475230217,
-0.051793769001960754,
0.01907614804804325,
0.1353648453950882,
-0.05957060679793358,
0.0790727287530899,
0.009676631540060043,
0.03272223845124245,
-0.0756201520562172,
0.12716612219810486,
-0.0326482355594635,
-0.00317723723128438,
-0.017815135419368744,
0.13600848615169525,
0.009728637523949146,
-0.011754735372960567,
-0.04559149593114853,
0.008021404035389423,
0.12952429056167603,
0.043327152729034424,
-0.013156856410205364,
0.048576246947050095,
-0.06384508311748505,
-0.023066319525241852,
0.01688096486032009,
-0.09438814967870712,
0.032380811870098114,
0.03205122798681259,
-0.041213031858205795,
-0.013761885464191437,
0.025345461443066597,
0.01518732775002718,
-0.01492044422775507,
0.1022389754652977,
-0.08001606166362762,
0.005813201889395714,
-0.08512265980243683,
-0.08766317367553711,
0.005406683776527643,
-0.009963711723685265,
0.0009757045190781355,
-0.09400035440921783,
-0.12522242963314056,
-0.043772779405117035,
0.06216840073466301,
-0.03872703015804291,
-0.038603294640779495,
-0.04584945738315582,
-0.07657361030578613,
0.05303448066115379,
-0.009286228567361832,
0.11376377940177917,
-0.051625464111566544,
0.10740680247545242,
0.020668435841798782,
0.032730527222156525,
0.0438106395304203,
0.0414443239569664,
-0.062491267919540405,
0.0680697113275528,
-0.12249070405960083,
0.06501667946577072,
-0.07719942927360535,
0.02319638803601265,
-0.12185020744800568,
-0.11395180970430374,
-0.027466442435979843,
0.002052946714684367,
0.08767251670360565,
0.12499040365219116,
-0.13932912051677704,
-0.06770721822977066,
0.1580318659543991,
-0.09662897139787674,
-0.12403424829244614,
0.1197078749537468,
-0.03456445783376694,
0.016678528860211372,
0.030311498790979385,
0.13605371117591858,
0.09681767970323563,
-0.07905209064483643,
-0.0023109123576432467,
-0.037645336240530014,
0.09960397332906723,
0.05292070657014847,
0.1008596271276474,
-0.004136035684496164,
-0.020607147365808487,
-0.01130122970789671,
-0.055805034935474396,
0.06174386665225029,
-0.08786890655755997,
-0.08158213645219803,
-0.031217137351632118,
-0.07389386743307114,
0.04700354486703873,
0.0564737543463707,
0.03229723498225212,
-0.08329310268163681,
-0.1279706507921219,
0.044363826513290405,
0.11427687853574753,
-0.10255543142557144,
0.014008837752044201,
-0.05798180401325226,
0.03448333591222763,
-0.04283535107970238,
-0.015653351321816444,
-0.14756493270397186,
-0.08844117075204849,
0.02593543566763401,
-0.04301869496703148,
-0.005301665514707565,
-0.03732508793473244,
0.0905819982290268,
0.07252205908298492,
-0.06370357424020767,
-0.08631670475006104,
-0.0639321580529213,
0.009535789489746094,
-0.08656777441501617,
-0.2153526097536087,
-0.07117675244808197,
-0.031645286828279495,
0.18365220725536346,
-0.2487623393535614,
0.03953852877020836,
-0.017248788848519325,
0.144306480884552,
0.04245239123702049,
-0.03781469538807869,
0.005694948602467775,
0.03579362854361534,
-0.039103616029024124,
-0.08272900432348251,
0.04888619855046272,
0.003734149504452944,
-0.12188301980495453,
0.01743805594742298,
-0.1507221907377243,
0.08556873351335526,
0.09342791885137558,
-0.02170260064303875,
-0.10566450655460358,
-0.06822450459003448,
-0.06965711712837219,
-0.059430401772260666,
-0.028649678453803062,
-0.009332968853414059,
0.15283100306987762,
0.03515392169356346,
0.12649613618850708,
-0.0899798721075058,
-0.05335300788283348,
0.021954121068120003,
-0.012217708863317966,
-0.031554847955703735,
0.1334719955921173,
0.05639122053980827,
-0.12717664241790771,
0.10630538314580917,
0.10679596662521362,
-0.06915593147277832,
0.15411663055419922,
-0.051070816814899445,
-0.09481849521398544,
-0.03166775777935982,
0.04566638544201851,
0.035735297948122025,
0.10638318210840225,
-0.10687463730573654,
0.022862739861011505,
0.020206568762660027,
0.0008719391189515591,
0.021470969542860985,
-0.19658923149108887,
-0.010407498106360435,
0.04273160547018051,
-0.04611051827669144,
0.019156813621520996,
-0.018922289833426476,
0.005502503365278244,
0.09791955351829529,
-0.012472763657569885,
-0.014812451787292957,
0.018797075375914574,
-0.009455051273107529,
-0.09327202290296555,
0.21350856125354767,
-0.08574733883142471,
-0.15262940526008606,
-0.1269918531179428,
0.014728686772286892,
-0.027978356927633286,
-0.009649497456848621,
0.029301874339580536,
-0.07461618632078171,
-0.029155021533370018,
-0.08883000910282135,
0.0034289651084691286,
-0.03833068162202835,
0.019631320610642433,
-0.003139754058793187,
-0.0059502036310732365,
0.08271573483943939,
-0.09714248031377792,
0.008723882958292961,
0.005472881719470024,
-0.013640591874718666,
0.05123050510883331,
0.042692720890045166,
0.06942299753427505,
0.11666324734687805,
-0.005820820573717356,
-0.006473558954894543,
-0.024365149438381195,
0.17076246440410614,
-0.08881065249443054,
-0.0029542152769863605,
0.1258295625448227,
-0.029918666929006577,
0.05533035472035408,
0.11119180917739868,
0.05197065323591232,
-0.07413884997367859,
0.02977585233747959,
0.045519862323999405,
-0.003626969177275896,
-0.23117661476135254,
-0.019442155957221985,
-0.04758835211396217,
-0.029554463922977448,
0.13194717466831207,
0.036048661917448044,
-0.0269843228161335,
0.07649737596511841,
-0.06156645342707634,
0.014427355490624905,
0.002685198560357094,
0.09416135400533676,
0.06893079727888107,
0.04111045226454735,
0.10908906161785126,
-0.011691246181726456,
-0.05829749256372452,
0.02701018750667572,
-0.020129326730966568,
0.20885591208934784,
-0.01935921050608158,
0.15872173011302948,
0.03705541789531708,
0.14006829261779785,
0.005939209368079901,
0.06776443123817444,
0.021394984796643257,
-0.02396506816148758,
0.018956543877720833,
-0.06396671384572983,
-0.04495752975344658,
0.04906880110502243,
0.010968520306050777,
0.05208077281713486,
-0.11306590586900711,
0.01358717866241932,
0.02108604833483696,
0.28294166922569275,
0.05213248357176781,
-0.32078731060028076,
-0.09558576345443726,
0.021401841193437576,
-0.05697565898299217,
-0.08233033120632172,
0.0018964943010360003,
0.12889738380908966,
-0.10139049589633942,
0.05468642711639404,
-0.11884041130542755,
0.0795428603887558,
-0.05837347358465195,
-0.0010708183981478214,
0.059037916362285614,
0.09365333616733551,
-0.020564723759889603,
0.07523594051599503,
-0.24399207532405853,
0.2762572765350342,
-0.005202562548220158,
0.0725182443857193,
-0.06092647463083267,
0.03203238919377327,
0.04438056796789169,
-0.00808976124972105,
0.07027174532413483,
-0.011076861061155796,
-0.0986115112900734,
-0.18046684563159943,
-0.09070700407028198,
0.022525273263454437,
0.12529470026493073,
-0.0654931366443634,
0.1359158456325531,
-0.0462394542992115,
-0.0065314993262290955,
0.06567201763391495,
-0.06455165147781372,
-0.14022564888000488,
-0.10875143855810165,
0.03926686570048332,
0.02131977677345276,
0.05395733565092087,
-0.11647573858499527,
-0.11899720877408981,
-0.04418681189417839,
0.1818782240152359,
-0.055989835411310196,
-0.056162577122449875,
-0.14492125809192657,
0.07450181245803833,
0.14401692152023315,
-0.06832819432020187,
0.03439722955226898,
0.004404108971357346,
0.15520992875099182,
0.017145752906799316,
-0.018899500370025635,
0.08700574189424515,
-0.08628159761428833,
-0.22750407457351685,
-0.050206508487463,
0.15254604816436768,
0.03748760372400284,
0.05084852874279022,
-0.010708710178732872,
0.017687339335680008,
-0.020572127774357796,
-0.06959428638219833,
0.048135656863451004,
0.020147832110524178,
0.046837691217660904,
0.053100813180208206,
-0.05701727792620659,
0.003367431228980422,
-0.0648970678448677,
-0.043673835694789886,
0.1421121209859848,
0.3190597891807556,
-0.06322222203016281,
0.00651511549949646,
0.03088267333805561,
-0.06028367578983307,
-0.13528652489185333,
0.011465910822153091,
0.11583045870065689,
0.020622901618480682,
0.03592133894562721,
-0.191046342253685,
0.045994650572538376,
0.0803636834025383,
-0.022290993481874466,
0.09065122157335281,
-0.2732055187225342,
-0.13539773225784302,
0.09660455584526062,
0.15193824470043182,
0.004587586037814617,
-0.1609763354063034,
-0.056573159992694855,
-0.010024301707744598,
-0.06180860847234726,
0.12076640129089355,
-0.028430189937353134,
0.12322629243135452,
-0.015957290306687355,
0.03906718268990517,
0.035644736140966415,
-0.06563103199005127,
0.16566620767116547,
-0.05982121452689171,
0.07286552339792252,
-0.030491523444652557,
0.024596668779850006,
0.02907683327794075,
-0.07244116812944412,
0.011233028955757618,
-0.10879597812891006,
0.04092470183968544,
-0.13255605101585388,
-0.03596385940909386,
-0.07187321037054062,
0.0436987429857254,
-0.05858008190989494,
-0.050060730427503586,
-0.01659597083926201,
0.053963929414749146,
0.06974423676729202,
-0.00032317364821210504,
0.14455632865428925,
-0.019259488210082054,
0.1606426239013672,
0.10387025773525238,
0.11656741797924042,
0.034632377326488495,
-0.05605508014559746,
-0.038020484149456024,
-0.01238695252686739,
0.049717362970113754,
-0.10138122737407684,
0.033772505819797516,
0.12762129306793213,
0.028759794309735298,
0.15628767013549805,
0.04794696718454361,
-0.06709924340248108,
0.004001602064818144,
0.055976346135139465,
-0.11412973701953888,
-0.13293379545211792,
-0.0313839465379715,
0.06349397450685501,
-0.17157363891601562,
-0.01568855717778206,
0.1284220814704895,
-0.07272288203239441,
-0.013449925929307938,
0.0033390282187610865,
0.02424471452832222,
-0.01216795388609171,
0.18627622723579407,
0.03521794453263283,
0.07887297123670578,
-0.06497985124588013,
0.07648635655641556,
0.04233432188630104,
-0.12533320486545563,
0.046271588653326035,
0.08160927891731262,
-0.04930853843688965,
-0.038612112402915955,
0.06011028587818146,
0.11528965085744858,
0.0024762065149843693,
-0.040359508246183395,
-0.12618336081504822,
-0.11832933872938156,
0.05738738551735878,
0.09484980255365372,
0.024664366617798805,
0.010903097689151764,
-0.010997132398188114,
0.03278375044465065,
-0.12003934383392334,
0.1269100159406662,
0.07376409322023392,
0.08980276435613632,
-0.14005160331726074,
0.1506686955690384,
-0.006438399665057659,
-0.004467445891350508,
-0.009482361376285553,
0.026646126061677933,
-0.10596754401922226,
-0.007045764476060867,
-0.11180411279201508,
0.017106059938669205,
-0.05160559341311455,
-0.001212093629874289,
0.008228490129113197,
-0.062174439430236816,
-0.051061149686574936,
0.003134071594104171,
-0.09826112538576126,
-0.05364368110895157,
0.011256014928221703,
0.06760777533054352,
-0.09744516760110855,
-0.030090034008026123,
0.04079441726207733,
-0.10833059251308441,
0.0809825137257576,
0.0397908054292202,
0.01893887296319008,
0.019244642928242683,
-0.1276300698518753,
0.04169965535402298,
0.015499735251069069,
-0.003442273009568453,
0.0008114213705994189,
-0.15148819983005524,
0.005197910126298666,
-0.025359828025102615,
0.011562567204236984,
0.002288562012836337,
0.0477861724793911,
-0.13127774000167847,
-0.03689691796898842,
-0.03332473710179329,
-0.039866767823696136,
-0.06454744935035706,
0.03744349628686905,
0.022919131442904472,
0.004806122276932001,
0.1838691234588623,
-0.08851950615644455,
0.0567268542945385,
-0.2366749793291092,
0.009508803486824036,
-0.011601359583437443,
-0.09089943766593933,
-0.042441487312316895,
-0.040099553763866425,
0.07810033857822418,
-0.06656145304441452,
0.07487665861845016,
-0.03795872628688812,
0.026167303323745728,
0.02927473746240139,
-0.10301929712295532,
0.04727416858077049,
0.03730344399809837,
0.2422686368227005,
0.0341506227850914,
-0.032008036971092224,
0.035461921244859695,
0.0007087561534717679,
0.06372442841529846,
0.08733942359685898,
0.16472768783569336,
0.18716731667518616,
-0.02180989645421505,
0.0865698903799057,
0.03894283249974251,
-0.09380479902029037,
-0.11133420467376709,
0.08597749471664429,
-0.021183017641305923,
0.10126101970672607,
-0.018195755779743195,
0.21379300951957703,
0.12616777420043945,
-0.18020184338092804,
0.0228157639503479,
-0.036758385598659515,
-0.0773962140083313,
-0.08744967728853226,
-0.07711084187030792,
-0.08051121979951859,
-0.14215613901615143,
0.007276004645973444,
-0.12215248495340347,
0.016998562961816788,
0.05414757877588272,
0.023791350424289703,
0.00841610599309206,
0.16212739050388336,
0.07200150936841965,
0.0002286359085701406,
0.10283012688159943,
0.025167787447571754,
0.0011701848125085235,
-0.053058624267578125,
-0.13236254453659058,
0.047083381563425064,
-0.0327865332365036,
0.045901574194431305,
-0.0475313737988472,
-0.03652670606970787,
0.061314187943935394,
0.011068129912018776,
-0.13146381080150604,
0.02356206253170967,
-0.009564677253365517,
0.06501027196645737,
0.06494323909282684,
0.021446552127599716,
0.009062539786100388,
-0.03462212160229683,
0.22105605900287628,
-0.06714639812707901,
-0.029106495901942253,
-0.11414036899805069,
0.2070382535457611,
-0.019500812515616417,
-0.030744316056370735,
0.032027468085289,
-0.07814130187034607,
0.024775458499789238,
0.15599483251571655,
0.10732139647006989,
-0.02660478465259075,
-0.0009319172822870314,
0.013568096794188023,
-0.013505679555237293,
-0.04003860428929329,
0.1017017588019371,
0.09195497632026672,
-0.013432910665869713,
-0.06874924153089523,
-0.03754112124443054,
-0.038960959762334824,
-0.025739384815096855,
-0.041765689849853516,
0.06061011925339699,
0.03572644293308258,
0.0030605026986449957,
-0.02710730955004692,
0.09045447409152985,
-0.03506305068731308,
-0.12740164995193481,
0.030125238001346588,
-0.1628425568342209,
-0.17682838439941406,
-0.04273116961121559,
0.07154256850481033,
0.01002413034439087,
0.04723060131072998,
-0.014996804296970367,
-0.01023596990853548,
0.08926218748092651,
-0.007448574993759394,
-0.023890193551778793,
-0.06915180385112762,
0.056704722344875336,
-0.07954257726669312,
0.21806754171848297,
-0.025330351665616035,
0.024980343878269196,
0.1296357363462448,
0.015428446233272552,
-0.0996449738740921,
0.04524378478527069,
0.07703857123851776,
-0.10048331320285797,
0.06949757039546967,
0.20062321424484253,
-0.03666027635335922,
0.11337004601955414,
0.062355078756809235,
-0.11436530202627182,
0.0047583500854671,
-0.08672254532575607,
-0.061413321644067764,
-0.054252542555332184,
0.008284407667815685,
-0.040018267929553986,
0.1472781002521515,
0.22199973464012146,
-0.06018543988466263,
-0.023010501638054848,
-0.05392381176352501,
0.034994520246982574,
0.06534883379936218,
0.11587685346603394,
-0.02744973823428154,
-0.2706533670425415,
0.012858927249908447,
0.04996664077043533,
0.027734074741601944,
-0.27640777826309204,
-0.09251341223716736,
0.012525837868452072,
-0.05794887617230415,
-0.08134337514638901,
0.10460615903139114,
0.08176710456609726,
0.04864778369665146,
-0.04739847779273987,
-0.10439000278711319,
-0.04953964799642563,
0.17346587777137756,
-0.15432405471801758,
-0.05406825244426727
] |
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# experiments
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the Salesforce/dialogstudio dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7918
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0878 | 0.4 | 22 | 2.0826 |
| 1.9213 | 0.8 | 44 | 1.9025 |
| 1.7334 | 1.2 | 66 | 1.8022 |
| 1.7909 | 1.6 | 88 | 1.7930 |
| 1.7901 | 2.0 | 110 | 1.7918 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.13.3
| {"tags": ["generated_from_trainer"], "datasets": ["Salesforce/dialogstudio"], "base_model": "meta-llama/Llama-2-7b-hf", "model-index": [{"name": "experiments", "results": []}]} | null | AbdulHannanMujawar/experiments | [
"safetensors",
"generated_from_trainer",
"dataset:Salesforce/dialogstudio",
"base_model:meta-llama/Llama-2-7b-hf",
"region:us"
] | 2024-02-11T04:59:23+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #dataset-Salesforce/dialogstudio #base_model-meta-llama/Llama-2-7b-hf #region-us
| experiments
===========
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the Salesforce/dialogstudio dataset.
It achieves the following results on the evaluation set:
* Loss: 1.7918
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 4
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 2
### Training results
### Framework versions
* Transformers 4.32.1
* Pytorch 2.0.1+cu117
* Datasets 2.14.6
* Tokenizers 0.13.3
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* num\\_epochs: 2",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1+cu117\n* Datasets 2.14.6\n* Tokenizers 0.13.3"
] | [
"TAGS\n#safetensors #generated_from_trainer #dataset-Salesforce/dialogstudio #base_model-meta-llama/Llama-2-7b-hf #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* num\\_epochs: 2",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1+cu117\n* Datasets 2.14.6\n* Tokenizers 0.13.3"
] | [
47,
145,
4,
33
] | [
"passage: TAGS\n#safetensors #generated_from_trainer #dataset-Salesforce/dialogstudio #base_model-meta-llama/Llama-2-7b-hf #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* num\\_epochs: 2### Training results### Framework versions\n\n\n* Transformers 4.32.1\n* Pytorch 2.0.1+cu117\n* Datasets 2.14.6\n* Tokenizers 0.13.3"
] | [
-0.11578119546175003,
0.08205576986074448,
-0.0020842859521508217,
0.09405625611543655,
0.14311903715133667,
0.00995413213968277,
0.1469561755657196,
0.10524368286132812,
-0.11824996024370193,
0.07782665640115738,
0.0920526459813118,
0.1058209091424942,
0.025891998782753944,
0.2094549685716629,
-0.07106813043355942,
-0.22618885338306427,
0.03345532342791557,
-0.015999626368284225,
-0.08361870795488358,
0.11838020384311676,
0.07403159886598587,
-0.14954806864261627,
0.08259148895740509,
-0.020365850999951363,
-0.16317208111286163,
-0.007099248003214598,
0.003409001277759671,
-0.04110194742679596,
0.11063853651285172,
-0.0051493518985807896,
0.13214096426963806,
0.04501491039991379,
0.11088396608829498,
-0.18324732780456543,
0.012339429929852486,
0.062279991805553436,
0.0067631397396326065,
0.07520446181297302,
0.04761859402060509,
-0.03531970456242561,
0.08552056550979614,
-0.11344937235116959,
0.07655838131904602,
0.025335317477583885,
-0.15280315279960632,
-0.2556724548339844,
-0.11899498105049133,
0.023754017427563667,
0.09774277359247208,
0.06546443700790405,
-0.022706028074026108,
0.1781691610813141,
-0.06084364652633667,
0.09115391969680786,
0.2949475944042206,
-0.2882305979728699,
-0.07566958665847778,
0.033101145178079605,
0.00883791595697403,
0.07788770645856857,
-0.10981830209493637,
-0.006283227354288101,
0.053166769444942474,
0.02960127964615822,
0.119255430996418,
-0.012626216746866703,
-0.06504400819540024,
-0.0008831770974211395,
-0.1466488540172577,
-0.009604832157492638,
0.09921394288539886,
0.03690361976623535,
-0.04744148999452591,
-0.022628119215369225,
-0.06964930891990662,
-0.18378585577011108,
-0.06430470198392868,
-0.012029065750539303,
0.07046293467283249,
-0.07389774918556213,
-0.1163683533668518,
0.02584758773446083,
-0.07836878299713135,
-0.074054054915905,
-0.007540362887084484,
0.20235946774482727,
0.04800301417708397,
0.010188058950006962,
-0.01676480658352375,
0.10372625291347504,
-0.06703223288059235,
-0.165218785405159,
-0.0034167212434113026,
0.023477260023355484,
-0.04291607066988945,
-0.05562237277626991,
-0.040708351880311966,
-0.02941233478486538,
0.02845960482954979,
0.15611271560192108,
-0.1506160944700241,
0.05261712521314621,
0.002815194660797715,
0.009939677082002163,
-0.07853059470653534,
0.13258647918701172,
-0.059763453900814056,
-0.021442824974656105,
0.006882472429424524,
0.11110413074493408,
0.05735853686928749,
0.0019792653620243073,
-0.07872612029314041,
0.04146749898791313,
0.0982428714632988,
0.042285285890102386,
-0.0673699826002121,
0.03816363960504532,
-0.05192574858665466,
0.006192613393068314,
0.06858216971158981,
-0.10000517219305038,
0.03870868310332298,
0.01929337903857231,
-0.08080431073904037,
-0.05380931869149208,
0.0051751649007201195,
0.023502705618739128,
0.027447491884231567,
0.13488541543483734,
-0.08815500140190125,
0.035127539187669754,
-0.08191025257110596,
-0.12351862341165543,
0.022161919623613358,
-0.06619188189506531,
-0.0009023906895890832,
-0.0792904943227768,
-0.1396050900220871,
-0.02957771345973015,
0.03911280632019043,
-0.0639166533946991,
-0.008960668928921223,
-0.05218813568353653,
-0.09996441751718521,
0.015868613496422768,
-0.01404211763292551,
0.10198433697223663,
-0.08217482268810272,
0.10003470629453659,
0.058403246104717255,
0.07689445465803146,
-0.024422243237495422,
0.0187307707965374,
-0.09609057009220123,
0.039120614528656006,
-0.29458823800086975,
0.018839893862605095,
-0.0667613297700882,
0.0738874226808548,
-0.09226949512958527,
-0.09089674055576324,
0.02744014374911785,
-0.02469955012202263,
0.10815766453742981,
0.14489859342575073,
-0.192718043923378,
-0.04981589317321777,
0.19258269667625427,
-0.12174180895090103,
-0.13477060198783875,
0.1099417582154274,
-0.046959616243839264,
0.013620130717754364,
0.06094397231936455,
0.18707922101020813,
-0.005556849297136068,
-0.14133581519126892,
-0.02379118651151657,
-0.08371260017156601,
0.08485882729291916,
-0.020559974014759064,
0.06547344475984573,
-0.0103416433557868,
0.058893024921417236,
0.0034589548595249653,
-0.026877427473664284,
0.018918225541710854,
-0.11653187870979309,
-0.07435017079114914,
-0.034867893904447556,
-0.1042444109916687,
0.046787112951278687,
0.04715682938694954,
0.046204712241888046,
-0.13262023031711578,
-0.08767426759004593,
0.05292142182588577,
0.09353440999984741,
-0.05863681435585022,
0.033843036741018295,
-0.06263497471809387,
0.09168670326471329,
-0.061325717717409134,
-0.028759200125932693,
-0.17187288403511047,
-0.09562798589468002,
0.028936926275491714,
-0.004537381697446108,
0.015806498005986214,
-0.07831691205501556,
0.08418668806552887,
0.10615650564432144,
-0.08601611107587814,
-0.029315268620848656,
-0.03231965750455856,
0.007848367094993591,
-0.11445443332195282,
-0.2581714391708374,
-0.04147599637508392,
-0.0447775274515152,
0.12516304850578308,
-0.19791792333126068,
0.02895508147776127,
0.027022231370210648,
0.1184968575835228,
0.038858141750097275,
-0.03314771130681038,
-0.005147801246494055,
0.06658507138490677,
-0.011283471249043941,
-0.07316126674413681,
0.034322746098041534,
-0.005982565693557262,
-0.07469962537288666,
-0.027781330049037933,
-0.1638805866241455,
0.16366328299045563,
0.12632034718990326,
0.008384347893297672,
-0.11440054327249527,
-0.03423295542597771,
-0.060166679322719574,
-0.030741261318325996,
-0.057930734008550644,
0.04423881694674492,
0.12263191491365433,
0.025383668020367622,
0.11979687958955765,
-0.09534579515457153,
-0.03494447097182274,
0.03259889781475067,
-0.03510033339262009,
0.03455420956015587,
0.107480488717556,
0.06172508746385574,
-0.11289944499731064,
0.12408312410116196,
0.14161989092826843,
-0.05427689477801323,
0.10280146449804306,
-0.05805409327149391,
-0.05482051521539688,
-0.0451430007815361,
0.0072329104878008366,
0.020479213446378708,
0.15676960349082947,
-0.030778147280216217,
0.01483954954892397,
0.002497122623026371,
0.015533657744526863,
-0.007437944877892733,
-0.20907972753047943,
-0.028110964223742485,
0.01794709637761116,
-0.05307776853442192,
-0.025308310985565186,
-0.027375347912311554,
0.01226765476167202,
0.11549428105354309,
0.0020906515419483185,
-0.05598112940788269,
-0.006200709380209446,
0.004648572765290737,
-0.06203107163310051,
0.21727609634399414,
-0.0822078138589859,
-0.054489534348249435,
-0.06422510743141174,
-0.04182732477784157,
-0.04927971214056015,
0.004844253417104483,
0.05901254341006279,
-0.11015770584344864,
-0.04440814629197121,
-0.10195562243461609,
-0.014875796623528004,
0.056214578449726105,
0.03306123986840248,
-0.012031982652842999,
-0.006671815644949675,
0.06306790560483932,
-0.09981447458267212,
-0.009266129694879055,
-0.06269270181655884,
-0.03363386541604996,
0.04539448395371437,
0.06294538080692291,
0.111360564827919,
0.14166320860385895,
-0.008336749859154224,
0.01592201367020607,
-0.03037705272436142,
0.22170019149780273,
-0.07393889874219894,
-0.019577866420149803,
0.0868004560470581,
0.003693346632644534,
0.062023211270570755,
0.17395099997520447,
0.06547493487596512,
-0.1214781403541565,
0.015310967341065407,
0.04279784485697746,
-0.03958294168114662,
-0.21261358261108398,
-0.03336590155959129,
-0.02216503396630287,
-0.051995474845170975,
0.07213418930768967,
0.018869873136281967,
-0.020311539992690086,
0.042857877910137177,
0.0038185243029147387,
-0.005656485911458731,
-0.008501752279698849,
0.0802900493144989,
0.041176073253154755,
0.06433844566345215,
0.11942547559738159,
-0.03237507864832878,
-0.0385710746049881,
0.02629953809082508,
-0.01747504621744156,
0.22256149351596832,
-0.028253579512238503,
0.112640380859375,
0.056408483535051346,
0.14642629027366638,
-0.0016522392397746444,
0.07440438121557236,
0.024450890719890594,
-0.05229826644062996,
0.000672222173307091,
-0.07504026591777802,
-0.013458164408802986,
0.027497412636876106,
-0.066008560359478,
0.05062389001250267,
-0.1363443285226822,
0.03486935794353485,
0.06722725927829742,
0.27020296454429626,
0.06343597918748856,
-0.3456917703151703,
-0.07385037839412689,
0.011513586156070232,
0.0008813355234451592,
0.00040856978739611804,
0.00047223243745975196,
0.12108317017555237,
-0.05428992584347725,
0.08163944631814957,
-0.06238951534032822,
0.0694451779127121,
-0.022540103644132614,
0.022669531404972076,
0.042886510491371155,
0.09723852574825287,
-0.03949255868792534,
0.013826187700033188,
-0.21759051084518433,
0.31702831387519836,
0.032374776899814606,
0.0973680391907692,
-0.018569137901067734,
-0.016036024317145348,
0.021179473027586937,
0.07334235310554504,
0.06800518929958344,
-0.014248923398554325,
-0.10930466651916504,
-0.20309224724769592,
-0.09362411499023438,
0.031776297837495804,
0.1260126680135727,
-0.0035194922238588333,
0.14095202088356018,
0.004996126517653465,
-0.024518582969903946,
0.0602169930934906,
-0.05193958804011345,
-0.09717001765966415,
-0.04269973933696747,
-0.013077879324555397,
0.009984727948904037,
-0.010865048505365849,
-0.07929787784814835,
-0.10867930948734283,
-0.07145719230175018,
0.13805073499679565,
0.03187691047787666,
-0.04535909369587898,
-0.1312079131603241,
0.07708505541086197,
0.12211129069328308,
-0.07588578760623932,
0.041594378650188446,
0.012465259991586208,
0.08016320317983627,
0.014399155974388123,
-0.02115328051149845,
0.12794926762580872,
-0.057467248290777206,
-0.22180406749248505,
-0.05683233588933945,
0.12360261380672455,
0.04965651407837868,
0.05436737835407257,
-0.01692219264805317,
0.047993581742048264,
0.028447842225432396,
-0.08270122110843658,
0.04042234644293785,
-0.018087884411215782,
0.087766133248806,
0.030261937528848648,
-0.019101710990071297,
0.009482746943831444,
-0.06509463489055634,
-0.015040659345686436,
0.10490422695875168,
0.3714883327484131,
-0.07300012558698654,
0.022721080109477043,
0.0800122544169426,
-0.03702834993600845,
-0.14938710629940033,
0.04348227009177208,
0.05146654322743416,
-0.01183029543608427,
0.03682485967874527,
-0.13047659397125244,
0.08393555879592896,
0.09369207173585892,
-0.038301821798086166,
0.08747837692499161,
-0.28294849395751953,
-0.14467135071754456,
0.07737831026315689,
0.16140545904636383,
0.07835153490304947,
-0.17779625952243805,
-0.026501351967453957,
-0.018479397520422935,
-0.11485666781663895,
0.09996496140956879,
-0.15892447531223297,
0.10266802459955215,
-0.012589695863425732,
0.06516216695308685,
0.022168349474668503,
-0.06528551876544952,
0.13070814311504364,
0.007214797660708427,
0.1294303983449936,
-0.03593287244439125,
-0.008832396008074284,
0.08151046186685562,
-0.07041081041097641,
0.017751870676875114,
-0.045693594962358475,
0.028698250651359558,
-0.03042597323656082,
-0.007625414989888668,
-0.0785134807229042,
0.0189108457416296,
-0.042738109827041626,
-0.050207532942295074,
-0.03789832442998886,
0.04254413768649101,
0.04939647018909454,
-0.021871816366910934,
0.16525952517986298,
0.002773402724415064,
0.1905813217163086,
0.14064954221248627,
0.05916231870651245,
-0.07051535695791245,
-0.0013130810111761093,
0.03356678783893585,
-0.028859397396445274,
0.03207780793309212,
-0.14847208559513092,
0.033341117203235626,
0.12456843256950378,
0.032810550183057785,
0.11151115596294403,
0.06464104354381561,
-0.0625620037317276,
0.019588882103562355,
0.07445698231458664,
-0.15954644978046417,
-0.09050995856523514,
0.03957831859588623,
-0.015398452989757061,
-0.12784238159656525,
0.07861503958702087,
0.11915480345487595,
-0.05640444904565811,
-0.013604022562503815,
-0.018292633816599846,
0.03311097249388695,
-0.030305296182632446,
0.23147815465927124,
0.06089083477854729,
0.06894610822200775,
-0.11597662419080734,
0.08840802311897278,
0.047865331172943115,
-0.08123999834060669,
0.02681831642985344,
0.10346807539463043,
-0.09022610634565353,
-0.017654644325375557,
0.09838152676820755,
0.1680942177772522,
-0.047532353550195694,
-0.035568125545978546,
-0.17551365494728088,
-0.11750832200050354,
0.04813382402062416,
0.21681199967861176,
0.0715818703174591,
0.0012553783599287271,
0.01636253111064434,
0.014655154198408127,
-0.1315307766199112,
0.09762000292539597,
0.061922430992126465,
0.09698402881622314,
-0.12494807690382004,
0.14450260996818542,
-0.009493572637438774,
0.00701083755120635,
-0.019659385085105896,
0.04916924238204956,
-0.13875707983970642,
0.010421876795589924,
-0.12605221569538116,
-0.017394019290804863,
-0.04159634932875633,
-0.008135350421071053,
-0.016320262104272842,
-0.05543189495801926,
-0.07267072796821594,
0.012626571580767632,
-0.1205657348036766,
-0.019847240298986435,
0.01973610743880272,
0.018568340688943863,
-0.1570180356502533,
-0.032926589250564575,
0.018552303314208984,
-0.08146451413631439,
0.0684545487165451,
0.04898814111948013,
0.034081749618053436,
0.04709042236208916,
-0.14288640022277832,
-0.006453533191233873,
0.05647094547748566,
-0.03335551545023918,
0.08347437530755997,
-0.11484596133232117,
-0.030153373256325722,
-0.026678532361984253,
0.06424564868211746,
0.024734482169151306,
0.09343128651380539,
-0.12205830216407776,
0.021064219996333122,
-0.01143229566514492,
-0.061510007828474045,
-0.03081655316054821,
0.015643687918782234,
0.08149343729019165,
-0.002156487200409174,
0.1471039056777954,
-0.0910787284374237,
0.026394322514533997,
-0.21058566868305206,
-0.024337122216820717,
-0.014312089420855045,
-0.1096659004688263,
-0.0986788272857666,
-0.015373952686786652,
0.09001223742961884,
-0.05895550549030304,
0.10235406458377838,
-0.0047234827652573586,
0.08777425438165665,
0.045504987239837646,
-0.05633498355746269,
0.012446807697415352,
0.047888267785310745,
0.14500856399536133,
0.02391061931848526,
-0.0474252849817276,
0.07926616072654724,
0.04292312636971474,
0.09632499516010284,
0.06453582644462585,
0.2514524459838867,
0.1484823077917099,
0.02364741452038288,
0.0853375717997551,
0.044809602200984955,
-0.08847355842590332,
-0.12115660309791565,
0.053880587220191956,
-0.05519057810306549,
0.08225739002227783,
-0.019597128033638,
0.1611383557319641,
0.10803031176328659,
-0.17801085114479065,
0.019542304798960686,
-0.0627870261669159,
-0.08290377259254456,
-0.11579545587301254,
0.001975939841940999,
-0.10117780417203903,
-0.1682916283607483,
0.010016565211117268,
-0.11898840218782425,
0.03298327699303627,
0.10612629354000092,
0.008632706478238106,
0.03232010081410408,
0.18230058252811432,
0.05422457307577133,
0.058749206364154816,
0.03525203466415405,
0.028292693197727203,
-0.03156431391835213,
-0.0031727412715554237,
-0.09157124906778336,
0.021028747782111168,
-0.036116719245910645,
0.024167561903595924,
-0.03514910489320755,
-0.061276305466890335,
0.0638279914855957,
0.017534060403704643,
-0.1190965548157692,
0.025296326726675034,
0.030598238110542297,
0.08628664165735245,
0.0244135744869709,
0.02075350098311901,
0.020462900400161743,
-0.017349770292639732,
0.22935211658477783,
-0.07006718218326569,
-0.07009091228246689,
-0.10005651414394379,
0.28028759360313416,
0.02918637916445732,
-0.004716056399047375,
0.010179903358221054,
-0.09919747710227966,
0.005447613075375557,
0.12999102473258972,
0.17001229524612427,
-0.0755796954035759,
-0.00016370286175515503,
-0.03943261504173279,
-0.01634262315928936,
-0.049382735043764114,
0.09923583269119263,
0.10075278580188751,
0.01942935213446617,
-0.0959935262799263,
-0.019334755837917328,
-0.04961666464805603,
-0.03948334977030754,
-0.04398879036307335,
0.031369466334581375,
0.03579723834991455,
0.026701882481575012,
-0.049508728086948395,
0.08368946611881256,
-0.04552657529711723,
-0.12087732553482056,
0.06846478581428528,
-0.22489137947559357,
-0.16974610090255737,
-0.024043481796979904,
0.0651073232293129,
0.014828763902187347,
0.06924214959144592,
-0.030456911772489548,
-0.0347447469830513,
0.07869503647089005,
-0.023989200592041016,
-0.04889616742730141,
-0.133991539478302,
0.08129660785198212,
-0.14245975017547607,
0.2255001664161682,
-0.039094023406505585,
0.045402683317661285,
0.12820833921432495,
0.0138566168025136,
-0.10804466903209686,
0.06926940381526947,
0.06614594906568527,
-0.13567793369293213,
0.00853003654628992,
0.1425851583480835,
-0.055498912930488586,
0.09122075885534286,
0.04393570497632027,
-0.13504184782505035,
0.015514581464231014,
-0.03767974302172661,
-0.045017559081315994,
-0.04230313375592232,
-0.04449157044291496,
-0.055111128836870193,
0.12217271327972412,
0.1901000738143921,
-0.04845716059207916,
0.04943060502409935,
-0.0410175621509552,
0.04231175407767296,
0.08057685196399689,
0.04399806261062622,
-0.0351191870868206,
-0.2995660901069641,
0.05437843129038811,
0.12715238332748413,
-0.007604022044688463,
-0.25904324650764465,
-0.07302914559841156,
0.017237728461623192,
-0.041076935827732086,
-0.09181354939937592,
0.09426617622375488,
0.07495232671499252,
0.05871092900633812,
-0.05815204977989197,
-0.1253296434879303,
-0.07490982860326767,
0.17812412977218628,
-0.15707096457481384,
-0.09854443371295929
] |
null | null | transformers | # .samplemodel
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using teknium/OpenHermes-2.5-Mistral-7B as a base.
### Models Merged
The following models were included in the merge:
* Open-Orca/Mistral-7B-OpenOrca
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
weight: 1.0
- model: Open-Orca/Mistral-7B-OpenOrca
parameters:
weight: 0.6
merge_method: task_arithmetic
base_model: teknium/OpenHermes-2.5-Mistral-7B
dtype: float16
``` | {"license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": []} | text-generation | giraffe176/Open_Hermes_Orca_Mistral-7B | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2212.04089",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T05:00:16+00:00 | [
"2212.04089"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #conversational #arxiv-2212.04089 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # .samplemodel
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the task arithmetic merge method using teknium/OpenHermes-2.5-Mistral-7B as a base.
### Models Merged
The following models were included in the merge:
* Open-Orca/Mistral-7B-OpenOrca
### Configuration
The following YAML configuration was used to produce this model:
| [
"# .samplemodel\n\nThis is a merge of pre-trained language models created using mergekit.",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the task arithmetic merge method using teknium/OpenHermes-2.5-Mistral-7B as a base.",
"### Models Merged\n\nThe following models were included in the merge:\n* Open-Orca/Mistral-7B-OpenOrca",
"### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #mergekit #merge #conversational #arxiv-2212.04089 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# .samplemodel\n\nThis is a merge of pre-trained language models created using mergekit.",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the task arithmetic merge method using teknium/OpenHermes-2.5-Mistral-7B as a base.",
"### Models Merged\n\nThe following models were included in the merge:\n* Open-Orca/Mistral-7B-OpenOrca",
"### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
75,
22,
4,
37,
29,
17
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #mergekit #merge #conversational #arxiv-2212.04089 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# .samplemodel\n\nThis is a merge of pre-trained language models created using mergekit.## Merge Details### Merge Method\n\nThis model was merged using the task arithmetic merge method using teknium/OpenHermes-2.5-Mistral-7B as a base.### Models Merged\n\nThe following models were included in the merge:\n* Open-Orca/Mistral-7B-OpenOrca### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
-0.09901755303144455,
-0.07782027870416641,
-0.000589804956689477,
0.018579542636871338,
0.07760039716959,
0.049179814755916595,
0.1859860122203827,
0.0482967384159565,
0.1038186177611351,
-0.0075602722354233265,
0.032181426882743835,
0.06485921889543533,
0.030894028022885323,
0.2148968130350113,
-0.11371921002864838,
-0.21448516845703125,
0.06423255801200867,
-0.02843611128628254,
-0.13560372591018677,
0.08033885806798935,
0.1283010095357895,
-0.014930574223399162,
0.07623181492090225,
0.015753185376524925,
-0.1272299736738205,
0.016510862857103348,
-0.010436875745654106,
-0.008312524296343327,
0.10285286605358124,
0.15379749238491058,
0.05917494371533394,
0.02054627425968647,
-0.010224232450127602,
-0.09931185841560364,
0.0503411702811718,
-0.028403153643012047,
0.0059818970039486885,
0.05393094941973686,
0.03400146961212158,
-0.013316934928297997,
0.12310276925563812,
-0.026140395551919937,
0.010463572107255459,
0.08857250213623047,
-0.10998962074518204,
-0.12538979947566986,
-0.07610520720481873,
0.042598430067300797,
0.1415274292230606,
0.020162861794233322,
-0.006913929246366024,
0.09275832027196884,
0.04767221957445145,
0.0800803154706955,
-0.051914796233177185,
-0.29137399792671204,
-0.024336088448762894,
0.18092374503612518,
0.08282234519720078,
-0.039611492305994034,
0.0301275122910738,
0.002991307061165571,
0.0746026337146759,
-0.018871918320655823,
0.013908278197050095,
-0.05069200322031975,
0.07588499039411545,
-0.1061074435710907,
-0.11993918567895889,
0.007255328819155693,
0.1642344444990158,
0.05232701078057289,
-0.014218415133655071,
-0.11934812366962433,
-0.152994766831398,
0.10208461433649063,
-0.011696546338498592,
-0.03617558255791664,
0.01749185286462307,
0.05649108439683914,
0.13570097088813782,
-0.06410331279039383,
-0.06555194407701492,
0.0011469359742477536,
-0.18414387106895447,
0.15397797524929047,
0.007928495295345783,
0.04475417733192444,
-0.07557270675897598,
0.02926243469119072,
-0.20313438773155212,
-0.11385950446128845,
-0.00851777009665966,
-0.06731361150741577,
-0.03838721290230751,
-0.03334785997867584,
-0.12265706807374954,
-0.16929534077644348,
0.08799570053815842,
0.19144904613494873,
-0.08155117183923721,
0.015764273703098297,
0.04346207156777382,
0.08789854496717453,
0.05142031982541084,
-0.019731763750314713,
-0.11676401644945145,
-0.12576070427894592,
0.08002763241529465,
-0.018433578312397003,
0.11097005754709244,
0.00843864306807518,
-0.13844746351242065,
-0.026274440810084343,
-0.081724613904953,
0.0002965178864542395,
0.04216152802109718,
0.10056858509778976,
-0.042520709335803986,
-0.0709441527724266,
0.21660763025283813,
-0.04708505794405937,
0.025047915056347847,
-0.0085533382371068,
-0.020496807992458344,
-0.009566773660480976,
0.1267860382795334,
0.08556614816188812,
0.04718481004238129,
-0.004248339682817459,
-0.0421425998210907,
-0.02503194287419319,
-0.04814589023590088,
-0.10422055423259735,
0.0045846328139305115,
0.0005558964912779629,
0.008482697419822216,
-0.13233251869678497,
-0.22597476840019226,
-0.013834991492331028,
0.08194825053215027,
-0.05505278706550598,
-0.034365464001894,
-0.04329407587647438,
0.02831154502928257,
-0.021990954875946045,
-0.016927996650338173,
-0.028651025146245956,
-0.01309297140687704,
-0.05779219791293144,
-0.029311075806617737,
0.054374270141124725,
-0.25957828760147095,
0.020797107368707657,
-0.12475815415382385,
0.10724043846130371,
-0.14745604991912842,
0.113771952688694,
0.015330205671489239,
0.0824539065361023,
-0.09665805846452713,
0.024420227855443954,
-0.010111802257597446,
0.006867734249681234,
0.07129841297864914,
0.16459137201309204,
-0.0948873832821846,
-0.04589390009641647,
0.10673116892576218,
-0.1223677545785904,
-0.166148379445076,
0.11741583794355392,
-0.018386073410511017,
0.16000956296920776,
0.031605858355760574,
0.1946292370557785,
0.1001536026597023,
0.036614831537008286,
0.040150176733732224,
0.0009675425826571882,
-0.003757825121283531,
-0.02622014470398426,
0.07637924700975418,
-0.010992131195962429,
-0.1168026477098465,
0.032112665474414825,
0.026368264108896255,
0.14124755561351776,
-0.03579830750823021,
-0.06332092732191086,
-0.07249070703983307,
-0.07517681270837784,
0.10081326961517334,
-0.039933204650878906,
0.04302710294723511,
-0.05989356338977814,
-0.00029298823210410774,
0.07048077881336212,
0.09137527644634247,
-0.06624426692724228,
0.0025891729164868593,
-0.044865675270557404,
0.08699947595596313,
-0.12963786721229553,
0.04789166897535324,
-0.1179201677441597,
-0.047947052866220474,
-0.027163445949554443,
-0.03364087641239166,
0.02013907954096794,
0.05362255871295929,
0.08940991759300232,
0.03956161439418793,
-0.041024237871170044,
-0.00061490957159549,
0.14778007566928864,
0.053106117993593216,
-0.04366680979728699,
-0.1839832216501236,
-0.07787932455539703,
-0.08796367794275284,
0.3173084259033203,
-0.11378873139619827,
0.07186571508646011,
-0.1092018336057663,
0.19065749645233154,
-0.018639249727129936,
0.06840980798006058,
0.03807270526885986,
0.024607118219137192,
-0.05876806378364563,
0.0008632858516648412,
0.08162056654691696,
0.06002617999911308,
-0.19450858235359192,
0.1689920574426651,
-0.14606772363185883,
0.04334232211112976,
0.09416836500167847,
0.04306335747241974,
-0.019544357433915138,
-0.10473620146512985,
-0.022552456706762314,
-0.07555365562438965,
0.0885913074016571,
-0.05074499920010567,
0.09667473286390305,
0.014803553000092506,
0.12261925637722015,
-0.046263378113508224,
0.012988608330488205,
0.022487374022603035,
-0.07612477988004684,
-0.02818133495748043,
0.026758460327982903,
-0.041535861790180206,
-0.2583114802837372,
0.11405444145202637,
0.21853502094745636,
0.011857411824166775,
0.05206538736820221,
0.017811674624681473,
0.03681912273168564,
-0.06389705836772919,
-0.003229098627343774,
-0.015434153378009796,
-0.048464927822351456,
-0.09546612203121185,
0.06801068037748337,
0.06275030225515366,
0.0035512486938387156,
0.058549653738737106,
-0.053737711161375046,
0.04588855057954788,
0.07039824873209,
0.026027129963040352,
0.07355421781539917,
0.11283843964338303,
-0.020017795264720917,
0.052906665951013565,
0.01662205345928669,
-0.0887720137834549,
0.06816045939922333,
0.006971487309783697,
-0.14501002430915833,
0.1601497381925583,
-0.11334843933582306,
-0.15713900327682495,
-0.16812290251255035,
-0.08746247738599777,
-0.11639750003814697,
-0.013132095336914062,
0.07495282590389252,
0.0647314190864563,
-0.053555261343717575,
-0.11340681463479996,
0.0677676647901535,
0.07099422812461853,
-0.02234150841832161,
0.022278698161244392,
-0.014574084430932999,
0.006127330474555492,
-0.08117302507162094,
-0.023636963218450546,
0.0034796944819390774,
-0.04043705388903618,
0.07066334038972855,
-0.10631685703992844,
0.091530442237854,
0.1671265959739685,
-0.03158577159047127,
-0.031800493597984314,
-0.023684244602918625,
0.1533653438091278,
-0.002372011076658964,
0.10226336866617203,
0.15473927557468414,
-0.12065070122480392,
0.04488462954759598,
0.2777252495288849,
0.028831077739596367,
-0.0384802520275116,
0.01000648457556963,
-0.07835781574249268,
-0.05644041672348976,
-0.1637255698442459,
-0.16171135008335114,
-0.11331743001937866,
0.014756232500076294,
0.004564529284834862,
0.024289807304739952,
0.12802599370479584,
0.07691142708063126,
-0.04905278608202934,
-0.036401260644197464,
0.0426260381937027,
0.061153557151556015,
0.19814790785312653,
0.0021236150059849024,
0.10100797563791275,
-0.053299304097890854,
0.022759171202778816,
0.08197824656963348,
-0.004851324018090963,
0.14516161382198334,
0.09977863729000092,
0.11239998042583466,
0.0765700563788414,
-0.016292324289679527,
0.04966980963945389,
0.0816492959856987,
-0.03265334293246269,
0.011188789270818233,
-0.040590688586235046,
-0.09351057559251785,
0.0061234645545482635,
0.10154072195291519,
-0.09502211958169937,
0.10046124458312988,
-0.07215304672718048,
-0.008762071840465069,
0.07559575885534286,
0.18403112888336182,
0.11530763655900955,
-0.2950884997844696,
-0.13408151268959045,
0.05958406254649162,
0.021488774567842484,
-0.010327987372875214,
-0.03151596337556839,
-0.005267353728413582,
-0.05579087510704994,
0.17760270833969116,
-0.02978668361902237,
0.11385486274957657,
0.060512229800224304,
-0.012942906469106674,
-0.06050604581832886,
0.08920637518167496,
0.019333265721797943,
0.04768559709191322,
-0.15706287324428558,
0.19324944913387299,
-0.003152139950543642,
-0.013978187926113605,
0.0024523832835257053,
0.025573566555976868,
0.04249270260334015,
0.2483612447977066,
0.020878806710243225,
-0.010014520958065987,
0.02276580035686493,
0.01866224780678749,
-0.09323368966579437,
0.026464184746146202,
-0.07235366851091385,
-0.028219154104590416,
0.06981290131807327,
-0.04957050830125809,
-0.049652498215436935,
0.03328225016593933,
0.17017529904842377,
-0.08472226560115814,
-0.13386929035186768,
0.024679450318217278,
0.11287610232830048,
0.044001005589962006,
-0.04379438981413841,
-0.013023854233324528,
-0.10189031064510345,
0.2518129348754883,
0.037184104323387146,
-0.093771792948246,
-0.0787714496254921,
-0.02660575695335865,
0.11684970557689667,
-0.05363980308175087,
0.07843092083930969,
-0.04542597010731697,
0.06239303946495056,
-0.06957004964351654,
-0.1879771202802658,
0.13427342474460602,
-0.1143292561173439,
-0.02450556866824627,
-0.014657034538686275,
0.034407734870910645,
-0.06023438647389412,
0.00382609642110765,
0.026231827214360237,
0.05032641813158989,
-0.07561139017343521,
-0.0346897728741169,
-0.058677785098552704,
0.22301602363586426,
-0.004656166769564152,
0.07358995079994202,
-0.0484665185213089,
-0.2336108535528183,
0.02617613971233368,
-0.02443714626133442,
0.1553940773010254,
0.2539485692977905,
-0.06810658425092697,
0.07341239601373672,
0.19524414837360382,
-0.06887988746166229,
-0.16902703046798706,
-0.04500509425997734,
-0.038487508893013,
0.06650925427675247,
0.005329559091478586,
0.014131144620478153,
0.05327148362994194,
0.0988331139087677,
-0.020953074097633362,
0.013528121635317802,
-0.302822083234787,
-0.1586271971464157,
0.0883614644408226,
0.025438405573368073,
0.27141475677490234,
-0.10127735137939453,
-0.05879770964384079,
-0.09131425619125366,
-0.1868750900030136,
0.014181549660861492,
-0.17024636268615723,
0.05675908550620079,
0.004082570783793926,
-0.02435508370399475,
0.008354216814041138,
-0.03463226929306984,
0.162775918841362,
-0.05800822377204895,
0.03177662938833237,
-0.08970130234956741,
-0.002024930901825428,
0.1016741618514061,
-0.055524472147226334,
0.10995916277170181,
-0.06743903458118439,
0.024071624502539635,
0.0030501862056553364,
-0.05120968073606491,
-0.019674673676490784,
0.05677877366542816,
0.002130939858034253,
-0.06885726749897003,
-0.029393263161182404,
0.025511162355542183,
0.012605177238583565,
0.02410789765417576,
0.1343337595462799,
-0.05756250023841858,
0.1347944140434265,
0.24225790798664093,
0.12183238565921783,
-0.145459845662117,
0.0611078143119812,
0.0157417431473732,
-0.0923333615064621,
0.06279206275939941,
-0.10522863268852234,
-0.0074156844057142735,
0.10913117974996567,
-0.023258447647094727,
0.09045761823654175,
0.03034263290464878,
0.00772105623036623,
0.04370759800076485,
0.07916709780693054,
-0.11300408095121384,
-0.27885690331459045,
0.005521649960428476,
0.05661705136299133,
-0.041867971420288086,
0.08051984757184982,
0.19603659212589264,
-0.08253754675388336,
-0.004610468167811632,
0.03048691898584366,
0.014503318816423416,
-0.12426602840423584,
0.058041706681251526,
-0.03451213985681534,
-0.008350500836968422,
-0.08337824046611786,
0.04195227846503258,
0.07668720930814743,
-0.0930512547492981,
-0.02391865663230419,
0.06817033886909485,
-0.12965849041938782,
-0.08689718693494797,
-0.10962025076150894,
0.18741275370121002,
-0.10416118800640106,
-0.09230941534042358,
-0.07053983211517334,
-0.11696244031190872,
-0.004179882816970348,
0.09398824721574783,
0.09291554242372513,
0.009162683971226215,
-0.02199023962020874,
-0.05766591802239418,
-0.046460215002298355,
0.058305077254772186,
0.04480446130037308,
0.08577219396829605,
-0.09074821323156357,
0.01731097884476185,
-0.03582930937409401,
0.04365937039256096,
-0.05908854678273201,
-0.03862285241484642,
-0.08687455952167511,
-0.030525894835591316,
-0.19498710334300995,
-0.004922774620354176,
-0.16048911213874817,
-0.02238290011882782,
0.005887533538043499,
-0.055196162313222885,
-0.03126759082078934,
0.02252155914902687,
-0.015490426681935787,
-0.019458023831248283,
-0.03867065906524658,
0.02309705689549446,
-0.0710018202662468,
-0.07151859998703003,
-0.01575334556400776,
-0.0428447350859642,
0.07466846704483032,
0.03983093425631523,
-0.07693307846784592,
-0.08272050321102142,
-0.1600506454706192,
-0.05166342109441757,
0.08394063264131546,
0.01293492317199707,
0.036451682448387146,
-0.13131025433540344,
-0.04489367827773094,
0.07222011685371399,
-0.030039476230740547,
-0.03605722263455391,
0.06753809005022049,
-0.04636465013027191,
0.02212701551616192,
-0.025014284998178482,
-0.023931926116347313,
-0.012530787847936153,
-0.04229980334639549,
0.015194538049399853,
0.09196686744689941,
0.12505367398262024,
-0.050478022545576096,
0.04192585498094559,
-0.14861960709095,
-0.035734567791223526,
-0.019629616290330887,
-0.10022367537021637,
-0.05707414075732231,
-0.0891832634806633,
-0.018025651574134827,
-0.004858420230448246,
0.1677156388759613,
-0.0037329974584281445,
-0.06502299755811691,
0.035808440297842026,
-0.030102530494332314,
0.08874697983264923,
0.03713084012269974,
0.25779327750205994,
0.04058254510164261,
0.03213343024253845,
-0.08868007361888885,
0.09934637695550919,
0.010258762165904045,
-0.01993025280535221,
0.0548766665160656,
0.03148461878299713,
0.022687658667564392,
0.08132395893335342,
0.06357850134372711,
0.02188381552696228,
-0.003145977621898055,
-0.12421216070652008,
0.007892048917710781,
0.04313715174794197,
-0.010907575488090515,
0.09918539226055145,
0.15209396183490753,
-0.13167716562747955,
0.06034724414348602,
0.023186279460787773,
-0.018042493611574173,
-0.08599415421485901,
-0.05755351111292839,
-0.11196623742580414,
-0.1564132273197174,
-0.09777818620204926,
-0.06761907786130905,
-0.06267275661230087,
-0.015596775338053703,
0.006414895411580801,
-0.007605778053402901,
0.12098081409931183,
-0.03144221007823944,
-0.011899991892278194,
0.006940615363419056,
-0.04638396203517914,
0.015917569398880005,
-0.04187647998332977,
-0.05118132755160332,
0.037758372724056244,
0.0044610402546823025,
-0.028173862025141716,
0.07380963116884232,
0.05681595206260681,
0.05755665898323059,
-0.042766377329826355,
-0.07616131752729416,
-0.0372464694082737,
0.08046465367078781,
0.009822525084018707,
-0.01800299808382988,
0.07148051261901855,
-0.020691413432359695,
0.02893783710896969,
0.06516988575458527,
-0.037350449711084366,
-0.12261075526475906,
-0.13454662263393402,
0.22770275175571442,
-0.062139689922332764,
0.03901747614145279,
0.024034613743424416,
-0.07705550640821457,
0.01171020045876503,
0.0987047553062439,
0.3160442113876343,
-0.04089323803782463,
-0.0039002052508294582,
0.013826549984514713,
0.002274526050314307,
-0.002453327877447009,
0.06818938255310059,
0.004464063793420792,
0.18595711886882782,
-0.06123152747750282,
0.1013636663556099,
-0.01053441222757101,
-0.06684274226427078,
-0.06498436629772186,
-0.02837320975959301,
-0.04013912007212639,
-0.059062615036964417,
0.05290369689464569,
0.09266848862171173,
-0.05375237762928009,
0.03202123939990997,
0.0016067755641415715,
-0.11550960689783096,
-0.07384602725505829,
-0.07851086556911469,
0.07401830703020096,
0.008842356503009796,
0.06615869700908661,
-0.07545597106218338,
-0.011814791709184647,
0.20190571248531342,
-0.026260225102305412,
-0.04711996763944626,
-0.08291500806808472,
0.04507265239953995,
-0.04554111883044243,
-0.004175127483904362,
-0.022457823157310486,
0.06450333446264267,
0.10316045582294464,
0.02597893215715885,
-0.12746873497962952,
-0.023727837949991226,
0.025174932554364204,
0.057774923741817474,
0.08721710741519928,
-0.08453436940908432,
-0.04944359511137009,
0.04020283743739128,
0.040494635701179504,
-0.19596660137176514,
0.03648536652326584,
0.047197598963975906,
-0.08499925583600998,
-0.07140997797250748,
0.07367926090955734,
-0.02474506013095379,
0.12876367568969727,
0.10082656145095825,
-0.06934521347284317,
-0.0022497321479022503,
0.01046824548393488,
0.049529071897268295,
0.08625126630067825,
0.0867830216884613,
-0.04312244430184364,
-0.19081497192382812,
0.01571984775364399,
0.05934640392661095,
0.08911016583442688,
-0.254197895526886,
-0.09626537561416626,
-0.12187609076499939,
-0.03386928513646126,
-0.02206837758421898,
0.06734702736139297,
0.1763065904378891,
0.005701988469809294,
-0.028782662004232407,
-0.15044069290161133,
-0.012103904969990253,
0.0930519700050354,
-0.06592854112386703,
-0.10817448049783707
] |
null | null | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="sanchitkalra/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
| {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": "FrozenLake-v1-4x4-no_slippery"}, "metrics": [{"type": "mean_reward", "value": "1.00 +/- 0.00", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | sanchitkalra/q-FrozenLake-v1-4x4-noSlippery | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | 2024-02-11T05:02:08+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
| [
"# Q-Learning Agent playing1 FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n\n ## Usage"
] | [
"TAGS\n#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n",
"# Q-Learning Agent playing1 FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n\n ## Usage"
] | [
40,
39
] | [
"passage: TAGS\n#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n# Q-Learning Agent playing1 FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n\n ## Usage"
] | [
0.04578453302383423,
-0.08074592798948288,
-0.00430759321898222,
0.10720831900835037,
0.05034215748310089,
-0.040469273924827576,
0.11997015029191971,
0.018999949097633362,
0.20601962506771088,
-0.010012076236307621,
0.1455274522304535,
0.007022971753031015,
-0.006192410364747047,
0.1867983490228653,
0.04572829231619835,
-0.26324528455734253,
0.01831899583339691,
-0.09495259821414948,
-0.07281816750764847,
0.11870454251766205,
0.05470194295048714,
-0.01901467889547348,
-0.0007633853238075972,
0.056141503155231476,
-0.0673527717590332,
0.0007737681735306978,
0.031996939331293106,
-0.012976245954632759,
0.19804789125919342,
-0.02254498563706875,
0.06641989201307297,
0.054705578833818436,
0.0758768692612648,
-0.1998077929019928,
0.0358855277299881,
-0.04215473681688309,
-0.09439758956432343,
-0.03934839740395546,
-0.018780618906021118,
0.05878105387091637,
0.053356342017650604,
0.03858819976449013,
0.058354366570711136,
0.09384993463754654,
-0.0773480236530304,
0.04328357055783272,
0.04280758649110794,
0.024811049923300743,
0.04589218273758888,
-0.0237203948199749,
-0.027002155780792236,
0.08246652781963348,
-0.22182892262935638,
0.10318073630332947,
-0.010159241035580635,
-0.5270710587501526,
-0.00633762264624238,
0.24088262021541595,
0.11517096310853958,
0.05707438662648201,
-0.06903956830501556,
0.10566288232803345,
0.03913382440805435,
-0.007209456991404295,
0.03210983797907829,
0.02150118350982666,
0.12817370891571045,
0.06009242683649063,
-0.09581366181373596,
0.040699947625398636,
0.13722525537014008,
0.012822695076465607,
0.020306183025240898,
-0.08888901025056839,
0.0410032719373703,
-0.03461858257651329,
-0.007679527159780264,
-0.09758518636226654,
0.05478060990571976,
0.012466507963836193,
-0.0934976264834404,
-0.09247440844774246,
-0.04236573353409767,
-0.06708304584026337,
0.11252415925264359,
0.046419668942689896,
-0.0874939113855362,
0.03884070739150047,
-0.06760413944721222,
0.05918780341744423,
-0.16863860189914703,
0.02074250765144825,
-0.06627868115901947,
-0.09376336634159088,
-0.11799788475036621,
-0.01683047041296959,
-0.07946427166461945,
0.009092256426811218,
0.056664444506168365,
0.1447116881608963,
0.22076484560966492,
0.06690320372581482,
0.09728849679231644,
0.07456006109714508,
0.06531001627445221,
0.1538129299879074,
0.10918238013982773,
0.019075315445661545,
-0.015266558155417442,
0.0948706716299057,
-0.06445580720901489,
-0.1351388692855835,
-0.15579092502593994,
0.005488025024533272,
0.0983937531709671,
0.08871900290250778,
-0.044080477207899094,
-0.006702381651848555,
-0.024641724303364754,
0.08566431701183319,
-0.11314457654953003,
-0.024612564593553543,
-0.002267979085445404,
0.06882024556398392,
-0.024801667779684067,
0.020378148183226585,
-0.06242705136537552,
0.12715265154838562,
0.04222423583269119,
-0.059924717992544174,
-0.055308472365140915,
-0.03053177334368229,
-0.014276440255343914,
-0.027539284899830818,
0.02446848154067993,
-0.07659092545509338,
0.04767750948667526,
-0.16766095161437988,
-0.042871296405792236,
-0.04784649610519409,
0.025697942823171616,
-0.03907240927219391,
-0.13557587563991547,
-0.17699143290519714,
-0.048906855285167694,
-0.022438718006014824,
0.03549358621239662,
-0.038111843168735504,
0.006551501806825399,
-0.006318534724414349,
-0.1583600640296936,
0.09783563017845154,
0.09784027189016342,
-0.03643378987908363,
-0.02749447710812092,
0.056263517588377,
-0.07194498926401138,
0.1561182290315628,
-0.21054518222808838,
-0.054014235734939575,
-0.044764336198568344,
-0.06595750898122787,
0.19673264026641846,
0.012690845876932144,
-0.01202624011784792,
0.19873127341270447,
-0.29073721170425415,
-0.06078760325908661,
0.12533614039421082,
-0.07834373414516449,
-0.0936407670378685,
0.06941844522953033,
-0.04206686094403267,
0.023345354944467545,
0.046047765761613846,
0.36345911026000977,
-0.02069227211177349,
-0.16197136044502258,
-0.021782705560326576,
0.13971707224845886,
-0.1184760183095932,
0.059895481914281845,
0.04240793362259865,
0.12543781101703644,
-0.04250509291887283,
-0.018672896549105644,
-0.09023164212703705,
0.05999075248837471,
-0.05241934582591057,
-0.09016361832618713,
-0.03393383324146271,
-0.07645075023174286,
0.13294468820095062,
-0.0629684180021286,
0.05601520463824272,
-0.03255095332860947,
-0.07133250683546066,
-0.050324998795986176,
-0.016492370516061783,
0.04460815340280533,
0.05951254442334175,
-0.12794871628284454,
0.11029167473316193,
0.13025271892547607,
-0.0006193425506353378,
-0.07498852163553238,
-0.17872096598148346,
0.003240168560296297,
0.009576505981385708,
0.039837226271629333,
0.17141658067703247,
0.12209978699684143,
0.033295199275016785,
0.008770671673119068,
-0.06389404833316803,
-0.18276847898960114,
0.058129217475652695,
-0.056212130934000015,
-0.14230976998806,
-0.052409034222364426,
-0.0728459507226944,
0.017381802201271057,
-0.0859743058681488,
-0.017379917204380035,
0.021926190704107285,
0.006908397190272808,
0.02990424446761608,
-0.026645656675100327,
-0.049561817198991776,
0.021254703402519226,
0.06490101665258408,
-0.0037617047782987356,
0.12023693323135376,
0.008277264423668385,
-0.18308481574058533,
0.07930773496627808,
0.08478537946939468,
0.09196605533361435,
0.013250201940536499,
0.02685922384262085,
-0.021522263064980507,
-0.08061408251523972,
-0.054420311003923416,
0.02957955375313759,
0.11417073011398315,
0.1317172348499298,
0.2361993044614792,
0.08753683418035507,
0.04697408527135849,
-0.02164587564766407,
-0.016415923833847046,
0.002810494042932987,
-0.06318057328462601,
-0.029935607686638832,
0.10614971816539764,
0.05865858122706413,
-0.067733034491539,
-0.04576427489519119,
0.09590928256511688,
0.02732124738395214,
0.21205885708332062,
-0.03342745825648308,
0.01286078616976738,
-0.10957037657499313,
-0.06550975888967514,
-0.031982194632291794,
0.09201868623495102,
0.09498392790555954,
0.009755023755133152,
-0.022056059911847115,
-0.04259001836180687,
0.0012916827108711004,
-0.1334889680147171,
-0.10375088453292847,
0.026475343853235245,
0.013400445692241192,
-0.11206940561532974,
0.11674030870199203,
-0.11352457851171494,
0.039504457265138626,
0.06024791672825813,
-0.13837239146232605,
0.04428480193018913,
-0.029713207855820656,
-0.07886212319135666,
0.16866780817508698,
-0.11075661331415176,
-0.094340018928051,
-0.08831550180912018,
0.004082420375198126,
0.0075836325995624065,
-0.03922267258167267,
-0.009283260442316532,
-0.19952571392059326,
-0.005375816952437162,
-0.03544965013861656,
0.013616434298455715,
-0.06988783925771713,
-0.11287739872932434,
-0.010957922786474228,
0.07084179669618607,
-0.043388739228248596,
-0.07803605496883392,
0.007967432029545307,
-0.08923084288835526,
-0.10623309016227722,
0.028189711272716522,
0.019765101373195648,
-0.022883659228682518,
0.16152891516685486,
0.01816628873348236,
0.05626589432358742,
-0.03298520669341087,
0.30665266513824463,
-0.038163769990205765,
0.08371731638908386,
-0.02993497997522354,
-0.07433546334505081,
0.06130730360746384,
-0.022327827289700508,
0.06086638569831848,
-0.020221687853336334,
-0.02362890914082527,
0.0077952733263373375,
-0.08579335361719131,
-0.18365982174873352,
-0.05417544022202492,
0.03724347800016403,
0.195254847407341,
0.031118987128138542,
0.01910330168902874,
-0.0488768145442009,
-0.010547760874032974,
0.1665220558643341,
-0.10005921125411987,
0.04030545800924301,
-0.05366240441799164,
0.11506262421607971,
-0.08640182018280029,
0.06195629760622978,
0.020486772060394287,
0.04266135022044182,
-0.04877188801765442,
0.09486009180545807,
0.0826394334435463,
0.1121082529425621,
-0.02206910029053688,
0.046257395297288895,
0.019012698903679848,
0.07383184134960175,
0.11073657125234604,
0.0368414968252182,
-0.0729052945971489,
0.001982470043003559,
-0.006313489284366369,
-0.039427030831575394,
0.11933320760726929,
0.17963355779647827,
-0.11991413682699203,
-0.05106910318136215,
0.27167606353759766,
0.0031242913100868464,
0.19481229782104492,
-0.01315275114029646,
0.043591804802417755,
-0.04484925419092178,
0.04572054371237755,
-0.05338600277900696,
-0.04086209088563919,
0.2094656229019165,
0.08045925945043564,
-0.17165091633796692,
-0.08549032360315323,
-0.05912299454212189,
0.07081323862075806,
0.10728751868009567,
0.0013539529172703624,
-0.04156802222132683,
0.0004610282776411623,
0.0014198932331055403,
0.08339415490627289,
-0.14520122110843658,
0.11816094070672989,
-0.03172019124031067,
0.05612684786319733,
0.017555562779307365,
-0.045326150953769684,
0.04264266416430473,
0.07474290579557419,
0.26618310809135437,
0.0904107540845871,
-0.040318213403224945,
-0.0892091691493988,
-0.12260187417268753,
0.010461576282978058,
0.029102616012096405,
-0.03534553572535515,
0.0037547778338193893,
-0.020087555050849915,
0.0318896509706974,
0.008264793083071709,
0.016230624169111252,
-0.08987458795309067,
-0.03175399824976921,
-0.027736429125070572,
-0.023839212954044342,
0.10733365267515182,
-0.09495144337415695,
-0.1444292515516281,
-0.15713949501514435,
0.04191131144762039,
-0.0766405463218689,
-0.056593164801597595,
-0.054507751017808914,
-0.05239389091730118,
-0.0311186034232378,
-0.03773957118391991,
0.09099467098712921,
-0.0021037792321294546,
0.14807306230068207,
-0.1920108050107956,
-0.04220759496092796,
0.051812779158353806,
-0.07607918977737427,
-0.08729588985443115,
0.03410962224006653,
0.12136995792388916,
0.05116051807999611,
0.11504370719194412,
0.013609255664050579,
0.09567681699991226,
0.0045484392903745174,
-0.06713183224201202,
0.15302421152591705,
-0.14069625735282898,
-0.27875974774360657,
-0.03836318850517273,
0.016946332529187202,
0.1615200787782669,
-0.05613167956471443,
0.031766023486852646,
0.3335736393928528,
0.27782970666885376,
-0.1428707242012024,
0.25916144251823425,
0.019178593531250954,
0.004398873541504145,
-0.19130495190620422,
-0.10125631093978882,
0.025324683636426926,
0.04740457236766815,
0.12032642960548401,
-0.14564448595046997,
-0.010732659138739109,
-0.04543145373463631,
-0.025908485054969788,
0.10386138409376144,
-0.12300799041986465,
-0.07263197749853134,
0.07765276730060577,
0.039809420704841614,
0.1808302253484726,
0.03932500258088112,
0.0014799144119024277,
0.13626977801322937,
0.06612244248390198,
0.019124457612633705,
0.05216038227081299,
0.08028066903352737,
-0.018944554030895233,
0.14207926392555237,
0.05448179319500923,
-0.02551644667983055,
0.052681710571050644,
-0.0054580713622272015,
-0.03219012916088104,
0.015605825930833817,
-0.183198019862175,
-0.10147556662559509,
-0.0561356320977211,
-0.10798973590135574,
-0.04978342354297638,
0.056853994727134705,
-0.12395523488521576,
-0.007896827533841133,
-0.03841273859143257,
0.03718273714184761,
-0.07831971347332001,
-0.09360362589359283,
-0.036494381725788116,
0.1351792961359024,
0.07210618257522583,
0.04471297934651375,
0.035655103623867035,
-0.07390819489955902,
0.07097936421632767,
0.21671734750270844,
0.08159157633781433,
0.028919655829668045,
-0.19545674324035645,
-0.024042490869760513,
-0.0803457647562027,
0.06306298077106476,
-0.08856996893882751,
-0.016788700595498085,
0.11923003196716309,
0.08616556972265244,
0.05413002520799637,
0.09640096127986908,
-0.045083072036504745,
0.021686913445591927,
0.02684609219431877,
-0.15131035447120667,
-0.18501274287700653,
-0.08534606546163559,
-0.03519878163933754,
0.11561143398284912,
-0.06398691236972809,
0.10897188633680344,
-0.13615410029888153,
0.010051886551082134,
-0.006060056854039431,
0.02693452313542366,
-0.03596206381917,
-0.11251141875982285,
0.15348562598228455,
0.11999429017305374,
-0.06767056882381439,
0.03127254918217659,
-0.09527092427015305,
-0.04423454403877258,
0.12686803936958313,
-0.013623855076730251,
-0.0371493324637413,
-0.054547641426324844,
-0.03628576174378395,
0.15247689187526703,
-0.03436964750289917,
0.008244883269071579,
-0.041229065507650375,
-0.18217355012893677,
0.0798322781920433,
0.09045056998729706,
0.019827889278531075,
-0.031874191015958786,
-0.09797266125679016,
-0.010231015272438526,
-0.0011165260802954435,
0.11730700731277466,
-0.10696814209222794,
-0.10933240503072739,
-0.15144047141075134,
0.06713984161615372,
-0.0007159380475059152,
0.18502596020698547,
-0.06394898891448975,
-0.08904669433832169,
-0.12429379671812057,
0.02344517596065998,
-0.0027384376153349876,
-0.042264558374881744,
0.01618490368127823,
0.07992301136255264,
-0.04095321521162987,
0.02075677551329136,
-0.06651144474744797,
0.06372585147619247,
-0.11786920577287674,
0.09625071287155151,
0.01063506118953228,
0.016993753612041473,
-0.0417880080640316,
-0.01618220843374729,
0.039470795542001724,
-0.057925306260585785,
0.07921463251113892,
0.011758086271584034,
0.0010938759660348296,
0.10196787863969803,
-0.0034960443153977394,
0.06409632414579391,
-0.05372481048107147,
-0.023290161043405533,
0.06578411161899567,
-0.05874887853860855,
-0.03370826691389084,
-0.1573946475982666,
-0.0709633082151413,
0.020051732659339905,
-0.04775108024477959,
0.002077929675579071,
0.03673801198601723,
0.062159497290849686,
-0.06937079131603241,
-0.12125655263662338,
-0.043812792748212814,
-0.028638383373618126,
0.021301284432411194,
0.10829301923513412,
-0.07526551932096481,
0.1547859013080597,
-0.052787959575653076,
-0.00020603960729204118,
0.07437096536159515,
0.04048224538564682,
0.01393822580575943,
-0.10422444343566895,
-0.04698587954044342,
-0.11035211384296417,
0.1502903699874878,
-0.007902312092483044,
-0.03533121198415756,
0.03719403222203255,
-0.11946307867765427,
-0.1572723090648651,
0.03418220207095146,
0.10199101269245148,
0.0448341928422451,
0.025807438418269157,
0.027079269289970398,
-0.04042419046163559,
-0.021270349621772766,
-0.07034418731927872,
0.0882953479886055,
-0.12085357308387756,
-0.09669415652751923,
0.09555385261774063,
0.12178351730108261,
-0.0036850625183433294,
-0.07441367954015732,
0.11554073542356491,
-0.021787192672491074,
0.05525410920381546,
-0.02971339225769043,
0.10308072715997696,
0.0796005055308342,
-0.12273547053337097,
0.005693064536899328,
-0.036891788244247437,
-0.0741485133767128,
-0.12975730001926422,
0.019545545801520348,
-0.061916105449199677,
-0.13383042812347412,
0.12179028987884521,
-0.09376577287912369,
0.030037038028240204,
-0.10506992787122726,
0.021338803693652153,
0.01864001713693142,
0.061665527522563934,
-0.10988292098045349,
0.08575301617383957,
0.13424484431743622,
-0.043199893087148666,
-0.07184189558029175,
-0.12455986440181732,
-0.05022053420543671,
-0.04231856390833855,
-0.13957437872886658,
-0.11600435525178909,
0.0100301094353199,
-0.023418782278895378,
-0.05818291753530502,
0.0015462689334526658,
-0.03659068048000336,
0.008594646118581295,
0.021907730028033257,
0.04032021388411522,
-0.02693161368370056,
0.05134565755724907,
-0.057569269090890884,
-0.052510857582092285,
0.11489357799291611,
0.04113486409187317,
-0.03561042994260788,
-0.052359987050294876,
0.12997733056545258,
-0.11959461867809296,
0.07662346214056015,
-0.020313527435064316,
0.017129231244325638,
-0.06435854732990265,
0.17131924629211426,
0.11673715710639954,
-0.1367570012807846,
-0.005008010193705559,
-0.08210669457912445,
0.020409544929862022,
0.023555370047688484,
0.13693512976169586,
-0.03411718085408211,
-0.0012358218664303422,
-0.1580323874950409,
0.018575575202703476,
-0.18557456135749817,
-0.03716109320521355,
0.04671547934412956,
0.09917585551738739,
0.15293832123279572,
-0.0034432117827236652,
-0.1263325810432434,
0.10424192249774933,
-0.2118520885705948,
0.0907607227563858,
0.05121984705328941,
-0.11874113976955414,
-0.06765396893024445,
-0.06795281916856766,
0.1198519766330719,
0.009196433238685131,
0.2040700763463974,
-0.013615905307233334,
-0.09132910519838333,
-0.07060808688402176,
-0.01980910450220108,
-0.030524181202054024,
0.09714830666780472,
0.041414931416511536,
0.04653804749250412,
0.12821412086486816,
0.00368314771912992,
0.07533777505159378,
0.060310911387205124,
0.02759413793683052,
-0.012300663627684116,
0.04076618701219559,
0.08261215686798096,
-0.14588621258735657,
-0.1659701019525528,
0.1326720416545868,
0.025149408727884293,
0.11792458593845367,
0.03658788278698921,
-0.1549617499113083,
0.06687124073505402,
0.2523096203804016,
-0.11147607117891312,
0.02505038119852543,
0.12737524509429932,
-0.0366884209215641,
0.0672016367316246,
0.1144871786236763,
-0.02633814327418804,
-0.05217865854501724,
-0.011363590136170387,
0.10233135521411896,
0.028660254552960396,
-0.04646271467208862,
-0.02340836264193058,
-0.03373933956027031,
-0.019070526584982872,
-0.011738128960132599,
-0.0909019410610199,
-0.1543993502855301,
-0.10471053421497345,
-0.16619662940502167,
0.04399140924215317,
-0.04626438021659851,
0.13418889045715332,
0.09469578415155411,
-0.012723101302981377,
0.04568437114357948,
0.028575526550412178,
0.07275456190109253,
0.07916246354579926,
-0.02939477376639843,
-0.036159269511699677
] |
null | null | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "diffusers"} | null | AmrutaMuthal/mero_scaled_filled_boxes_from_pretrained_controlnet | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"diffusers:ControlNetModel",
"region:us"
] | 2024-02-11T05:15:35+00:00 | [
"1910.09700"
] | [] | TAGS
#diffusers #safetensors #arxiv-1910.09700 #diffusers-ControlNetModel #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#diffusers #safetensors #arxiv-1910.09700 #diffusers-ControlNetModel #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
32,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#diffusers #safetensors #arxiv-1910.09700 #diffusers-ControlNetModel #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06377048790454865,
0.2081737369298935,
-0.002637275028973818,
0.025890585035085678,
0.11254095286130905,
-0.0018340451642870903,
0.039896558970212936,
0.12930721044540405,
-0.004281109198927879,
0.11765749752521515,
0.04478417709469795,
0.08719214051961899,
0.10116349905729294,
0.18550843000411987,
0.04866766929626465,
-0.20569464564323425,
0.0032541751861572266,
-0.09994316846132278,
0.04181749373674393,
0.11212309449911118,
0.13799089193344116,
-0.10305756330490112,
0.08281620591878891,
-0.044638682156801224,
-0.014005470089614391,
-0.00529136136174202,
-0.09854451566934586,
-0.06491228938102722,
0.0670396238565445,
0.053765248507261276,
0.04711805656552315,
0.002644543768838048,
0.10286134481430054,
-0.2846705913543701,
0.017661822959780693,
0.08096422255039215,
0.004618849139660597,
0.06390245258808136,
0.0722770243883133,
-0.06876412034034729,
0.12442078441381454,
-0.07610006630420685,
0.1323736608028412,
0.0834868848323822,
-0.061870697885751724,
-0.20317679643630981,
-0.07835674285888672,
0.08785581588745117,
0.12151990830898285,
0.061049025505781174,
-0.02416766993701458,
0.15761330723762512,
-0.06447074562311172,
0.009746657684445381,
0.13347691297531128,
-0.11645394563674927,
-0.05396676063537598,
0.07471991330385208,
0.12172991782426834,
0.10747449100017548,
-0.1428055763244629,
-0.0035929479636251926,
0.04709639400243759,
0.02965513989329338,
0.08147239685058594,
0.021573469042778015,
0.12376076728105545,
0.04444783180952072,
-0.14230717718601227,
-0.040386851876974106,
0.12145093083381653,
0.03417740762233734,
-0.061886005103588104,
-0.22241899371147156,
-0.0036783383693546057,
-0.034242745488882065,
-0.016687270253896713,
-0.07297617942094803,
0.03999572619795799,
-0.026385903358459473,
0.0886121466755867,
-0.046320125460624695,
-0.1048990786075592,
-0.041386183351278305,
0.08519886434078217,
0.07369492948055267,
0.011449771001935005,
-0.02339407429099083,
0.0435074046254158,
0.1326204389333725,
0.046787556260824203,
-0.10154959559440613,
-0.06781005859375,
-0.07091456651687622,
-0.08958733826875687,
-0.0388299860060215,
0.06348288804292679,
0.030076345428824425,
0.028775116428732872,
0.2207881063222885,
0.012297693639993668,
0.03762616962194443,
0.024066505953669548,
0.014686635695397854,
0.05775611475110054,
0.07680855691432953,
-0.05108252912759781,
-0.15556038916110992,
-0.04102834314107895,
0.09469912201166153,
-0.004272876773029566,
-0.03815359249711037,
-0.042707040905952454,
0.04565487056970596,
0.058198023587465286,
0.1289050430059433,
0.08410504460334778,
-0.025530928745865822,
-0.05548035725951195,
-0.027727719396352768,
0.2467982918024063,
-0.14524556696414948,
0.046623554080724716,
-0.02403278276324272,
-0.022771194577217102,
-0.03997054696083069,
0.030325056985020638,
0.027668939903378487,
0.00007867119711590931,
0.10540188103914261,
-0.06206312030553818,
-0.04953313246369362,
-0.09252604097127914,
-0.03276311606168747,
0.039026301354169846,
-0.019492194056510925,
-0.014160433784127235,
-0.08540339022874832,
-0.0998675599694252,
-0.04918094724416733,
0.05182720720767975,
-0.060967180877923965,
-0.03864250332117081,
0.0065652746707201,
-0.07593010365962982,
-0.008195350877940655,
-0.0034020585007965565,
0.10188561677932739,
-0.03557964786887169,
0.042161282151937485,
-0.03600775822997093,
0.05584898963570595,
0.09540753066539764,
0.02695886418223381,
-0.06971152126789093,
0.05436353012919426,
-0.2158716917037964,
0.07149454951286316,
-0.11717414855957031,
0.036872100085020065,
-0.16928376257419586,
-0.039700910449028015,
0.007649819366633892,
0.008194316178560257,
0.014932669699192047,
0.13043805956840515,
-0.20803944766521454,
-0.013102827593684196,
0.12473299354314804,
-0.09316392242908478,
-0.10552482306957245,
0.0715356394648552,
-0.03312484174966812,
0.16810430586338043,
0.042014230042696,
-0.009626450948417187,
0.07216241955757141,
-0.1839769184589386,
-0.05982957035303116,
-0.014113794080913067,
-0.01809072121977806,
0.13371551036834717,
0.06510177254676819,
-0.06662117689847946,
0.05949807167053223,
0.03036811575293541,
-0.031133852899074554,
-0.05335499346256256,
-0.051353100687265396,
-0.10577154159545898,
-0.006127530708909035,
-0.08745787292718887,
0.0445585772395134,
-0.015443197451531887,
-0.08353685587644577,
-0.027650075033307076,
-0.17304760217666626,
-0.013468013145029545,
0.09827733039855957,
0.014279291965067387,
-0.00791954156011343,
-0.08121423423290253,
0.027516042813658714,
-0.018622614443302155,
-0.011345567181706429,
-0.16710998117923737,
-0.03910508751869202,
0.05200386047363281,
-0.14846496284008026,
0.027026452124118805,
-0.05432510748505592,
0.05986957624554634,
0.03712550923228264,
-0.05276787653565407,
-0.015118689276278019,
-0.014063146896660328,
0.013149172998964787,
-0.04678153991699219,
-0.1962045431137085,
-0.0484924279153347,
-0.036841221153736115,
0.14334902167320251,
-0.2587006986141205,
0.027210362255573273,
0.048287034034729004,
0.14400926232337952,
0.001419590669684112,
-0.0572277307510376,
0.01874362863600254,
-0.0539449006319046,
-0.05492565780878067,
-0.06333786249160767,
-0.0027980750892311335,
-0.030179105699062347,
-0.042658478021621704,
0.007756236474961042,
-0.16905280947685242,
-0.03962906822562218,
0.08912510424852371,
0.13573390245437622,
-0.15121588110923767,
-0.029439346864819527,
-0.05143774673342705,
-0.06362884491682053,
-0.07212772220373154,
-0.06429759413003922,
0.10822952538728714,
0.04906785860657692,
0.039082713425159454,
-0.07951384782791138,
-0.07221343368291855,
0.02819986641407013,
0.007403645198792219,
-0.0333842895925045,
0.08081383258104324,
0.060681089758872986,
-0.07873602211475372,
0.0681864470243454,
0.10067778825759888,
0.08359763026237488,
0.09100386500358582,
0.02346755750477314,
-0.11456741392612457,
-0.03253275901079178,
0.03977520018815994,
0.024808665737509727,
0.15390528738498688,
-0.048391032963991165,
0.040994562208652496,
0.04412076249718666,
-0.039410993456840515,
0.0222026314586401,
-0.08421929180622101,
0.02092646434903145,
0.02068931981921196,
-0.005363529082387686,
0.06175244227051735,
-0.023873088881373405,
-0.009397247806191444,
0.07668150216341019,
0.04497964307665825,
0.044112563133239746,
-0.004342460539191961,
-0.018789421766996384,
-0.1027018129825592,
0.1591726541519165,
-0.09500688314437866,
-0.2622419595718384,
-0.15704365074634552,
0.036072827875614166,
0.03271475061774254,
-0.022855816408991814,
0.025783978402614594,
-0.06298311054706573,
-0.10442981868982315,
-0.1134033352136612,
-0.018431980162858963,
0.019023122265934944,
-0.06928987801074982,
-0.07533760368824005,
0.07200528681278229,
0.0357227586209774,
-0.15220774710178375,
0.03837219998240471,
0.051843397319316864,
-0.053433746099472046,
-0.020615264773368835,
0.0993279367685318,
0.12534672021865845,
0.14403940737247467,
-0.013101748190820217,
-0.028952520340681076,
0.02979404479265213,
0.2069244384765625,
-0.13239093124866486,
0.11662235110998154,
0.12431637197732925,
-0.04762829467654228,
0.08455760776996613,
0.16300168633460999,
0.026775958016514778,
-0.09027547389268875,
0.04610971733927727,
0.03829003870487213,
-0.04199068993330002,
-0.26072555780410767,
-0.06236930564045906,
0.013038437813520432,
-0.06857940554618835,
0.09854187071323395,
0.1007872149348259,
0.11489661782979965,
0.028950445353984833,
-0.07093239575624466,
-0.052515335381031036,
-0.00291564897634089,
0.11340965330600739,
-0.07040002942085266,
-0.01878509297966957,
0.07138895243406296,
-0.04252476245164871,
0.005390253383666277,
0.11051289737224579,
0.033723071217536926,
0.1861899197101593,
0.021697254851460457,
0.12021936476230621,
0.06512792408466339,
0.08832882344722748,
-0.00308399205096066,
0.030414510518312454,
0.044145502150058746,
0.01819337159395218,
-0.00492758909240365,
-0.10325012356042862,
0.004378082230687141,
0.14404545724391937,
0.03866729885339737,
0.017975034192204475,
0.0059730177745223045,
-0.016794636845588684,
0.05103623867034912,
0.16486330330371857,
-0.016101133078336716,
-0.2008070945739746,
-0.07099151611328125,
0.0703515112400055,
-0.060511935502290726,
-0.12373160570859909,
-0.025732077658176422,
0.05607713386416435,
-0.17495931684970856,
0.02563953399658203,
-0.016396384686231613,
0.08904987573623657,
-0.09842278063297272,
-0.02874584123492241,
0.015854543074965477,
0.08046268671751022,
-0.015274902805685997,
0.0848907083272934,
-0.13453565537929535,
0.12237779796123505,
0.030542759224772453,
0.08919113874435425,
-0.11610386520624161,
0.07680154591798782,
-0.01147140096873045,
-0.0005135016981512308,
0.19908349215984344,
-0.0040532504208385944,
-0.03355611115694046,
-0.0789879709482193,
-0.11378518491983414,
-0.021512014791369438,
0.1288967728614807,
-0.12106489390134811,
0.0833699107170105,
-0.0068733589723706245,
-0.04322643205523491,
0.00442207045853138,
-0.12413717061281204,
-0.18239852786064148,
-0.19523265957832336,
0.06241945922374725,
-0.09621210396289825,
0.011331039480865002,
-0.11367218941450119,
-0.06359435617923737,
-0.023821929469704628,
0.2263954132795334,
-0.18205317854881287,
-0.06861625611782074,
-0.141544908285141,
-0.052977077662944794,
0.16958707571029663,
-0.036899399012327194,
0.07237377017736435,
-0.0185378547757864,
0.20060767233371735,
-0.004113456699997187,
0.002708928193897009,
0.060240261256694794,
-0.0868271067738533,
-0.17089012265205383,
-0.07454077899456024,
0.14976073801517487,
0.1291600912809372,
0.04787569120526314,
0.0012452536029741168,
0.00403722794726491,
-0.02108047716319561,
-0.11945714801549911,
0.003337414702400565,
0.1564033478498459,
0.04172747582197189,
0.015705350786447525,
-0.049039095640182495,
-0.09168023616075516,
-0.07094007730484009,
-0.07085976004600525,
0.06017254292964935,
0.2042320817708969,
-0.10109544545412064,
0.1833738386631012,
0.1581447869539261,
-0.07441775500774384,
-0.22102802991867065,
0.029392126947641373,
0.052459463477134705,
-0.006484836805611849,
0.05483517423272133,
-0.1764940768480301,
0.09039569646120071,
0.02486194297671318,
-0.05226637050509453,
0.1523270308971405,
-0.16455034911632538,
-0.1571565866470337,
0.06094888970255852,
0.03537524491548538,
-0.23056192696094513,
-0.13701777160167694,
-0.09278956800699234,
-0.052148595452308655,
-0.1343025118112564,
0.05843020975589752,
0.009990302845835686,
0.012220613658428192,
0.03206508234143257,
0.011442789807915688,
0.027158470824360847,
-0.05685865134000778,
0.1901194453239441,
0.0012381926644593477,
0.018812870606780052,
-0.06639792770147324,
-0.05988646671175957,
0.09505824744701385,
-0.05831746384501457,
0.12520629167556763,
0.007042815908789635,
0.01730077899992466,
-0.09950532764196396,
-0.047398172318935394,
-0.04886259138584137,
0.05088451877236366,
-0.07916641235351562,
-0.1031486764550209,
-0.04766669496893883,
0.09123209118843079,
0.06754767894744873,
-0.034038908779621124,
-0.01663188822567463,
-0.07096507400274277,
0.09416376054286957,
0.18141265213489532,
0.17021767795085907,
0.004436153918504715,
-0.07347141206264496,
0.02121775783598423,
-0.037613991647958755,
0.04148101061582565,
-0.247993603348732,
0.027281999588012695,
0.06036447733640671,
0.03379884362220764,
0.08991432189941406,
-0.024625539779663086,
-0.18824471533298492,
-0.042236100882291794,
0.07690601795911789,
-0.05881313607096672,
-0.2221745401620865,
-0.0108470618724823,
0.10420241951942444,
-0.1940937638282776,
-0.019748587161302567,
0.03421337902545929,
-0.043894797563552856,
-0.024959968402981758,
0.0006069004302844405,
0.06836739182472229,
0.007156317122280598,
0.09645794332027435,
0.07323960959911346,
0.09420419484376907,
-0.08342017978429794,
0.10327562689781189,
0.1051737517118454,
-0.08062507212162018,
0.034471284598112106,
0.07340624928474426,
-0.0519249364733696,
-0.041710637509822845,
0.03383316472172737,
0.03482773154973984,
0.015317275188863277,
-0.05084845796227455,
0.023472392931580544,
-0.03516261279582977,
0.04089570790529251,
0.07703907042741776,
0.030318358913064003,
-0.020225372165441513,
0.06770274043083191,
0.030050557106733322,
-0.1064314991235733,
0.09634553641080856,
0.019519727677106857,
0.03647226467728615,
-0.06930379569530487,
-0.028757428750395775,
0.03442561998963356,
0.02432624250650406,
-0.016748853027820587,
-0.02617635950446129,
-0.030378317460417747,
-0.017591223120689392,
-0.13747917115688324,
-0.019110525026917458,
-0.078964002430439,
0.006068241782486439,
0.014263411983847618,
-0.03363654017448425,
-0.0031190067529678345,
0.02337503619492054,
-0.06774810701608658,
-0.07063894718885422,
-0.007129215635359287,
0.10269966721534729,
-0.14853094518184662,
0.005992756690829992,
0.06968291103839874,
-0.1075638085603714,
0.07726727426052094,
-0.009291965514421463,
0.01529664732515812,
0.013588636182248592,
-0.1562168449163437,
0.05501227453351021,
-0.003817147808149457,
0.022130368277430534,
0.030471300706267357,
-0.16191059350967407,
-0.0024054443929344416,
-0.044457148760557175,
-0.02187769114971161,
-0.0024079063441604376,
-0.027808334678411484,
-0.12302738428115845,
0.07198501378297806,
-0.008433463051915169,
-0.0458790585398674,
-0.021341515704989433,
0.044643498957157135,
0.08661559224128723,
-0.030511582270264626,
0.10019075125455856,
-0.006369329523295164,
0.05518387258052826,
-0.16449865698814392,
-0.026776805520057678,
-0.04455685615539551,
0.023708714172244072,
0.02320259064435959,
-0.00791719276458025,
0.04039971902966499,
-0.008299227803945541,
0.22276704013347626,
-0.04755617678165436,
0.15361692011356354,
0.053174346685409546,
-0.00928426906466484,
-0.010469505563378334,
0.05753704532980919,
0.03868582472205162,
0.044479213654994965,
0.008476300165057182,
0.016060272231698036,
-0.023497045040130615,
-0.009990712627768517,
-0.16206595301628113,
0.021770887076854706,
0.13991720974445343,
0.07263870537281036,
0.013672846369445324,
0.05994291976094246,
-0.1343328356742859,
-0.11365697532892227,
0.10323594510555267,
-0.02779589779675007,
0.004973008297383785,
-0.08456133306026459,
0.12263290584087372,
0.1483525037765503,
-0.14490994811058044,
0.054680563509464264,
-0.055336400866508484,
-0.05473881587386131,
-0.09278364479541779,
-0.12874361872673035,
-0.05461100861430168,
-0.04267687723040581,
0.005050985142588615,
-0.03757528215646744,
0.05949963629245758,
0.022970780730247498,
-0.009546318091452122,
-0.00018646169337444007,
0.12258876860141754,
-0.019952749833464622,
-0.005935148801654577,
0.048283901065588,
0.04126444458961487,
0.018960895016789436,
-0.059614378958940506,
0.029235752299427986,
0.013179820030927658,
0.034869272261857986,
0.061353299766778946,
0.03746691718697548,
-0.048322226852178574,
0.031375739723443985,
0.0016615327913314104,
-0.10529478639364243,
0.019356973469257355,
-0.009209123440086842,
-0.07386144995689392,
0.137705460190773,
0.0417676717042923,
0.0100643215700984,
-0.0362134724855423,
0.22313518822193146,
-0.05495068058371544,
-0.07900619506835938,
-0.12234710156917572,
0.08853080123662949,
-0.012143363244831562,
0.06311090290546417,
0.021082118153572083,
-0.1265936940908432,
0.0037784301675856113,
0.14354795217514038,
0.12795285880565643,
-0.002555170562118292,
0.010470351204276085,
0.043231915682554245,
0.005067542660981417,
-0.06272687762975693,
0.047650955617427826,
0.06501071900129318,
0.1458711326122284,
-0.07927033305168152,
0.07871092110872269,
-0.0066283284686505795,
-0.07475323230028152,
-0.03235168009996414,
0.11066454648971558,
-0.033056020736694336,
0.03270018473267555,
-0.05395359545946121,
0.10889895260334015,
-0.062150150537490845,
-0.2921062409877777,
0.029646672308444977,
-0.09576381742954254,
-0.1482827216386795,
-0.011039423756301403,
0.05783425644040108,
-0.03071897104382515,
0.01572267711162567,
0.06516639143228531,
-0.051801178604364395,
0.19044767320156097,
0.027609825134277344,
-0.07542408257722855,
-0.06343930214643478,
0.04765486717224121,
-0.06868550181388855,
0.3003348112106323,
0.007105046417564154,
0.038069646805524826,
0.09800047427415848,
-0.029364388436079025,
-0.1832560896873474,
0.015591043047606945,
0.11554247885942459,
-0.07769329100847244,
0.07573072612285614,
0.19147874414920807,
-0.012091076001524925,
0.11594957858324051,
0.05863192677497864,
-0.04125644266605377,
0.04600447788834572,
-0.01905503310263157,
-0.046874359250068665,
-0.10752508789300919,
0.06759212911128998,
-0.06184959411621094,
0.1594933420419693,
0.08747886121273041,
-0.057011138647794724,
-0.004505429416894913,
-0.05461994558572769,
0.052491117268800735,
0.01455291360616684,
0.12631557881832123,
0.024675920605659485,
-0.18541878461837769,
0.03306131064891815,
-0.010157587006688118,
0.10545752197504044,
-0.2396007478237152,
-0.08084530383348465,
0.08366255462169647,
-0.012259399518370628,
-0.05015650391578674,
0.10185766220092773,
0.05622407793998718,
0.0377991609275341,
-0.03942566365003586,
-0.11152336746454239,
-0.016667718067765236,
0.1443726122379303,
-0.13839513063430786,
-0.017837122082710266
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] | {"license": "apache-2.0", "library_name": "transformers"} | text-generation | indischepartij/MiniCPM-3B-OpenHermes-2.5-v2 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T05:15:58+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
68,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.05421007052063942,
0.21353216469287872,
-0.005195770412683487,
0.015510992147028446,
0.09552915394306183,
0.007233798038214445,
0.06299852579832077,
0.11748887598514557,
-0.05413045361638069,
0.1254425197839737,
0.042821433395147324,
0.11764875799417496,
0.11788404732942581,
0.14865340292453766,
-0.009830472990870476,
-0.2117120623588562,
0.04803319647908211,
-0.09720031917095184,
-0.012052030302584171,
0.1252613067626953,
0.15213333070278168,
-0.10217810422182083,
0.06851313263177872,
-0.024368764832615852,
-0.027055442333221436,
-0.037150971591472626,
-0.05546269938349724,
-0.04745631664991379,
0.039544492959976196,
0.04528430104255676,
0.06970518082380295,
0.001712438534013927,
0.08877605944871902,
-0.2992722690105438,
0.014970153570175171,
0.0640135332942009,
-0.001543649472296238,
0.07006900012493134,
0.08662033081054688,
-0.06534518301486969,
0.11219346523284912,
-0.05878305807709694,
0.13900697231292725,
0.08096235245466232,
-0.08774862438440323,
-0.1692102998495102,
-0.08263298124074936,
0.1174328476190567,
0.17627361416816711,
0.058563701808452606,
-0.03340518847107887,
0.10680689662694931,
-0.07751280069351196,
0.018406087532639503,
0.04142440855503082,
-0.10325261205434799,
-0.061977569013834,
0.0889614075422287,
0.1026742234826088,
0.04743117466568947,
-0.12422743439674377,
-0.025862542912364006,
0.018615398555994034,
0.02007068693637848,
0.08595702797174454,
0.015395105816423893,
0.14564822614192963,
0.03601236268877983,
-0.1341829150915146,
-0.0676095113158226,
0.10975120216608047,
0.0368351936340332,
-0.033129241317510605,
-0.2364804446697235,
-0.012580571696162224,
-0.022237909957766533,
-0.03624308109283447,
-0.044529348611831665,
0.04631321132183075,
-0.0005323975346982479,
0.09220490604639053,
-0.010182738304138184,
-0.07924249023199081,
-0.04084255173802376,
0.08169548213481903,
0.044452786445617676,
0.026453007012605667,
-0.020324107259511948,
0.0203366931527853,
0.10622947663068771,
0.08327034115791321,
-0.11443831771612167,
-0.05162142962217331,
-0.05888386815786362,
-0.07111316919326782,
-0.04280072823166847,
0.034990426152944565,
0.03930659219622612,
0.07840628921985626,
0.24959580600261688,
0.029059061780571938,
0.048530738800764084,
0.03179147467017174,
0.010655518621206284,
0.04971959441900253,
0.09806057065725327,
-0.05242425575852394,
-0.13289262354373932,
-0.02298697642982006,
0.09952209144830704,
0.007216785568743944,
-0.026848504319787025,
-0.03550588712096214,
0.06144018843770027,
0.04493623599410057,
0.11029700189828873,
0.09567772597074509,
0.02058328315615654,
-0.07759489119052887,
-0.05045783892273903,
0.18797671794891357,
-0.15546999871730804,
0.03424759581685066,
0.03241557255387306,
-0.03225022181868553,
-0.042539987713098526,
0.010223302990198135,
0.03644843399524689,
-0.03834828361868858,
0.08707873523235321,
-0.055407486855983734,
-0.05217565596103668,
-0.11175728589296341,
-0.028877221047878265,
0.04535342752933502,
0.011876794509589672,
-0.030229168012738228,
-0.029383152723312378,
-0.09198717027902603,
-0.08744015544652939,
0.09337115287780762,
-0.06617824733257294,
-0.07453399896621704,
-0.033669911324977875,
-0.07625599950551987,
0.02099107764661312,
0.018597649410367012,
0.08792351931333542,
-0.02761901170015335,
0.04983241856098175,
-0.055906862020492554,
0.046567339450120926,
0.10784912109375,
0.037745919078588486,
-0.06983573734760284,
0.07124537974596024,
-0.20427170395851135,
0.088422030210495,
-0.08268746733665466,
0.045390188694000244,
-0.16388723254203796,
-0.024082660675048828,
0.03879587724804878,
0.01778320223093033,
-0.0032686772756278515,
0.13137176632881165,
-0.19658426940441132,
-0.01668846420943737,
0.17825444042682648,
-0.10253147780895233,
-0.08507469296455383,
0.052842628210783005,
-0.056965745985507965,
0.1198565885424614,
0.03634784743189812,
0.018906032666563988,
0.05675210803747177,
-0.10537079721689224,
-0.01592581532895565,
-0.05311892181634903,
-0.007714042440056801,
0.12185113877058029,
0.08123867958784103,
-0.09110184758901596,
0.04094868525862694,
0.01818959414958954,
-0.037934836000204086,
-0.06679833680391312,
-0.030334651470184326,
-0.10395018756389618,
0.011312548071146011,
-0.0824674665927887,
0.010543725453317165,
-0.012028217315673828,
-0.09357302635908127,
-0.029082268476486206,
-0.15845413506031036,
-0.02274945005774498,
0.08667369186878204,
-0.005154716316610575,
-0.024379126727581024,
-0.1027505174279213,
0.025411827489733696,
0.013339781202375889,
-0.008432595059275627,
-0.12652909755706787,
-0.02950648032128811,
0.029136933386325836,
-0.1445825845003128,
0.025755291804671288,
-0.07152844220399857,
0.04687676951289177,
0.012527765706181526,
-0.03304968401789665,
-0.022122470661997795,
0.01316812727600336,
0.017333848401904106,
-0.027659740298986435,
-0.22898216545581818,
-0.023435210809111595,
-0.03599431738257408,
0.16630098223686218,
-0.229477196931839,
0.039603669196367264,
0.05587010458111763,
0.14605022966861725,
-0.0025137641932815313,
-0.05595584213733673,
0.02650558017194271,
-0.06440931558609009,
-0.027612756937742233,
-0.05448679253458977,
0.003134383587166667,
-0.016004344448447227,
-0.0415244959294796,
0.025792177766561508,
-0.1693287044763565,
-0.03902023285627365,
0.10298878699541092,
0.048855215311050415,
-0.12400372326374054,
-0.03926670551300049,
-0.03078654408454895,
-0.05742620304226875,
-0.04631776735186577,
-0.059575360268354416,
0.09847971796989441,
0.0571528784930706,
0.04098925739526749,
-0.0692935362458229,
-0.07416164129972458,
-0.00269014248624444,
-0.022786108776926994,
-0.022351281717419624,
0.09653493016958237,
0.08616705983877182,
-0.12496592849493027,
0.09849628806114197,
0.0806584507226944,
0.057344526052474976,
0.08248010277748108,
-0.021596938371658325,
-0.07536353170871735,
-0.025714652612805367,
0.03437156602740288,
0.021032460033893585,
0.12986093759536743,
-0.07052668184041977,
0.04064677283167839,
0.045514266937971115,
-0.03359606862068176,
0.025925764814019203,
-0.08497381955385208,
0.017476709559559822,
0.02272469736635685,
-0.021497435867786407,
0.02897656336426735,
-0.04235527291893959,
0.013233993202447891,
0.0862521231174469,
0.04959078133106232,
0.022235149517655373,
0.020284386351704597,
-0.050040870904922485,
-0.11617273092269897,
0.16021136939525604,
-0.11329260468482971,
-0.20821933448314667,
-0.13356228172779083,
0.03088466450572014,
0.037179749459028244,
-0.01598362997174263,
-0.0025709797628223896,
-0.051371123641729355,
-0.1025322750210762,
-0.09225393831729889,
0.006456200033426285,
0.040953103452920914,
-0.09247945994138718,
-0.04293585941195488,
0.04079096391797066,
0.04231250286102295,
-0.13822127878665924,
0.01610880345106125,
0.04589884355664253,
-0.08359266072511673,
-0.01120610348880291,
0.06256414204835892,
0.08998946845531464,
0.19560815393924713,
0.013581868261098862,
-0.012131399475038052,
0.023843638598918915,
0.22275377810001373,
-0.1383862942457199,
0.1014406755566597,
0.13049447536468506,
-0.07322458177804947,
0.08163802325725555,
0.21160255372524261,
0.040092695504426956,
-0.09270840883255005,
0.02441057190299034,
0.04003278911113739,
-0.023381903767585754,
-0.2509364187717438,
-0.07303188741207123,
-0.004622313659638166,
-0.06134811416268349,
0.08438423275947571,
0.08801863342523575,
0.09943808615207672,
0.038168229162693024,
-0.0836082473397255,
-0.08809591829776764,
0.06154439225792885,
0.10864007472991943,
-0.004196378868073225,
0.005868837237358093,
0.09007053822278976,
-0.03175199031829834,
0.01909078285098076,
0.08826909214258194,
0.01844124309718609,
0.14803802967071533,
0.04756850376725197,
0.17049501836299896,
0.08995312452316284,
0.08402234315872192,
-0.0015238280175253749,
0.021388573572039604,
0.010524826124310493,
0.04439735412597656,
-0.0017697714501991868,
-0.07938341051340103,
-0.018823746591806412,
0.11968310177326202,
0.05288228765130043,
0.015503411181271076,
0.01803954504430294,
-0.0391206219792366,
0.0744151771068573,
0.19708149135112762,
-0.003263753140345216,
-0.19755280017852783,
-0.05384271964430809,
0.07781800627708435,
-0.09241209179162979,
-0.10619477927684784,
0.0019064407097175717,
0.02124488726258278,
-0.16801559925079346,
0.040584951639175415,
-0.0322476401925087,
0.11023034900426865,
-0.1111789122223854,
-0.021756893023848534,
0.07052167505025864,
0.05959389731287956,
-0.014178748242557049,
0.07435203343629837,
-0.2035863697528839,
0.11238204687833786,
0.009567494504153728,
0.0717628002166748,
-0.09909266978502274,
0.0891956314444542,
-0.001081119291484356,
-0.025000736117362976,
0.1611567735671997,
-0.006757483817636967,
-0.07005572319030762,
-0.06452172249555588,
-0.09549829363822937,
-0.007743114605545998,
0.09846057742834091,
-0.13114306330680847,
0.0837324783205986,
-0.03229309991002083,
-0.03283150866627693,
0.000035455705074127764,
-0.09856724739074707,
-0.11704195290803909,
-0.17358876764774323,
0.05246591195464134,
-0.1162688285112381,
0.03708010911941528,
-0.10647160559892654,
-0.029181834310293198,
-0.03587225452065468,
0.18525031208992004,
-0.20157071948051453,
-0.0807575136423111,
-0.13813824951648712,
-0.09876710921525955,
0.1394060254096985,
-0.04165269434452057,
0.09829629957675934,
-0.008952802047133446,
0.16236551105976105,
0.009415987879037857,
-0.01310163363814354,
0.07753563672304153,
-0.09245961159467697,
-0.20152728259563446,
-0.0660102367401123,
0.16194145381450653,
0.10931919515132904,
0.036590855568647385,
0.005600698292255402,
0.03727604076266289,
-0.026978204026818275,
-0.11075286567211151,
0.02552393265068531,
0.14167837798595428,
0.0849403515458107,
0.002661976730450988,
-0.01830657199025154,
-0.13354960083961487,
-0.08307620137929916,
-0.04577168449759483,
0.024014126509428024,
0.1599515974521637,
-0.07414983958005905,
0.15789707005023956,
0.1328311711549759,
-0.06604088842868805,
-0.2016577124595642,
0.005006593186408281,
0.024452360346913338,
-0.009555138647556305,
0.015897223725914955,
-0.17855186760425568,
0.08419980853796005,
0.011494292877614498,
-0.05953359231352806,
0.08966474235057831,
-0.18357999622821808,
-0.1389443427324295,
0.0829738900065422,
0.05449368804693222,
-0.20674683153629303,
-0.13991928100585938,
-0.0965299978852272,
-0.03951890766620636,
-0.1560729444026947,
0.09325455129146576,
-0.002555206185206771,
0.002427567495033145,
0.03608793020248413,
0.010130190290510654,
0.027736838907003403,
-0.05545626953244209,
0.1822115033864975,
0.0015607478562742472,
0.028007594868540764,
-0.0849214494228363,
-0.09926366060972214,
0.028430836275219917,
-0.04676833376288414,
0.07731037586927414,
-0.034188736230134964,
0.015682758763432503,
-0.11721178144216537,
-0.04310533404350281,
-0.05702150613069534,
0.014305627904832363,
-0.10113276541233063,
-0.09224298596382141,
-0.04827515035867691,
0.08720213174819946,
0.10896769165992737,
-0.018856149166822433,
-0.03554953634738922,
-0.08316361904144287,
0.0637880191206932,
0.22650088369846344,
0.19465456902980804,
0.07965768128633499,
-0.0686941146850586,
0.0003643847012426704,
-0.025200067088007927,
0.04334692284464836,
-0.19990992546081543,
0.055416274815797806,
0.060230378061532974,
0.018969237804412842,
0.10871423035860062,
-0.026253951713442802,
-0.14472559094429016,
-0.0721317008137703,
0.06167231872677803,
-0.0606088787317276,
-0.20093978941440582,
0.011844802647829056,
0.05368282273411751,
-0.17043231427669525,
-0.042620155960321426,
0.035140108317136765,
-0.01567363739013672,
-0.03511351719498634,
0.011021547019481659,
0.09591306746006012,
-0.007927972823381424,
0.09122961759567261,
0.07482846081256866,
0.09281997382640839,
-0.09625906497240067,
0.08788356184959412,
0.10036601126194,
-0.06110791116952896,
0.031820133328437805,
0.09031558781862259,
-0.04985802620649338,
-0.03767872974276543,
0.05876798555254936,
0.0977143719792366,
0.0181441493332386,
-0.05742422118782997,
0.001989413984119892,
-0.09092903882265091,
0.060996487736701965,
0.11156345158815384,
0.024177588522434235,
0.01323536317795515,
0.054828476160764694,
0.031693775206804276,
-0.08715648204088211,
0.12227930873632431,
0.0558650903403759,
0.01360325701534748,
-0.043362557888031006,
-0.01541239582002163,
0.011019410565495491,
-0.03362196311354637,
-0.004392077215015888,
-0.0068086134269833565,
-0.07655733823776245,
-0.006663029082119465,
-0.13749735057353973,
0.020432505756616592,
-0.07976438105106354,
0.01191214844584465,
0.024302974343299866,
-0.02403266914188862,
0.007492481265217066,
-0.0005300515913404524,
-0.0747627392411232,
-0.05692018195986748,
-0.009850657545030117,
0.10309379547834396,
-0.16633078455924988,
0.019606593996286392,
0.08275865763425827,
-0.10563306510448456,
0.09102261066436768,
-0.009379170835018158,
-0.0074268514290452,
0.0061704558320343494,
-0.1587742269039154,
0.053865980356931686,
-0.028385495766997337,
0.005714855622500181,
0.005054907873272896,
-0.18175947666168213,
-0.0027730907313525677,
-0.030795710161328316,
-0.07112878561019897,
-0.006538000423461199,
-0.027773858979344368,
-0.11184186488389969,
0.09471060335636139,
0.010890747420489788,
-0.08225402235984802,
-0.02280508726835251,
0.03642101585865021,
0.08786973357200623,
-0.0425306037068367,
0.14135800302028656,
-0.01673547364771366,
0.06452823430299759,
-0.17004156112670898,
-0.008491916581988335,
-0.010103556327521801,
0.0216610599309206,
-0.05692877247929573,
-0.00717727467417717,
0.04933054745197296,
-0.021108359098434448,
0.18962650001049042,
-0.024675166234374046,
0.01256572362035513,
0.059918999671936035,
0.028900403529405594,
0.002346554771065712,
0.09849470108747482,
0.06742341816425323,
0.010411731898784637,
0.008202279917895794,
0.01431958843022585,
-0.04742715507745743,
-0.03674702346324921,
-0.17788489162921906,
0.06548750400543213,
0.20393411815166473,
0.1029265746474266,
-0.01982530765235424,
0.06886112689971924,
-0.11523269861936569,
-0.10029982775449753,
0.1369268149137497,
-0.03827545791864395,
-0.0034170160070061684,
-0.07522282749414444,
0.14319820702075958,
0.14159227907657623,
-0.1937766969203949,
0.07344622910022736,
-0.07756593823432922,
-0.047934211790561676,
-0.10181821882724762,
-0.20400717854499817,
-0.06506483256816864,
-0.04013410210609436,
-0.012756729498505592,
-0.057141683995723724,
0.06803543120622635,
0.09175455570220947,
-0.005058931186795235,
-0.016183175146579742,
0.06868628412485123,
-0.03566555678844452,
0.0012162495404481888,
0.03283097967505455,
0.05696803331375122,
0.01834675297141075,
-0.06658197939395905,
0.010480284690856934,
-0.013662338256835938,
0.0498485192656517,
0.07791288942098618,
0.03786285221576691,
-0.024411363527178764,
0.014696408063173294,
-0.028134189546108246,
-0.10276906192302704,
0.05010531097650528,
-0.02319330908358097,
-0.050738364458084106,
0.15068596601486206,
0.02490590326488018,
0.006162187084555626,
-0.010335122235119343,
0.2244664579629898,
-0.06681383401155472,
-0.10548964142799377,
-0.14899702370166779,
0.07716231048107147,
-0.052965231239795685,
0.04415183141827583,
0.051153216511011124,
-0.11254875361919403,
0.02664860151708126,
0.15966027975082397,
0.16181878745555878,
-0.033362921327352524,
0.01282995380461216,
0.028031745925545692,
0.005923285614699125,
-0.026338767260313034,
0.03893594443798065,
0.050021905452013016,
0.1392587572336197,
-0.0639779195189476,
0.0686778649687767,
0.005723598878830671,
-0.08273192495107651,
-0.02065124548971653,
0.12605585157871246,
-0.014959827065467834,
0.002611157251521945,
-0.053577721118927,
0.12211853265762329,
-0.06959804892539978,
-0.2090820074081421,
0.038501229137182236,
-0.07648737728595734,
-0.1334782987833023,
-0.02732706442475319,
0.0442705899477005,
-0.0013251103227958083,
0.018473748117685318,
0.0755845382809639,
-0.06794920563697815,
0.1716848760843277,
0.03500717878341675,
-0.06667187064886093,
-0.050138216465711594,
0.07921779155731201,
-0.07963936775922775,
0.30680927634239197,
0.01832200214266777,
0.04667375981807709,
0.10743077099323273,
-0.017963936552405357,
-0.12426140904426575,
0.02700815349817276,
0.103448286652565,
-0.07143918424844742,
0.05799660459160805,
0.16167333722114563,
-0.004595374222844839,
0.1301085501909256,
0.07091037184000015,
-0.0756249725818634,
0.04676031321287155,
-0.07615955173969269,
-0.07484336942434311,
-0.10520949959754944,
0.09598609805107117,
-0.08931051939725876,
0.14986251294612885,
0.12488403171300888,
-0.0589633472263813,
0.010744609870016575,
-0.025451499968767166,
0.06114969030022621,
-0.009655525907874107,
0.12451629340648651,
0.011233685538172722,
-0.18578436970710754,
0.02956356108188629,
-0.028040342032909393,
0.10093195736408234,
-0.18736286461353302,
-0.07799412310123444,
0.03976720571517944,
-0.00040075325523503125,
-0.0820973664522171,
0.1183193176984787,
0.07633206248283386,
0.029269572347402573,
-0.04921464994549751,
-0.02453635446727276,
-0.010994812473654747,
0.1487521231174469,
-0.09453071653842926,
-0.0056170192547142506
] |
null | null | transformers | # RPmerge
2.67
See the main model card: https://huggingface.co/brucethemoose/Yi-34B-200K-RPMerge
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using /home/alpha/Models/Raw/chargoddard_Yi-34B-200K-Llama as a base.
### Models Merged
The following models were included in the merge:
* /home/alpha/Models/Raw/migtissera_Tess-34B-v1.5b
* /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0
* /home/alpha/Models/Raw/cgato_Thespis-34b-DPO-v0.7
* /home/alpha/Models/Raw/Nous-Capybara-34B
* /home/alpha/Models/Raw/admo_limarp
* /home/alpha/Models/Raw/DrNicefellow_ChatAllInOne-Yi-34B-200K-V1
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: /home/alpha/Models/Raw/chargoddard_Yi-34B-200K-Llama
# No parameters necessary for base model
- model: /home/alpha/Models/Raw/migtissera_Tess-34B-v1.5b
#Emphasize the beginning of Vicuna format models
parameters:
weight: 0.19
density: 0.59
- model: /home/alpha/Models/Raw/Nous-Capybara-34B
parameters:
weight: 0.19
density: 0.55
# Vicuna format
- model: /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0
parameters:
weight: 0.05
density: 0.55
- model: /home/alpha/Models/Raw/DrNicefellow_ChatAllInOne-Yi-34B-200K-V1
parameters:
weight: 0.19
density: 0.55
- model: /home/alpha/Models/Raw/admo_limarp
parameters:
weight: 0.19
density: 0.48
- model: /home/alpha/Models/Raw/cgato_Thespis-34b-DPO-v0.7
parameters:
weight: 0.19
density: 0.59
merge_method: dare_ties
tokenizer_source: union
base_model: /home/alpha/Models/Raw/chargoddard_Yi-34B-200K-Llama
parameters:
int8_mask: true
dtype: bfloat16
```
| {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["mergekit", "merge", "Yi", "exllama", "exllamav2", "exl2"], "license_name": "yi-license", "license_link": "https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE", "base_model": []} | text-generation | brucethemoose/Yi-34B-200K-RPMerge-exl2-267bpw | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"Yi",
"exllama",
"exllamav2",
"exl2",
"en",
"arxiv:2311.03099",
"arxiv:2306.01708",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T05:18:20+00:00 | [
"2311.03099",
"2306.01708"
] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #mergekit #merge #Yi #exllama #exllamav2 #exl2 #en #arxiv-2311.03099 #arxiv-2306.01708 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # RPmerge
2.67
See the main model card: URL
## Merge Details
### Merge Method
This model was merged using the DARE TIES merge method using /home/alpha/Models/Raw/chargoddard_Yi-34B-200K-Llama as a base.
### Models Merged
The following models were included in the merge:
* /home/alpha/Models/Raw/migtissera_Tess-34B-v1.5b
* /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0
* /home/alpha/Models/Raw/cgato_Thespis-34b-DPO-v0.7
* /home/alpha/Models/Raw/Nous-Capybara-34B
* /home/alpha/Models/Raw/admo_limarp
* /home/alpha/Models/Raw/DrNicefellow_ChatAllInOne-Yi-34B-200K-V1
### Configuration
The following YAML configuration was used to produce this model:
| [
"# RPmerge\n\n2.67\n\nSee the main model card: URL",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the DARE TIES merge method using /home/alpha/Models/Raw/chargoddard_Yi-34B-200K-Llama as a base.",
"### Models Merged\n\nThe following models were included in the merge:\n* /home/alpha/Models/Raw/migtissera_Tess-34B-v1.5b\n* /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0\n* /home/alpha/Models/Raw/cgato_Thespis-34b-DPO-v0.7\n* /home/alpha/Models/Raw/Nous-Capybara-34B\n* /home/alpha/Models/Raw/admo_limarp\n* /home/alpha/Models/Raw/DrNicefellow_ChatAllInOne-Yi-34B-200K-V1",
"### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #mergekit #merge #Yi #exllama #exllamav2 #exl2 #en #arxiv-2311.03099 #arxiv-2306.01708 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# RPmerge\n\n2.67\n\nSee the main model card: URL",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the DARE TIES merge method using /home/alpha/Models/Raw/chargoddard_Yi-34B-200K-Llama as a base.",
"### Models Merged\n\nThe following models were included in the merge:\n* /home/alpha/Models/Raw/migtissera_Tess-34B-v1.5b\n* /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0\n* /home/alpha/Models/Raw/cgato_Thespis-34b-DPO-v0.7\n* /home/alpha/Models/Raw/Nous-Capybara-34B\n* /home/alpha/Models/Raw/admo_limarp\n* /home/alpha/Models/Raw/DrNicefellow_ChatAllInOne-Yi-34B-200K-V1",
"### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
95,
13,
4,
49,
169,
17
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #mergekit #merge #Yi #exllama #exllamav2 #exl2 #en #arxiv-2311.03099 #arxiv-2306.01708 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# RPmerge\n\n2.67\n\nSee the main model card: URL## Merge Details### Merge Method\n\nThis model was merged using the DARE TIES merge method using /home/alpha/Models/Raw/chargoddard_Yi-34B-200K-Llama as a base.### Models Merged\n\nThe following models were included in the merge:\n* /home/alpha/Models/Raw/migtissera_Tess-34B-v1.5b\n* /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0\n* /home/alpha/Models/Raw/cgato_Thespis-34b-DPO-v0.7\n* /home/alpha/Models/Raw/Nous-Capybara-34B\n* /home/alpha/Models/Raw/admo_limarp\n* /home/alpha/Models/Raw/DrNicefellow_ChatAllInOne-Yi-34B-200K-V1### Configuration\n\nThe following YAML configuration was used to produce this model:"
] | [
-0.0817263275384903,
0.11349861323833466,
-0.006203660275787115,
-0.007973513565957546,
0.08615712076425552,
0.08122184872627258,
0.15207239985466003,
0.14457261562347412,
0.03823588415980339,
0.11105862259864807,
0.013642791658639908,
0.1347588449716568,
0.11909070611000061,
0.11825734376907349,
0.035511404275894165,
-0.16784736514091492,
0.03095540776848793,
-0.04883507266640663,
-0.07759405672550201,
0.09883447736501694,
0.0876227468252182,
-0.06280944496393204,
0.1253231167793274,
0.054582200944423676,
-0.09501303732395172,
-0.004025700502097607,
-0.034986987709999084,
0.029679110273718834,
0.07393032312393188,
0.07582749426364899,
0.07371972501277924,
0.05963991582393646,
0.06366285681724548,
-0.17279408872127533,
0.01931772194802761,
0.04615667834877968,
-0.017979342490434647,
0.062346503138542175,
0.10977264493703842,
-0.08925168961286545,
0.17106923460960388,
-0.03830786049365997,
0.028422005474567413,
0.10577578097581863,
-0.10737920552492142,
-0.19812002778053284,
-0.10977578163146973,
0.18015870451927185,
0.08106645196676254,
0.02724185772240162,
-0.011396901682019234,
0.0538259856402874,
0.058969542384147644,
0.05897551029920578,
0.14792241156101227,
-0.16191256046295166,
-0.01474854163825512,
0.1363874226808548,
0.09521713852882385,
-0.08946704864501953,
-0.018586797639727592,
0.029070572927594185,
0.00826169177889824,
0.01662527024745941,
0.003597945673391223,
-0.007796847261488438,
0.28548648953437805,
-0.046178340911865234,
-0.09777700901031494,
-0.03831586241722107,
0.07781609892845154,
0.05572591349482536,
-0.005722830072045326,
-0.1174754947423935,
-0.0730503723025322,
-0.03524534031748772,
-0.04532618075609207,
0.008350611664354801,
0.014594589360058308,
-0.035099804401397705,
0.0738062635064125,
-0.03130688890814781,
-0.05600026994943619,
-0.039633676409721375,
0.007211079355329275,
0.053300097584724426,
0.02442815713584423,
0.012740176171064377,
-0.0205742996186018,
0.07832466810941696,
-0.06221121549606323,
-0.13664232194423676,
0.02525543048977852,
-0.06235218420624733,
-0.043696727603673935,
0.0017451962921768427,
0.00041361217154189944,
-0.04427717998623848,
0.07791115343570709,
0.1531522423028946,
-0.030209308490157127,
0.0416184663772583,
0.05998307466506958,
0.03621548414230347,
0.041523732244968414,
0.044017162173986435,
-0.1433267742395401,
-0.08561872690916061,
-0.0451909601688385,
0.03463641181588173,
-0.005033600609749556,
0.01601296290755272,
-0.07008042186498642,
0.03685005009174347,
-0.035738397389650345,
0.03637684881687164,
0.10228727012872696,
0.06606646627187729,
-0.06434598565101624,
-0.07820688933134079,
0.23633715510368347,
-0.07888654619455338,
0.030093533918261528,
0.02932560257613659,
-0.022190330550074577,
0.0055242013186216354,
0.03878270462155342,
0.01825305074453354,
-0.0029614425729960203,
0.07934533059597015,
-0.04638247936964035,
-0.0506751611828804,
-0.0754227265715599,
-0.0873035416007042,
0.006826610304415226,
-0.055376216769218445,
-0.021109875291585922,
-0.10184328258037567,
-0.12026624381542206,
-0.09384074062108994,
0.059013739228248596,
-0.08366470783948898,
-0.020024267956614494,
0.0014482357073575258,
-0.03626451641321182,
0.05893360823392868,
0.021343182772397995,
0.03604501485824585,
-0.009506232105195522,
0.02830890752375126,
-0.04185257852077484,
0.04355064034461975,
0.020163336768746376,
0.031176133081316948,
-0.02787238545715809,
0.11392397433519363,
-0.18908816576004028,
0.04453105106949806,
-0.03834462910890579,
0.06583652645349503,
-0.17223936319351196,
-0.03068842552602291,
-0.0023662950843572617,
0.022800317034125328,
0.023436352610588074,
0.13807354867458344,
-0.1231846883893013,
-0.06493551284074783,
0.14202725887298584,
-0.10380184650421143,
-0.097084179520607,
0.02492329478263855,
0.030125314369797707,
0.0523429736495018,
0.017317168414592743,
0.1499491184949875,
0.11967949569225311,
-0.046548303216695786,
-0.0628693476319313,
-0.07059495896100998,
-0.00788797251880169,
0.04218391701579094,
0.047101762145757675,
-0.04776328429579735,
-0.007461827248334885,
-0.0001987497234949842,
-0.005358221009373665,
0.021875062957406044,
-0.03207604959607124,
-0.04736262559890747,
-0.028766222298145294,
-0.07973553985357285,
0.038900092244148254,
0.008006954565644264,
-0.03395756706595421,
-0.03954559192061424,
-0.10393212735652924,
-0.05971311777830124,
0.12985403835773468,
-0.02370639704167843,
-0.01643310859799385,
-0.08132002502679825,
0.13612565398216248,
-0.014397922903299332,
0.0133050000295043,
-0.12842784821987152,
-0.0394151397049427,
-0.010940449312329292,
-0.08845103532075882,
0.01953796297311783,
-0.04011160880327225,
0.08580194413661957,
0.03858804330229759,
-0.018530547618865967,
-0.08675891906023026,
0.07036201655864716,
0.021414179354906082,
-0.008152293972671032,
-0.2086906135082245,
-0.1268429309129715,
-0.03456678241491318,
0.15370334684848785,
-0.10790622234344482,
0.040190476924180984,
-0.003177527105435729,
0.21727676689624786,
-0.017555460333824158,
-0.03830340877175331,
0.04040870442986488,
-0.029915669932961464,
-0.011097238399088383,
-0.027474671602249146,
0.08013123273849487,
-0.009215816855430603,
-0.08041293174028397,
0.11790848523378372,
-0.16572605073451996,
-0.038801997900009155,
0.08649991452693939,
0.0172188151627779,
-0.10505575686693192,
0.027034718543291092,
-0.031045449897646904,
-0.028769459575414658,
0.060504984110593796,
-0.10165742039680481,
0.0460827499628067,
0.043414026498794556,
0.07981990277767181,
-0.030582644045352936,
-0.05694114416837692,
0.03481380641460419,
-0.010577653534710407,
-0.0517413467168808,
0.12558996677398682,
0.0891016274690628,
-0.17740409076213837,
0.09156375378370285,
0.12168058753013611,
0.1531810313463211,
0.08424302935600281,
0.01945475861430168,
-0.03464401140809059,
-0.07462519407272339,
-0.01341406349092722,
0.027560971677303314,
0.055322449654340744,
-0.009317884221673012,
0.019116612151265144,
0.057866137474775314,
-0.011495924554765224,
0.018693793565034866,
-0.08499816060066223,
0.02838681824505329,
0.04270126670598984,
-0.0036099485587328672,
0.06509199738502502,
0.06866736710071564,
0.02124594897031784,
0.06996648013591766,
0.03885958716273308,
0.008596865460276604,
-0.03941184654831886,
-0.04165835306048393,
-0.09750256687402725,
0.14087945222854614,
-0.10390790551900864,
-0.12168952077627182,
-0.14760707318782806,
-0.14257170259952545,
-0.014901243150234222,
-0.014153292402625084,
0.03710142895579338,
-0.08103726804256439,
-0.08956754952669144,
-0.06531447917222977,
0.09767544269561768,
-0.007857043296098709,
-0.06699880957603455,
-0.0069829863496124744,
0.011320263147354126,
0.051807839423418045,
-0.09139854460954666,
-0.034011099487543106,
0.051632948219776154,
-0.015818960964679718,
0.008533541113138199,
0.021359845995903015,
0.07468289881944656,
0.12196779996156693,
0.034452956169843674,
0.0004547767748590559,
0.019860219210386276,
0.25888532400131226,
-0.0717868059873581,
0.12106341868638992,
0.18152891099452972,
-0.03429233655333519,
0.07657408714294434,
0.21365605294704437,
0.044763777405023575,
-0.03325691074132919,
-0.02739648148417473,
0.0025917217135429382,
-0.015541098080575466,
-0.17853562533855438,
-0.10654046386480331,
-0.013239052146673203,
-0.02586613968014717,
0.0935422033071518,
0.06587568670511246,
0.04206646978855133,
0.0709434300661087,
-0.09251780807971954,
-0.07031406462192535,
-0.018760615959763527,
0.08019760251045227,
0.08700188994407654,
-0.0010123056126758456,
0.06256166100502014,
-0.044665541499853134,
0.011008732952177525,
0.05743315443396568,
0.05562297999858856,
0.10296466946601868,
0.08640165627002716,
0.1543549746274948,
0.10390821099281311,
0.07079465687274933,
0.01188981719315052,
0.02072128839790821,
-0.002358162309974432,
0.028574131429195404,
-0.0015735030174255371,
-0.08821465820074081,
0.04073672741651535,
0.07094835489988327,
0.0409158430993557,
0.00920076947659254,
-0.0868568867444992,
-0.08050139248371124,
0.018116192892193794,
0.1511259227991104,
0.1110115721821785,
-0.26338061690330505,
-0.04862367361783981,
0.05387076735496521,
0.008626559749245644,
-0.07589339464902878,
-0.04136321321129799,
-0.05426782742142677,
-0.11715387552976608,
0.1234070211648941,
-0.00849562045186758,
0.0831371545791626,
-0.05374772474169731,
0.0020295153371989727,
0.0572759211063385,
0.09227575361728668,
0.00942569226026535,
0.02272508107125759,
-0.03330584987998009,
0.2178795039653778,
0.03067898191511631,
-0.0296051986515522,
-0.020077066496014595,
0.046375781297683716,
0.03610007092356682,
0.0623689629137516,
0.12785494327545166,
0.01282871887087822,
-0.10229601711034775,
-0.12751249969005585,
-0.07718471437692642,
-0.05631721019744873,
0.07350368797779083,
-0.15965421497821808,
0.10952791571617126,
-0.01657995395362377,
-0.09270165860652924,
-0.030310729518532753,
0.05358528345823288,
-0.0971221923828125,
-0.09615208953619003,
0.07914253324270248,
-0.023544523864984512,
0.009346959181129932,
-0.07201247662305832,
-0.021487705409526825,
-0.1346573680639267,
0.22767119109630585,
-0.04908503219485283,
-0.10598073154687881,
-0.11245716363191605,
-0.0374484620988369,
0.14820502698421478,
-0.07497872412204742,
0.04626030847430229,
-0.046396009624004364,
0.10251304507255554,
-0.035131752490997314,
-0.12188176065683365,
0.06496064364910126,
-0.10281161963939667,
-0.14894403517246246,
-0.051589883863925934,
0.15676991641521454,
0.010643013752996922,
0.041232235729694366,
-0.008261027745902538,
0.06029146537184715,
-0.036181412637233734,
-0.04013286530971527,
0.07580674439668655,
0.12809894979000092,
0.06525889784097672,
0.033548541367053986,
-0.03708043694496155,
-0.05595483258366585,
-0.08525071293115616,
-0.035657044500112534,
0.07061265408992767,
0.2637471854686737,
-0.07334380596876144,
0.08157698065042496,
0.0687793642282486,
-0.08186061680316925,
-0.15565058588981628,
-0.09519156068563461,
0.01204322837293148,
0.019772004336118698,
0.05247766524553299,
-0.1142113134264946,
0.02976945973932743,
0.027056220918893814,
-0.029051974415779114,
0.08976346999406815,
-0.2667604684829712,
-0.11820167303085327,
0.03890916332602501,
0.06643844395875931,
-0.035580094903707504,
-0.16920055449008942,
-0.1200716495513916,
-0.06363443285226822,
-0.23663559556007385,
0.012562043964862823,
0.07332471013069153,
0.05009216070175171,
-0.021698985248804092,
0.06776601821184158,
0.03242848068475723,
-0.03906905651092529,
0.14732158184051514,
-0.02705681510269642,
0.0019243787974119186,
-0.10054849833250046,
-0.01930636540055275,
0.032632164657115936,
-0.07018542289733887,
0.032789815217256546,
-0.04320588335394859,
0.03387969359755516,
-0.13224194943904877,
-0.007073689252138138,
-0.0881977453827858,
0.009367482736706734,
-0.06410912424325943,
-0.02650569938123226,
-0.05651290342211723,
0.07169946283102036,
0.06593886017799377,
-0.015620921738445759,
0.003758135950192809,
-0.09027239680290222,
0.1469465047121048,
0.16174151003360748,
0.08898867666721344,
0.0341155119240284,
-0.13331373035907745,
-0.023952681571245193,
-0.04902569204568863,
0.0025863265618681908,
-0.12005462497472763,
-0.004785433411598206,
0.10012683272361755,
-0.0013097613118588924,
0.08942420035600662,
-0.01198238879442215,
-0.11803719401359558,
-0.042277876287698746,
0.1153244823217392,
-0.0666825920343399,
-0.18803666532039642,
-0.030442051589488983,
0.080091692507267,
-0.09608160704374313,
-0.019413169473409653,
0.14691312611103058,
-0.003969346173107624,
-0.05007556825876236,
0.023374170064926147,
0.043281879276037216,
-0.04459754005074501,
0.0969776064157486,
0.03363705798983574,
0.07704401761293411,
-0.09296854585409164,
0.034409672021865845,
0.061819881200790405,
-0.04498130455613136,
0.01882132701575756,
0.11504829674959183,
-0.06422808766365051,
-0.06005578488111496,
-0.03777511790394783,
0.09180513769388199,
-0.07899906486272812,
-0.034658465534448624,
-0.040820229798555374,
-0.10175354033708572,
0.043153051286935806,
0.10306331515312195,
0.013682479038834572,
-0.0011689510429278016,
0.0608297623693943,
-0.0413900688290596,
-0.045564889907836914,
0.07673177123069763,
0.0332544781267643,
0.06696672737598419,
-0.1147882491350174,
0.020433679223060608,
0.0006648744456470013,
0.04417557269334793,
-0.004243847914040089,
0.031627558171749115,
-0.09849183261394501,
-0.03355254605412483,
-0.13139283657073975,
-0.022197961807250977,
-0.1219179779291153,
-0.0406377874314785,
-0.004921696148812771,
-0.01634441688656807,
-0.014016970992088318,
-0.010206601582467556,
-0.0918421596288681,
-0.09565632045269012,
-0.02975481003522873,
0.07544699311256409,
-0.08319663256406784,
-0.0028899835888296366,
0.030878618359565735,
-0.06009889394044876,
0.035986632108688354,
0.0015603619394823909,
0.0006206633406691253,
-0.03602586314082146,
-0.06553465127944946,
-0.03860399127006531,
-0.035027746111154556,
-0.0011272674892097712,
0.03184278681874275,
-0.18469120562076569,
-0.010019328445196152,
-0.05336043983697891,
-0.10405658930540085,
-0.02023552544414997,
-0.011932066641747952,
-0.09653443098068237,
0.07053527981042862,
-0.029842456802725792,
-0.00531230540946126,
-0.04854857549071312,
-0.007699299603700638,
0.03892158344388008,
-0.016984974965453148,
0.07601825892925262,
-0.027952047064900398,
0.08310162276029587,
-0.20169983804225922,
-0.008367598988115788,
-0.023725707083940506,
-0.042052414268255234,
0.018891390413045883,
-0.04455949366092682,
0.040249936282634735,
-0.02978624403476715,
0.08046814054250717,
-0.04306577146053314,
-0.01947176642715931,
0.03662417083978653,
0.015062512829899788,
-0.022372985258698463,
0.02179509587585926,
0.12043485790491104,
0.00037080992478877306,
0.0016790011432021856,
0.0025162757374346256,
0.03352983295917511,
-0.04402706027030945,
-0.03256650269031525,
0.09759430587291718,
0.10401972383260727,
0.12742780148983002,
0.008988537825644016,
0.13248613476753235,
-0.0666721761226654,
-0.08237864077091217,
-0.0026785852387547493,
-0.030474578961730003,
0.08035600930452347,
-0.054818619042634964,
0.11329386383295059,
0.13051097095012665,
-0.16041938960552216,
0.09895175695419312,
-0.026395006105303764,
0.0010399025632068515,
-0.0758807584643364,
-0.1944383829832077,
-0.07891512662172318,
-0.08843602240085602,
0.0018188668182119727,
-0.06331603229045868,
0.0352218933403492,
0.020294981077313423,
-0.0018416497623547912,
0.007395374123007059,
0.08070007711648941,
-0.01664445362985134,
-0.009158041328191757,
0.024954022839665413,
0.03602151945233345,
-0.017639920115470886,
-0.013017315417528152,
0.018130121752619743,
0.03865031898021698,
0.04040595516562462,
0.0010290124919265509,
0.03274322301149368,
-0.036005742847919464,
0.04387633129954338,
-0.013248826377093792,
-0.12692131102085114,
0.0012165791122242808,
0.019938359037041664,
0.019738463684916496,
0.06557948887348175,
0.009919031523168087,
0.031024109572172165,
-0.03771420568227768,
0.09855705499649048,
-0.03634555637836456,
-0.04227350652217865,
-0.07526643574237823,
0.16603173315525055,
-0.07516784220933914,
-0.031225252896547318,
0.03177299723029137,
-0.08895659446716309,
-0.004618062172085047,
0.1923293024301529,
0.27183252573013306,
0.005385638680309057,
-0.0006791243213228881,
0.04126651957631111,
0.02033941075205803,
-0.014650391414761543,
0.07524584978818893,
0.052579086273908615,
0.12281832098960876,
-0.0749945119023323,
0.0613134503364563,
-0.024881679564714432,
-0.055761802941560745,
-0.03761893883347511,
0.04203939437866211,
0.01823466643691063,
-0.020015036687254906,
0.04214242100715637,
0.12260887026786804,
-0.055163800716400146,
-0.10996367782354355,
0.06167212501168251,
-0.1405808925628662,
-0.1282818466424942,
-0.0316288098692894,
0.0666559636592865,
0.04716343432664871,
0.06985419988632202,
-0.028047356754541397,
-0.044192973524332047,
0.1932276487350464,
-0.0149171631783247,
-0.07973847538232803,
-0.07912863045930862,
0.008936529979109764,
-0.11536043137311935,
0.16814100742340088,
-0.01795779913663864,
-0.026381760835647583,
0.12339150905609131,
-0.03505496308207512,
-0.1543312817811966,
0.007212586235255003,
0.0739603117108345,
-0.09768545627593994,
0.06144729629158974,
0.15172512829303741,
0.0037404941394925117,
0.05778530240058899,
0.030206289142370224,
-0.16364991664886475,
0.056904636323451996,
0.06601991504430771,
0.00019319466082379222,
-0.04235050454735756,
0.10068024694919586,
-0.07978162914514542,
0.15742889046669006,
0.17012611031532288,
-0.04542285576462746,
-0.022198524326086044,
-0.013094019144773483,
0.027841297909617424,
0.06951605528593063,
0.09029851853847504,
-0.030499404296278954,
-0.16005539894104004,
0.02589005045592785,
-0.006462227087467909,
0.0747760757803917,
-0.21456778049468994,
-0.0933753103017807,
-0.02608180046081543,
-0.024294987320899963,
-0.0623471662402153,
0.11952909827232361,
0.09083446860313416,
0.04744979366660118,
-0.026716122403740883,
-0.05413394421339035,
-0.0074105276726186275,
0.1411927193403244,
-0.14502862095832825,
-0.07521994411945343
] |
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ai4privacy_v2_adapter_en
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1079
- Overall Precision: 0.8136
- Overall Recall: 0.8836
- Overall F1: 0.8472
- Overall Accuracy: 0.9560
- Accountname F1: 0.9712
- Accountnumber F1: 0.9677
- Age F1: 0.8432
- Amount F1: 0.7929
- Bic F1: 0.9689
- Bitcoinaddress F1: 0.9343
- Buildingnumber F1: 0.8405
- City F1: 0.8139
- Companyname F1: 0.9310
- County F1: 0.8406
- Creditcardcvv F1: 0.8889
- Creditcardissuer F1: 0.9661
- Creditcardnumber F1: 0.8404
- Currency F1: 0.5968
- Currencycode F1: 0.6556
- Currencyname F1: 0.0182
- Currencysymbol F1: 0.8176
- Date F1: 0.7858
- Dob F1: 0.4636
- Email F1: 0.9928
- Ethereumaddress F1: 0.9941
- Eyecolor F1: 0.7859
- Firstname F1: 0.8699
- Gender F1: 0.8945
- Height F1: 0.9227
- Iban F1: 0.9730
- Ip F1: 0.0497
- Ipv4 F1: 0.8345
- Ipv6 F1: 0.4659
- Jobarea F1: 0.9131
- Jobtitle F1: 0.9599
- Jobtype F1: 0.9303
- Lastname F1: 0.8016
- Litecoinaddress F1: 0.8483
- Mac F1: 0.9817
- Maskednumber F1: 0.7049
- Middlename F1: 0.5006
- Nearbygpscoordinate F1: 0.9969
- Ordinaldirection F1: 0.9519
- Password F1: 0.9780
- Phoneimei F1: 0.9928
- Phonenumber F1: 0.9752
- Pin F1: 0.7525
- Prefix F1: 0.9121
- Secondaryaddress F1: 0.9474
- Sex F1: 0.9770
- Ssn F1: 0.9771
- State F1: 0.8680
- Street F1: 0.8677
- Time F1: 0.9516
- Url F1: 0.9975
- Useragent F1: 0.9844
- Username F1: 0.9669
- Vehiclevin F1: 0.9775
- Vehiclevrm F1: 0.9888
- Zipcode F1: 0.8203
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Accountname F1 | Accountnumber F1 | Age F1 | Amount F1 | Bic F1 | Bitcoinaddress F1 | Buildingnumber F1 | City F1 | Companyname F1 | County F1 | Creditcardcvv F1 | Creditcardissuer F1 | Creditcardnumber F1 | Currency F1 | Currencycode F1 | Currencyname F1 | Currencysymbol F1 | Date F1 | Dob F1 | Email F1 | Ethereumaddress F1 | Eyecolor F1 | Firstname F1 | Gender F1 | Height F1 | Iban F1 | Ip F1 | Ipv4 F1 | Ipv6 F1 | Jobarea F1 | Jobtitle F1 | Jobtype F1 | Lastname F1 | Litecoinaddress F1 | Mac F1 | Maskednumber F1 | Middlename F1 | Nearbygpscoordinate F1 | Ordinaldirection F1 | Password F1 | Phoneimei F1 | Phonenumber F1 | Pin F1 | Prefix F1 | Secondaryaddress F1 | Sex F1 | Ssn F1 | State F1 | Street F1 | Time F1 | Url F1 | Useragent F1 | Username F1 | Vehiclevin F1 | Vehiclevrm F1 | Zipcode F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
| 0.9109 | 1.0 | 1088 | 0.5093 | 0.2688 | 0.3282 | 0.2956 | 0.8499 | 0.2034 | 0.3040 | 0.0752 | 0.1147 | 0.0935 | 0.5972 | 0.0673 | 0.0 | 0.0024 | 0.0 | 0.0 | 0.0 | 0.1141 | 0.0 | 0.0 | 0.0 | 0.0112 | 0.7137 | 0.0 | 0.9095 | 0.9119 | 0.0 | 0.3152 | 0.0 | 0.0 | 0.8248 | 0.0 | 0.6785 | 0.4199 | 0.0 | 0.0475 | 0.0 | 0.0167 | 0.0907 | 0.6333 | 0.0011 | 0.0 | 0.9525 | 0.0 | 0.6438 | 0.3918 | 0.2703 | 0.0 | 0.0099 | 0.2395 | 0.0 | 0.0220 | 0.0 | 0.0276 | 0.5557 | 0.9658 | 0.8157 | 0.0415 | 0.3955 | 0.0106 | 0.0181 |
| 0.2793 | 2.0 | 2176 | 0.1903 | 0.6974 | 0.7582 | 0.7265 | 0.9309 | 0.9684 | 0.8789 | 0.7561 | 0.3604 | 0.7609 | 0.8715 | 0.6492 | 0.4956 | 0.8028 | 0.5558 | 0.7756 | 0.6575 | 0.5363 | 0.4671 | 0.128 | 0.0 | 0.5910 | 0.7731 | 0.0186 | 0.9838 | 0.9465 | 0.4482 | 0.7689 | 0.5160 | 0.7446 | 0.9234 | 0.0 | 0.8226 | 0.8007 | 0.5589 | 0.8712 | 0.6553 | 0.6634 | 0.7056 | 0.9315 | 0.0382 | 0.0661 | 0.9954 | 0.8828 | 0.9270 | 0.9693 | 0.8621 | 0.1481 | 0.8783 | 0.9120 | 0.9262 | 0.8707 | 0.6693 | 0.7378 | 0.9152 | 0.9886 | 0.9524 | 0.8859 | 0.8352 | 0.8976 | 0.6466 |
| 0.1707 | 3.0 | 3264 | 0.1388 | 0.7704 | 0.8319 | 0.8000 | 0.9467 | 0.9702 | 0.9396 | 0.8120 | 0.6102 | 0.9298 | 0.9034 | 0.7409 | 0.6205 | 0.8922 | 0.7128 | 0.8446 | 0.9218 | 0.6983 | 0.5504 | 0.5380 | 0.0106 | 0.6877 | 0.6125 | 0.3259 | 0.9892 | 0.9956 | 0.6647 | 0.8358 | 0.7540 | 0.8859 | 0.9430 | 0.0 | 0.8313 | 0.7993 | 0.8235 | 0.9241 | 0.8191 | 0.7504 | 0.7882 | 0.9412 | 0.5129 | 0.4005 | 0.9969 | 0.9452 | 0.9618 | 0.9900 | 0.9452 | 0.5018 | 0.8959 | 0.9348 | 0.9406 | 0.9524 | 0.7643 | 0.7747 | 0.9497 | 0.9943 | 0.9714 | 0.9274 | 0.9048 | 0.9646 | 0.7387 |
| 0.1373 | 4.0 | 4352 | 0.1197 | 0.7751 | 0.8645 | 0.8174 | 0.9509 | 0.9651 | 0.9510 | 0.8263 | 0.7169 | 0.9592 | 0.9254 | 0.8151 | 0.7795 | 0.9148 | 0.8060 | 0.8808 | 0.9524 | 0.8007 | 0.5676 | 0.5656 | 0.0249 | 0.8000 | 0.7858 | 0.3425 | 0.9910 | 0.9869 | 0.7552 | 0.8609 | 0.8397 | 0.8981 | 0.9779 | 0.0278 | 0.8309 | 0.3179 | 0.8643 | 0.9475 | 0.9000 | 0.7812 | 0.8415 | 0.9749 | 0.6191 | 0.4617 | 0.9969 | 0.9519 | 0.9711 | 0.9914 | 0.9700 | 0.6733 | 0.9088 | 0.9421 | 0.9732 | 0.9671 | 0.8360 | 0.8494 | 0.9442 | 0.9943 | 0.9618 | 0.9487 | 0.9838 | 0.9672 | 0.8093 |
| 0.1202 | 5.0 | 5440 | 0.1106 | 0.8264 | 0.8796 | 0.8522 | 0.9564 | 0.9720 | 0.9634 | 0.8360 | 0.7423 | 0.9756 | 0.9327 | 0.8268 | 0.8031 | 0.9134 | 0.8404 | 0.8792 | 0.9660 | 0.7957 | 0.5723 | 0.6159 | 0.0167 | 0.8132 | 0.7914 | 0.4301 | 0.9928 | 0.9941 | 0.7544 | 0.8659 | 0.8871 | 0.9121 | 0.9695 | 0.0137 | 0.8361 | 0.7008 | 0.9108 | 0.9623 | 0.9126 | 0.7783 | 0.8459 | 0.9749 | 0.6770 | 0.4944 | 0.9985 | 0.9519 | 0.9754 | 0.9900 | 0.9673 | 0.7647 | 0.9115 | 0.9484 | 0.9760 | 0.9771 | 0.8588 | 0.8590 | 0.9526 | 0.9975 | 0.9820 | 0.9547 | 0.9871 | 0.9916 | 0.8133 |
| 0.1065 | 6.0 | 6528 | 0.1079 | 0.8136 | 0.8836 | 0.8472 | 0.9560 | 0.9712 | 0.9677 | 0.8432 | 0.7929 | 0.9689 | 0.9343 | 0.8405 | 0.8139 | 0.9310 | 0.8406 | 0.8889 | 0.9661 | 0.8404 | 0.5968 | 0.6556 | 0.0182 | 0.8176 | 0.7858 | 0.4636 | 0.9928 | 0.9941 | 0.7859 | 0.8699 | 0.8945 | 0.9227 | 0.9730 | 0.0497 | 0.8345 | 0.4659 | 0.9131 | 0.9599 | 0.9303 | 0.8016 | 0.8483 | 0.9817 | 0.7049 | 0.5006 | 0.9969 | 0.9519 | 0.9780 | 0.9928 | 0.9752 | 0.7525 | 0.9121 | 0.9474 | 0.9770 | 0.9771 | 0.8680 | 0.8677 | 0.9516 | 0.9975 | 0.9844 | 0.9669 | 0.9775 | 0.9888 | 0.8203 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-multilingual-cased", "model-index": [{"name": "ai4privacy_v2_adapter_en", "results": []}]} | null | Isotonic/ai4privacy_v2_adapter_en | [
"safetensors",
"generated_from_trainer",
"base_model:distilbert-base-multilingual-cased",
"license:apache-2.0",
"region:us"
] | 2024-02-11T05:21:15+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-distilbert-base-multilingual-cased #license-apache-2.0 #region-us
| ai4privacy\_v2\_adapter\_en
===========================
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1079
* Overall Precision: 0.8136
* Overall Recall: 0.8836
* Overall F1: 0.8472
* Overall Accuracy: 0.9560
* Accountname F1: 0.9712
* Accountnumber F1: 0.9677
* Age F1: 0.8432
* Amount F1: 0.7929
* Bic F1: 0.9689
* Bitcoinaddress F1: 0.9343
* Buildingnumber F1: 0.8405
* City F1: 0.8139
* Companyname F1: 0.9310
* County F1: 0.8406
* Creditcardcvv F1: 0.8889
* Creditcardissuer F1: 0.9661
* Creditcardnumber F1: 0.8404
* Currency F1: 0.5968
* Currencycode F1: 0.6556
* Currencyname F1: 0.0182
* Currencysymbol F1: 0.8176
* Date F1: 0.7858
* Dob F1: 0.4636
* Email F1: 0.9928
* Ethereumaddress F1: 0.9941
* Eyecolor F1: 0.7859
* Firstname F1: 0.8699
* Gender F1: 0.8945
* Height F1: 0.9227
* Iban F1: 0.9730
* Ip F1: 0.0497
* Ipv4 F1: 0.8345
* Ipv6 F1: 0.4659
* Jobarea F1: 0.9131
* Jobtitle F1: 0.9599
* Jobtype F1: 0.9303
* Lastname F1: 0.8016
* Litecoinaddress F1: 0.8483
* Mac F1: 0.9817
* Maskednumber F1: 0.7049
* Middlename F1: 0.5006
* Nearbygpscoordinate F1: 0.9969
* Ordinaldirection F1: 0.9519
* Password F1: 0.9780
* Phoneimei F1: 0.9928
* Phonenumber F1: 0.9752
* Pin F1: 0.7525
* Prefix F1: 0.9121
* Secondaryaddress F1: 0.9474
* Sex F1: 0.9770
* Ssn F1: 0.9771
* State F1: 0.8680
* Street F1: 0.8677
* Time F1: 0.9516
* Url F1: 0.9975
* Useragent F1: 0.9844
* Username F1: 0.9669
* Vehiclevin F1: 0.9775
* Vehiclevrm F1: 0.9888
* Zipcode F1: 0.8203
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 6
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.2\n* num\\_epochs: 6",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#safetensors #generated_from_trainer #base_model-distilbert-base-multilingual-cased #license-apache-2.0 #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.2\n* num\\_epochs: 6",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
43,
116,
4,
33
] | [
"passage: TAGS\n#safetensors #generated_from_trainer #base_model-distilbert-base-multilingual-cased #license-apache-2.0 #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.2\n* num\\_epochs: 6### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.10187412798404694,
0.030679218471050262,
-0.0013444607611745596,
0.1160336583852768,
0.1429014801979065,
0.017121508717536926,
0.15973567962646484,
0.08045288175344467,
-0.08108053356409073,
0.04906095936894417,
0.10214482992887497,
0.10047328472137451,
0.007974560372531414,
0.14775563776493073,
-0.055213019251823425,
-0.21338608860969543,
0.028125574812293053,
-0.03250459209084511,
-0.030238425359129906,
0.11835934221744537,
0.08213379234075546,
-0.1251591145992279,
0.07268892973661423,
-0.04611899331212044,
-0.18063537776470184,
0.024436382576823235,
0.020954817533493042,
-0.03538532555103302,
0.13986875116825104,
-0.01171921193599701,
0.13234581053256989,
0.019298261031508446,
0.12444368004798889,
-0.21908323466777802,
0.007812121883034706,
0.06283790618181229,
0.00447246665135026,
0.052148833870887756,
0.04673387482762337,
-0.04096323251724243,
0.09398963302373886,
-0.11819085478782654,
0.047543931752443314,
0.01864491030573845,
-0.13088130950927734,
-0.20869393646717072,
-0.09640226513147354,
-0.00588263152167201,
0.07039199024438858,
0.06772059202194214,
-0.010605166666209698,
0.13860014081001282,
-0.07860761135816574,
0.09359829872846603,
0.2420767843723297,
-0.3120308220386505,
-0.06554342061281204,
0.07985424995422363,
0.026211777701973915,
0.11015909165143967,
-0.10823193937540054,
-0.01632663421332836,
0.07260463386774063,
0.034968916326761246,
0.1198611631989479,
-0.03744184970855713,
-0.16362491250038147,
0.009028006345033646,
-0.14546474814414978,
0.016929417848587036,
0.0729445368051529,
0.04524305462837219,
-0.0647595226764679,
-0.0003682644455693662,
-0.07533033192157745,
-0.11372021585702896,
-0.05971216782927513,
-0.011576859280467033,
0.07887061685323715,
-0.026798635721206665,
-0.040520600974559784,
-0.0074644992128014565,
-0.08281680196523666,
-0.09672312438488007,
-0.05297171324491501,
0.21604661643505096,
0.04335497319698334,
0.02272411808371544,
-0.015504708513617516,
0.09832513332366943,
-0.08233404904603958,
-0.1332654058933258,
0.023352252319455147,
0.01455307099968195,
-0.0033688400872051716,
-0.04156474769115448,
-0.061083778738975525,
-0.036882203072309494,
0.050431132316589355,
0.13157320022583008,
-0.12769843637943268,
0.06121893972158432,
-0.017977187409996986,
0.019341306760907173,
-0.1056613177061081,
0.13559387624263763,
-0.04505596309900284,
-0.045998748391866684,
0.023810142651200294,
0.0871397852897644,
0.05051165074110031,
0.0003699090739246458,
-0.07955963164567947,
0.01991676725447178,
0.09651338309049606,
0.036653611809015274,
-0.09855599701404572,
0.046817027032375336,
-0.04771978035569191,
0.029833892360329628,
-0.013342073187232018,
-0.11546868085861206,
0.03772522136569023,
0.010685778222978115,
-0.06555292010307312,
-0.06079921871423721,
0.010496538132429123,
0.029117101803421974,
0.015889625996351242,
0.10030989348888397,
-0.07249799370765686,
0.05980226397514343,
-0.09799828380346298,
-0.12252147495746613,
-0.0036658106837421656,
-0.04371136054396629,
0.010889687575399876,
-0.0867731124162674,
-0.18370398879051208,
-0.01217692345380783,
0.05509883165359497,
-0.049958936870098114,
0.02284936234354973,
-0.07073844224214554,
-0.08572685718536377,
0.0032185425516217947,
-0.01774023286998272,
0.09863420575857162,
-0.08598985522985458,
0.0893569216132164,
0.044873498380184174,
0.06691848486661911,
-0.08721227198839188,
0.017200028523802757,
-0.10702861100435257,
0.020250901579856873,
-0.2410125583410263,
0.03870173916220665,
-0.08319772779941559,
0.061564475297927856,
-0.08133149147033691,
-0.08456069231033325,
0.0013841186882928014,
-0.0022069814149290323,
0.10910408198833466,
0.1313134729862213,
-0.21061120927333832,
-0.03353289142251015,
0.19395455718040466,
-0.11305401474237442,
-0.10647261142730713,
0.11584670841693878,
-0.05658898130059242,
0.048649806529283524,
0.07774394750595093,
0.21565312147140503,
-0.009402076713740826,
-0.1246015727519989,
0.022448047995567322,
-0.021263420581817627,
0.058995019644498825,
-0.010039332322776318,
0.049846336245536804,
-0.0015912919770926237,
-0.03437616303563118,
0.02210399881005287,
-0.03791099786758423,
0.05389143154025078,
-0.10492052137851715,
-0.07912147790193558,
-0.05545081943273544,
-0.11311405897140503,
0.03535076230764389,
0.03389681875705719,
0.051395807415246964,
-0.13958771526813507,
-0.05322279408574104,
0.055043380707502365,
0.08093133568763733,
-0.060362860560417175,
0.03581039607524872,
-0.0545298270881176,
0.04821208491921425,
-0.018208075314760208,
-0.031168092042207718,
-0.163583442568779,
-0.057429809123277664,
0.0287680272012949,
0.012608819641172886,
0.029026024043560028,
-0.05935268849134445,
0.07774682343006134,
0.10005880892276764,
-0.08166182041168213,
-0.015355591662228107,
-0.028337562456727028,
0.010842169634997845,
-0.11548799276351929,
-0.23115329444408417,
0.001922020222991705,
-0.03739386796951294,
0.10933899134397507,
-0.19439469277858734,
0.03181134909391403,
-0.04087665677070618,
0.058838941156864166,
0.016091125085949898,
-0.004191585350781679,
-0.031706299632787704,
0.08648613840341568,
-0.009475902654230595,
-0.06639626622200012,
0.049096040427684784,
-0.008392834104597569,
-0.07614262402057648,
-0.04747401177883148,
-0.11017104238271713,
0.15183338522911072,
0.12781848013401031,
-0.04964880645275116,
-0.08458179980516434,
-0.00756498659029603,
-0.038066282868385315,
-0.030505526810884476,
-0.049055296927690506,
0.05264664813876152,
0.12687160074710846,
-0.009575819596648216,
0.1149040088057518,
-0.08967261761426926,
0.001249032444320619,
0.0020429997239261866,
-0.04460212588310242,
0.04885711148381233,
0.09763369709253311,
0.07266221195459366,
-0.07624158263206482,
0.11115501075983047,
0.17209210991859436,
-0.09764066338539124,
0.08902613073587418,
-0.05550828203558922,
-0.056128885596990585,
-0.02873220108449459,
0.025659756734967232,
-0.019527621567249298,
0.13692831993103027,
-0.05095899850130081,
0.02972654066979885,
-0.012664400041103363,
0.04440639168024063,
0.007708957884460688,
-0.2254326492547989,
-0.04008178412914276,
-0.005182106047868729,
-0.07845667749643326,
-0.043913595378398895,
-0.03208582475781441,
0.004912740550935268,
0.10303980112075806,
-0.03523731976747513,
-0.09410788118839264,
0.011572781018912792,
-0.007879379205405712,
-0.06730230152606964,
0.2214122861623764,
-0.11182189732789993,
-0.0550137534737587,
-0.07416889071464539,
-0.06283263862133026,
-0.06137670949101448,
0.004858510568737984,
0.06388486921787262,
-0.09294839203357697,
-0.03166256844997406,
-0.11155234277248383,
0.022949445992708206,
0.05836646631360054,
0.02567882090806961,
0.006993964314460754,
-0.011101480573415756,
0.08272543549537659,
-0.12243492156267166,
-0.008360461331903934,
-0.05853590369224548,
-0.06824134290218353,
0.05350447818636894,
0.06765197962522507,
0.09914514422416687,
0.12348243594169617,
-0.020305586978793144,
-0.01490966696292162,
-0.028729675337672234,
0.2593331038951874,
-0.026394637301564217,
-0.025180116295814514,
0.10077665001153946,
-0.006112057715654373,
0.057471878826618195,
0.15525731444358826,
0.07819737493991852,
-0.13592727482318878,
0.026456592604517937,
0.0369684174656868,
-0.023406021296977997,
-0.22154591977596283,
-0.03579966723918915,
-0.018349381163716316,
-0.04755324870347977,
0.04498908668756485,
0.02495490573346615,
-0.038698647171258926,
0.04436240717768669,
0.04384096711874008,
0.027797887101769447,
-0.003069529077038169,
0.04799717664718628,
0.04778677970170975,
0.050859998911619186,
0.10814729332923889,
-0.04287821799516678,
-0.046807482838630676,
0.04066246747970581,
-0.009608656167984009,
0.21699444949626923,
0.005810425616800785,
0.06572507321834564,
0.06107763200998306,
0.19868087768554688,
-0.02206355147063732,
0.09733572602272034,
-0.0006739122327417135,
-0.047008369117975235,
-0.016746222972869873,
-0.06401348859071732,
-0.01393013633787632,
0.02739568240940571,
-0.1303001195192337,
0.059295956045389175,
-0.09952487051486969,
0.013439351692795753,
0.0829562246799469,
0.2640901803970337,
0.036381617188453674,
-0.29263290762901306,
-0.048872120678424835,
0.021626340225338936,
-0.013446420431137085,
-0.016168473288416862,
0.03280145674943924,
0.14404428005218506,
-0.0386531800031662,
0.06212439015507698,
-0.04775754362344742,
0.07173269242048264,
0.030325282365083694,
0.03427433595061302,
0.01992541365325451,
0.12733688950538635,
-0.0167823638767004,
0.034263040870428085,
-0.28469181060791016,
0.2920030951499939,
0.026281842961907387,
0.10370554774999619,
-0.03026283159852028,
-0.01171559002250433,
0.033426471054553986,
0.08325494080781937,
0.0647430494427681,
-0.01241295412182808,
-0.09808770567178726,
-0.17523208260536194,
-0.05918509140610695,
0.05760037153959274,
0.1387293040752411,
0.012899922206997871,
0.10356532037258148,
-0.012693062424659729,
0.003228368703275919,
0.08561266213655472,
-0.05131688341498375,
-0.15803992748260498,
-0.03989380598068237,
-0.05457967519760132,
0.05558229237794876,
-0.018026672303676605,
-0.08029235899448395,
-0.09224628657102585,
-0.1134331226348877,
0.09347211569547653,
0.011332010850310326,
-0.018518565222620964,
-0.09933041781187057,
0.05217953398823738,
0.10263659805059433,
-0.059982381761074066,
0.04053277149796486,
0.02420951798558235,
0.022471796721220016,
0.033748045563697815,
-0.04960692673921585,
0.12658707797527313,
-0.07414305210113525,
-0.15287011861801147,
-0.05424218252301216,
0.09901385754346848,
0.048931632190942764,
0.039069775491952896,
-0.015992429107427597,
0.008708668872714043,
0.008845318108797073,
-0.1047578752040863,
0.002305623609572649,
-0.023259509354829788,
0.061357282102108,
0.058755360543727875,
-0.08934332430362701,
-0.036723170429468155,
-0.058454662561416626,
-0.021301886066794395,
0.14009608328342438,
0.33948245644569397,
-0.07420827448368073,
0.02242242358624935,
0.09926644712686539,
-0.0597335584461689,
-0.18654745817184448,
0.05305619165301323,
0.027389032766222954,
-0.0019053679425269365,
0.08092393726110458,
-0.13625629246234894,
0.1202360987663269,
0.11568012833595276,
-0.017997518181800842,
0.10267133265733719,
-0.3004167079925537,
-0.13917219638824463,
0.09516182541847229,
0.17446641623973846,
0.151154026389122,
-0.1627427488565445,
-0.017017880454659462,
-0.03343116492033005,
-0.10025948286056519,
0.0892556831240654,
-0.17933738231658936,
0.1017712950706482,
-0.002918839454650879,
0.060738854110240936,
0.0006556780426762998,
-0.04893036186695099,
0.14256104826927185,
0.017246173694729805,
0.14807111024856567,
-0.04714712128043175,
0.012862781062722206,
0.052496109157800674,
-0.040287960320711136,
0.036602187901735306,
-0.10845663398504257,
0.04508150368928909,
0.008649677969515324,
-0.007758619263768196,
-0.06775859743356705,
0.028915802016854286,
-0.03425566852092743,
-0.061055950820446014,
-0.02767511084675789,
0.02880607172846794,
0.04634023457765579,
-0.022619379684329033,
0.09887100756168365,
0.010914490558207035,
0.15254086256027222,
0.12136095017194748,
0.050390247255563736,
-0.08213040977716446,
0.03806457296013832,
0.03244786337018013,
-0.02397095039486885,
0.04512474685907364,
-0.14188852906227112,
0.03550611436367035,
0.1093616783618927,
0.008521833457052708,
0.12616223096847534,
0.06825461238622665,
-0.028137583285570145,
0.009232263080775738,
0.07514489442110062,
-0.1619955152273178,
-0.10604451596736908,
0.042739737778902054,
-0.046960242092609406,
-0.08184784650802612,
0.07913166284561157,
0.10620111227035522,
-0.06795774400234222,
-0.0018124172929674387,
-0.03285716846585274,
0.03212329000234604,
-0.07653988152742386,
0.20294305682182312,
0.058266375213861465,
0.037607885897159576,
-0.10479909926652908,
0.11052339524030685,
0.029376685619354248,
-0.037955429404973984,
0.0046548726968467236,
0.0717136487364769,
-0.08474460989236832,
-0.023310808464884758,
0.1196419894695282,
0.1940975785255432,
-0.023677190765738487,
-0.05727727338671684,
-0.12905612587928772,
-0.11528712511062622,
0.018672747537493706,
0.19995039701461792,
0.09544511139392853,
0.0010199368698522449,
0.0005960940034128726,
0.011280667968094349,
-0.096156544983387,
0.08553199470043182,
0.03781226649880409,
0.07538194209337234,
-0.1206698939204216,
0.12730760872364044,
0.0023229813668876886,
0.010560392402112484,
-0.028171299025416374,
0.06022271141409874,
-0.12416993826627731,
0.01279657892882824,
-0.15116064250469208,
-0.012503216043114662,
-0.01888422481715679,
0.016367685049772263,
0.010442850179970264,
-0.0794953927397728,
-0.07153137028217316,
0.022351620718836784,
-0.11531634628772736,
-0.010171739384531975,
0.022701919078826904,
0.051309119910001755,
-0.14591558277606964,
-0.04778692498803139,
0.020274532958865166,
-0.05501735210418701,
0.061502519994974136,
0.05876941978931427,
-0.0011929627507925034,
0.08546682447195053,
-0.2308381199836731,
0.002981019439175725,
0.06911680102348328,
-0.009897767566144466,
0.05546678230166435,
-0.07424891740083694,
-0.03379169851541519,
0.000010016740816354286,
0.08630896359682083,
0.019800422713160515,
0.10849347710609436,
-0.11489364504814148,
-0.001469182432629168,
-0.04955942556262016,
-0.07231146842241287,
-0.025414645671844482,
-0.010476786643266678,
0.09839341044425964,
0.0015768831362947822,
0.17302261292934418,
-0.10217634588479996,
0.004157467745244503,
-0.19356290996074677,
-0.010737009346485138,
-0.016958696767687798,
-0.09911497682332993,
-0.15943509340286255,
-0.049839697778224945,
0.07079597562551498,
-0.04720258712768555,
0.14371050894260406,
0.0073481216095387936,
0.05258527398109436,
0.01613566279411316,
-0.06252922862768173,
0.013342870399355888,
0.04043206945061684,
0.21001122891902924,
0.022734014317393303,
-0.03154445067048073,
0.03413620963692665,
0.037110090255737305,
0.10537615418434143,
0.06085120141506195,
0.22609297931194305,
0.18837808072566986,
-0.0071396175771951675,
0.11280299723148346,
0.0393548347055912,
-0.0741797536611557,
-0.08828079700469971,
0.06449993699789047,
-0.03582720831036568,
0.0486694760620594,
-0.037622421979904175,
0.23919540643692017,
0.0602438747882843,
-0.16184517741203308,
0.039205554872751236,
-0.04899223521351814,
-0.08759315311908722,
-0.12065140902996063,
0.019248085096478462,
-0.09035126119852066,
-0.18720391392707825,
0.001375500694848597,
-0.11248232424259186,
0.0342327244579792,
0.12423382699489594,
0.012491339817643166,
0.012157250195741653,
0.1973106861114502,
0.012582183815538883,
0.04559260606765747,
0.03663511574268341,
-0.00045602850150316954,
-0.0332600362598896,
-0.03755418211221695,
-0.1186315193772316,
0.009525211527943611,
-0.021119559183716774,
0.023996738716959953,
-0.042920369654893875,
-0.05325552076101303,
0.058602914214134216,
-0.02888302132487297,
-0.08903506398200989,
0.01824009232223034,
0.030434831976890564,
0.06776440143585205,
0.052656225860118866,
0.03843974694609642,
-0.01168945711106062,
0.0055567133240401745,
0.23136913776397705,
-0.07249246537685394,
-0.11169827729463577,
-0.08263343572616577,
0.24909473955631256,
0.026235738769173622,
0.029966669157147408,
-0.00631578266620636,
-0.09154726564884186,
0.0053319321013987064,
0.1713017374277115,
0.16565172374248505,
-0.12977759540081024,
-0.0047888667322695255,
-0.04613107070326805,
-0.014482375234365463,
-0.05367652326822281,
0.11435850709676743,
0.12664397060871124,
-0.005698797293007374,
-0.09692629426717758,
-0.03240214288234711,
-0.055695317685604095,
-0.015317736193537712,
-0.07012607157230377,
0.032668717205524445,
-0.008478209376335144,
-0.0008945842855609953,
-0.05025510489940643,
0.08195414394140244,
-0.042070526629686356,
-0.12040392309427261,
0.06157618761062622,
-0.17298075556755066,
-0.15161308646202087,
-0.014682764187455177,
0.11906445771455765,
0.00048721744678914547,
0.04157733917236328,
-0.050625912845134735,
-0.000004945680302625988,
0.04070381820201874,
-0.041454631835222244,
-0.03135431557893753,
-0.13057324290275574,
0.06143214926123619,
-0.10586655884981155,
0.22866427898406982,
-0.015589875169098377,
0.07279864698648453,
0.11519290506839752,
0.041415974497795105,
-0.07344741374254227,
0.11504977941513062,
0.04522691294550896,
-0.10976015776395798,
0.013815813697874546,
0.08757457137107849,
-0.06812708079814911,
0.0895576924085617,
0.03953351452946663,
-0.09317289292812347,
0.021762873977422714,
-0.000025151955924229696,
-0.09235833585262299,
-0.055445488542318344,
-0.06908749043941498,
-0.07744430005550385,
0.11772727221250534,
0.1746578961610794,
-0.028543461114168167,
0.05900491401553154,
-0.06026042625308037,
0.04939837381243706,
0.03837941586971283,
0.05708855018019676,
-0.05196620151400566,
-0.266257107257843,
0.05054602399468422,
0.13722547888755798,
-0.015762198716402054,
-0.21428431570529938,
-0.08015573769807816,
0.012325551360845566,
-0.030376384034752846,
-0.11091670393943787,
0.09716849029064178,
0.10957714915275574,
0.040667824447155,
-0.042496636509895325,
-0.21438057720661163,
-0.07259775698184967,
0.17031076550483704,
-0.12766291201114655,
-0.10589152574539185
] |
null | null | diffusers | # Nico Yazawa
<Gallery />
## Model description
This model was trained to generate high quality images based on SIFAS cards.
To achieve better quality, you should be using hako-mikan's regional prompter, along with Latent Mode, which modifies the way Stable Diffusion isolates the LoRA resulting in a significant improvement.
## Trigger words
You should use `id_nico_yazawa` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/theidoldaily/nico-yazawa/tree/main) them in the Files & versions tab.
| {"license": "mit", "tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "masterpiece, high quality, defined pupil, looking at viewer, rounded pupil, defined iris, (soft iris:1.2),", "parameters": {"negative_prompt": "bad_anatomy, deformation, amputation, deformity, deformed_nipples, duplicated_torso, deformed_torso, long_torso, large_torso, unproportioned_torso, (deformed_pussy:1.2), (deformed_hands:1.2), unproportioned_eyes, unproportioned_head, small_head, duplicated_nose, big_nose, fusioned_clothes, fusioned_arms, undefined_limbs, divided_pussy, red_pussy, duplicated_pussy, deformed_anus, deformed_pussy,"}, "output": {"url": "images/nicochan.png"}}], "base_model": "cagliostrolab/animagine-xl-3.0", "instance_prompt": "id_nico_yazawa"} | text-to-image | theidoldaily/nico-yazawa | [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:cagliostrolab/animagine-xl-3.0",
"license:mit",
"region:us"
] | 2024-02-11T05:22:46+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-cagliostrolab/animagine-xl-3.0 #license-mit #region-us
| # Nico Yazawa
<Gallery />
## Model description
This model was trained to generate high quality images based on SIFAS cards.
To achieve better quality, you should be using hako-mikan's regional prompter, along with Latent Mode, which modifies the way Stable Diffusion isolates the LoRA resulting in a significant improvement.
## Trigger words
You should use 'id_nico_yazawa' to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
| [
"# Nico Yazawa\n\n<Gallery />",
"## Model description \n\nThis model was trained to generate high quality images based on SIFAS cards.\n\nTo achieve better quality, you should be using hako-mikan's regional prompter, along with Latent Mode, which modifies the way Stable Diffusion isolates the LoRA resulting in a significant improvement.",
"## Trigger words\n\nYou should use 'id_nico_yazawa' to trigger the image generation.",
"## Download model\n\nWeights for this model are available in Safetensors format.\n\nDownload them in the Files & versions tab."
] | [
"TAGS\n#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-cagliostrolab/animagine-xl-3.0 #license-mit #region-us \n",
"# Nico Yazawa\n\n<Gallery />",
"## Model description \n\nThis model was trained to generate high quality images based on SIFAS cards.\n\nTo achieve better quality, you should be using hako-mikan's regional prompter, along with Latent Mode, which modifies the way Stable Diffusion isolates the LoRA resulting in a significant improvement.",
"## Trigger words\n\nYou should use 'id_nico_yazawa' to trigger the image generation.",
"## Download model\n\nWeights for this model are available in Safetensors format.\n\nDownload them in the Files & versions tab."
] | [
56,
9,
68,
21,
28
] | [
"passage: TAGS\n#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-cagliostrolab/animagine-xl-3.0 #license-mit #region-us \n# Nico Yazawa\n\n<Gallery />## Model description \n\nThis model was trained to generate high quality images based on SIFAS cards.\n\nTo achieve better quality, you should be using hako-mikan's regional prompter, along with Latent Mode, which modifies the way Stable Diffusion isolates the LoRA resulting in a significant improvement.## Trigger words\n\nYou should use 'id_nico_yazawa' to trigger the image generation.## Download model\n\nWeights for this model are available in Safetensors format.\n\nDownload them in the Files & versions tab."
] | [
-0.05649413913488388,
-0.07903548330068588,
-0.0009592294809408486,
0.022497758269309998,
0.1347472369670868,
0.06044797971844673,
0.2401943951845169,
0.06103609502315521,
0.09342169016599655,
0.060754068195819855,
0.015022181905806065,
0.053823184221982956,
0.07258201390504837,
0.2310543805360794,
-0.03347219154238701,
-0.25115346908569336,
0.10615485906600952,
-0.03627773001790047,
0.0021277032792568207,
0.03658372536301613,
0.04921890050172806,
-0.05281838774681091,
0.10582321137189865,
-0.013739231042563915,
-0.13076245784759521,
0.02052583545446396,
-0.0018725373083725572,
-0.027527915313839912,
0.02197246439754963,
0.06979066878557205,
0.02910073660314083,
0.08893158286809921,
0.0619715116918087,
-0.1526051014661789,
0.06624031066894531,
0.015737105160951614,
-0.038410790264606476,
-0.015049643814563751,
0.00960741937160492,
-0.03646504506468773,
0.22426268458366394,
-0.08746135234832764,
-0.08495903760194778,
-0.02365121804177761,
-0.04358329996466637,
-0.0945054441690445,
-0.018670810386538506,
-0.05466831475496292,
0.15487076342105865,
0.0034253604244440794,
-0.0175661351531744,
-0.050281938165426254,
-0.0058657219633460045,
0.015879692509770393,
0.19163180887699127,
-0.15348123013973236,
-0.0666268840432167,
0.17151440680027008,
0.021592309698462486,
0.13722388446331024,
-0.021368803456425667,
0.14855265617370605,
0.11829646676778793,
-0.0770362988114357,
0.05212213471531868,
-0.02747366949915886,
0.17083494365215302,
-0.046633265912532806,
-0.07143854349851608,
-0.009335970506072044,
0.28576064109802246,
0.026102647185325623,
-0.03911354020237923,
-0.15110290050506592,
-0.061092205345630646,
0.1674385517835617,
-0.09170188009738922,
-0.008164854720234871,
-0.01617073081433773,
0.00868285819888115,
0.04552259296178818,
-0.0692957267165184,
-0.08438505232334137,
-0.09263329207897186,
-0.0441075898706913,
0.2150823175907135,
0.07462603598833084,
0.06712165474891663,
-0.01789480447769165,
0.06462772190570831,
-0.028952201828360558,
-0.14082671701908112,
0.018302908167243004,
-0.0678030475974083,
0.02776501700282097,
0.09260357171297073,
0.023143311962485313,
-0.11174326390028,
0.1261058747768402,
-0.04315865412354469,
0.08418598026037216,
-0.02438303455710411,
0.030167914927005768,
0.08576603978872299,
0.04973084479570389,
0.00036313210148364305,
-0.044624652713537216,
-0.046186547726392746,
0.024028951302170753,
0.04244116693735123,
0.08622599393129349,
-0.1124146580696106,
-0.1578194499015808,
-0.058352403342723846,
-0.03314848989248276,
0.0368940532207489,
-0.02235700748860836,
0.031663235276937485,
-0.018202578648924828,
-0.03399018198251724,
0.05777107551693916,
-0.03778986632823944,
-0.0465594045817852,
-0.07816575467586517,
-0.02628031000494957,
0.19690850377082825,
-0.00004900448038824834,
-0.01669607125222683,
0.0386069193482399,
0.12860320508480072,
-0.03358098864555359,
-0.0125357611104846,
-0.05652666464447975,
-0.004869690630584955,
-0.008043534122407436,
-0.09518330544233322,
0.019361110404133797,
-0.14595496654510498,
-0.2456713616847992,
-0.008459539152681828,
0.06287551671266556,
-0.02480435185134411,
0.07609164714813232,
-0.018195897340774536,
0.002342051360756159,
0.009810468181967735,
-0.0021307896822690964,
-0.036132488399744034,
-0.08340536057949066,
0.08271317183971405,
-0.007588130421936512,
0.1080821231007576,
-0.09829504042863846,
0.014339451678097248,
-0.05461930111050606,
0.0691588744521141,
-0.08582065999507904,
0.0567854605615139,
-0.06152712181210518,
0.019211599603295326,
-0.03642437607049942,
0.001205221633426845,
-0.09526523947715759,
0.08926501870155334,
-0.025407427921891212,
0.18862305581569672,
-0.19650056958198547,
-0.056954316794872284,
0.062425725162029266,
-0.21973669528961182,
-0.06110841780900955,
0.09533529728651047,
-0.03175249695777893,
0.1627279371023178,
0.09818840026855469,
0.21747741103172302,
0.0629076287150383,
-0.21498124301433563,
0.0011199315777048469,
0.01877375692129135,
-0.07146135717630386,
-0.06892047822475433,
0.08361943811178207,
0.13243848085403442,
-0.002664267085492611,
0.09452591091394424,
-0.08489071577787399,
0.07967083901166916,
-0.06944887340068817,
-0.05381827801465988,
-0.04445013031363487,
-0.05969565361738205,
-0.013305429369211197,
0.021472951397299767,
0.01606534607708454,
0.02633039280772209,
-0.004790316801518202,
-0.0029283175244927406,
0.13332277536392212,
-0.07023845613002777,
-0.008744318969547749,
-0.043393686413764954,
0.22574728727340698,
-0.14687809348106384,
0.02864212542772293,
0.015381133183836937,
-0.06748015433549881,
-0.02338995784521103,
0.040010903030633926,
0.04474874958395958,
-0.011125264689326286,
0.037364087998867035,
0.04918428510427475,
-0.05864553153514862,
-0.010532669723033905,
0.0778423622250557,
-0.036765486001968384,
0.02772272191941738,
-0.1125706285238266,
0.0035359705798327923,
-0.018693365156650543,
0.14485479891300201,
-0.11478981375694275,
0.012773801572620869,
0.03144174814224243,
0.0581856369972229,
0.009660384617745876,
0.054650064557790756,
0.03496669605374336,
-0.03928816691040993,
-0.0567561611533165,
-0.020740998908877373,
0.029774054884910583,
0.0030565557535737753,
-0.06404371559619904,
0.09489382058382034,
-0.1181425079703331,
0.14059925079345703,
0.12429410964250565,
0.06807424873113632,
0.02444450370967388,
-0.16354012489318848,
0.024680685251951218,
-0.0022311212960630655,
-0.09674111753702164,
-0.019115077331662178,
-0.12787459790706635,
-0.01726965233683586,
0.05076300725340843,
-0.08350521326065063,
0.1290566474199295,
0.06197945028543472,
-0.08147081732749939,
-0.0695614218711853,
0.06754723191261292,
0.12704172730445862,
-0.007972241379320621,
0.08462817221879959,
0.11353437602519989,
-0.05368514358997345,
0.1985144168138504,
-0.027148529887199402,
-0.11720435321331024,
0.0000789531331975013,
0.042680948972702026,
0.017546383664011955,
0.1804213523864746,
0.12124215811491013,
-0.025696896016597748,
0.04038246348500252,
-0.04483681544661522,
0.027786632999777794,
-0.09635689854621887,
-0.08496259897947311,
0.02160707116127014,
-0.07978550344705582,
0.09010623395442963,
0.12167512625455856,
-0.07755479216575623,
0.09032132476568222,
-0.08013550937175751,
-0.0064517781138420105,
-0.013200122863054276,
-0.01699184812605381,
0.005160622298717499,
0.08047831058502197,
0.03657901659607887,
-0.18242274224758148,
-0.1736120730638504,
-0.02860260009765625,
-0.11608923971652985,
-0.0030633951537311077,
0.0688023567199707,
-0.0875048041343689,
-0.0365503691136837,
-0.057651277631521225,
0.05632426217198372,
0.047194719314575195,
-0.043728169053792953,
-0.1029629111289978,
-0.044926658272743225,
-0.09088074415922165,
-0.06996826082468033,
-0.031274065375328064,
-0.08053392171859741,
0.0015201839851215482,
0.08769232034683228,
-0.13621041178703308,
0.22409312427043915,
0.07961716502904892,
0.03132055327296257,
0.05644422024488449,
-0.0008942871354520321,
0.12933620810508728,
-0.10063949227333069,
0.051964692771434784,
0.24549280107021332,
0.05662902444601059,
0.050491735339164734,
0.10727572441101074,
0.005549706984311342,
-0.10512490570545197,
0.013873417861759663,
-0.0055912453681230545,
-0.1757071614265442,
-0.06146503612399101,
-0.11406136304140091,
-0.07500874251127243,
-0.006452662404626608,
0.014090013690292835,
0.01974198967218399,
0.1157679557800293,
0.16840873658657074,
-0.03700444474816322,
-0.005594286136329174,
0.053382959216833115,
0.07392973452806473,
0.0009577085147611797,
0.039373043924570084,
0.07389668375253677,
-0.06674586236476898,
-0.05972385033965111,
0.15641464293003082,
0.042689792811870575,
0.22305697202682495,
-0.04092329740524292,
0.07348719984292984,
0.08857499063014984,
0.11247909069061279,
0.12202655524015427,
0.049612730741500854,
0.009080305695533752,
-0.00422743521630764,
-0.06983534246683121,
-0.1076294407248497,
0.004493912681937218,
0.09627038240432739,
-0.1098598837852478,
-0.04634077474474907,
-0.016335494816303253,
0.06472676247358322,
0.07047393172979355,
0.024345312267541885,
-0.03956012800335884,
-0.273692786693573,
0.07037559151649475,
0.07467056065797806,
0.109268918633461,
-0.06710369139909744,
0.015739431604743004,
0.10602515190839767,
-0.0249650739133358,
0.03977777436375618,
-0.03587532415986061,
0.08306831121444702,
-0.08583375811576843,
-0.027664953842759132,
-0.11228496581315994,
0.13319779932498932,
-0.022901440039277077,
0.05545176565647125,
-0.13138943910598755,
0.11470029503107071,
-0.004318179562687874,
0.02222265675663948,
-0.06484252214431763,
-0.05147392675280571,
0.12402679026126862,
0.09968029707670212,
0.1790110021829605,
0.00028830047813244164,
-0.058971431106328964,
-0.04153253510594368,
-0.11942670494318008,
0.040327370166778564,
0.04649139568209648,
-0.04460402578115463,
0.02592090144753456,
-0.039503343403339386,
0.005235831718891859,
-0.014687670394778252,
0.1100921556353569,
-0.06312188506126404,
-0.147039532661438,
0.02457033097743988,
0.1367325335741043,
-0.0023367763496935368,
-0.0012081856839358807,
-0.06106513738632202,
-0.062203630805015564,
0.024089641869068146,
0.21489401161670685,
-0.09989351779222488,
-0.12243282794952393,
-0.06018884479999542,
0.04599246755242348,
-0.05009908974170685,
-0.017187219113111496,
-0.00913100503385067,
0.13192327320575714,
-0.06001029908657074,
-0.15031415224075317,
-0.036741308867931366,
-0.02237895131111145,
0.02417275309562683,
-0.01003703847527504,
0.053139228373765945,
-0.005643628071993589,
-0.06335940957069397,
0.03887227922677994,
-0.009551056660711765,
0.02329995110630989,
-0.09134206920862198,
0.023498257622122765,
0.14233657717704773,
-0.012473982758820057,
0.04112088680267334,
-0.05524342507123947,
-0.06709619611501694,
-0.07361878454685211,
-0.04484802857041359,
-0.03500210493803024,
0.19608210027217865,
-0.03274789825081825,
0.019626764580607414,
0.09104736894369125,
-0.05374183505773544,
-0.20517510175704956,
-0.050271131098270416,
-0.07713618129491806,
0.02372034266591072,
-0.01771167665719986,
-0.06064742058515549,
0.09430021792650223,
0.1282419115304947,
-0.07130452990531921,
0.17298687994480133,
-0.2954314053058624,
-0.1147032231092453,
0.017018646001815796,
0.17391739785671234,
0.42921769618988037,
-0.2517067790031433,
-0.031878791749477386,
-0.15039263665676117,
-0.07778316736221313,
0.04919009655714035,
-0.09447817504405975,
0.07175871729850769,
-0.0044190362095832825,
-0.0009347793529741466,
0.0038111608009785414,
-0.017313377931714058,
0.20890170335769653,
-0.038743678480386734,
0.10900545865297318,
-0.1043517217040062,
0.0016110445139929652,
0.061800938099622726,
-0.07535689324140549,
0.08196958899497986,
-0.18935748934745789,
0.016049321740865707,
-0.04177359119057655,
-0.07506456971168518,
0.009862367063760757,
0.06920910626649857,
0.017186719924211502,
-0.08079305291175842,
-0.08155767619609833,
0.033479154109954834,
0.021813834086060524,
0.015811746940016747,
-0.01147178653627634,
-0.08497221767902374,
-0.017044436186552048,
0.0002976751420646906,
-0.048581987619400024,
0.01275021955370903,
-0.021907024085521698,
-0.08613148331642151,
-0.04461493343114853,
0.11928859353065491,
-0.18148554861545563,
-0.001340194372460246,
0.08762647211551666,
0.011341016739606857,
0.10254894196987152,
0.010928215458989143,
-0.018354369327425957,
0.07097611576318741,
0.1393764317035675,
-0.09567724913358688,
-0.15229883790016174,
-0.05254393815994263,
-0.025410939007997513,
0.13419540226459503,
0.0047082905657589436,
0.08158334344625473,
-0.06516049057245255,
0.04625995084643364,
0.011993138119578362,
0.011521605774760246,
-0.00046940866741351783,
0.03242654725909233,
0.014392386190593243,
-0.03256744146347046,
-0.09398443251848221,
0.057210955768823624,
-0.023865951225161552,
0.027894413098692894,
-0.03292619436979294,
-0.025677725672721863,
-0.0828436017036438,
-0.04353097453713417,
-0.02091814950108528,
0.13249360024929047,
-0.11765868216753006,
-0.1023653894662857,
-0.0681360736489296,
-0.08498936891555786,
-0.06691772490739822,
0.056259654462337494,
0.10663162916898727,
-0.06228533759713173,
0.031244682148098946,
0.015493044629693031,
-0.09200847148895264,
0.03491142392158508,
0.09628771245479584,
0.07130841165781021,
-0.18507134914398193,
-0.10105475038290024,
0.016168100759387016,
0.028219444677233696,
-0.11826182901859283,
-0.0556548573076725,
-0.034140292555093765,
0.018366031348705292,
-0.12238109856843948,
0.1233287826180458,
-0.10832991451025009,
-0.03331928700208664,
-0.02266509458422661,
-0.04488201066851616,
-0.029839681461453438,
-0.01152376551181078,
-0.055257923901081085,
0.031398698687553406,
-0.0019519941415637732,
0.03500963747501373,
-0.043549492955207825,
-0.05634504184126854,
0.03465553745627403,
-0.08179661631584167,
-0.0064903246238827705,
0.060398515313863754,
-0.05705200135707855,
0.041107576340436935,
-0.19301262497901917,
0.001811465248465538,
0.095707967877388,
0.0174070093780756,
-0.03985089436173439,
0.036726366728544235,
0.027354758232831955,
0.048589617013931274,
0.014326722361147404,
-0.03248577192425728,
-0.09162230789661407,
-0.0626482218503952,
0.08616316318511963,
-0.09168058633804321,
-0.02440652623772621,
-0.013792556710541248,
0.04489182308316231,
0.1788780242204666,
0.11971108615398407,
0.1145581305027008,
-0.03344699367880821,
0.004002964589744806,
-0.06732785701751709,
0.032785505056381226,
0.028891220688819885,
-0.15606625378131866,
-0.020941123366355896,
-0.14260408282279968,
-0.01529312040656805,
-0.015227403491735458,
0.18837276101112366,
0.07214163988828659,
-0.09670812636613846,
-0.06738435477018356,
0.06710797548294067,
0.1279141753911972,
-0.00794837437570095,
0.2760253846645355,
0.09230679273605347,
0.10153067857027054,
-0.05865032970905304,
0.04070843756198883,
0.07963915169239044,
0.08254553377628326,
-0.012973661534488201,
0.11526612192392349,
-0.011133546940982342,
0.07582971453666687,
0.0021723320242017508,
0.05683007463812828,
0.008735858835279942,
-0.0006036726990714669,
-0.12227284163236618,
0.029154932126402855,
0.03623732924461365,
0.024675404652953148,
0.2383805513381958,
-0.10986034572124481,
0.014341075904667377,
0.08742115646600723,
-0.01422584243118763,
-0.11203509569168091,
-0.275219202041626,
-0.10480251908302307,
-0.20021148025989532,
0.0608050599694252,
-0.048004671931266785,
0.0013087864499539137,
0.1867610365152359,
0.0186245609074831,
0.020326513797044754,
0.10901061445474625,
-0.025581486523151398,
-0.03770475834608078,
0.11067017167806625,
-0.0711393728852272,
-0.1044895350933075,
-0.0005790433497168124,
-0.0831359326839447,
0.04128648713231087,
-0.046297743916511536,
-0.008131174370646477,
0.027315109968185425,
0.062287576496601105,
0.0530211366713047,
-0.09116312861442566,
-0.053719907999038696,
-0.04605195298790932,
0.007569741457700729,
0.00999967847019434,
0.07504517585039139,
0.04417554289102554,
-0.05098078027367592,
0.009372496046125889,
0.16481420397758484,
0.015336026437580585,
-0.061447396874427795,
-0.07726530730724335,
0.00957639142870903,
-0.09712732583284378,
0.026896176859736443,
-0.04463444650173187,
-0.0388563796877861,
0.02057875506579876,
0.23914486169815063,
0.14255528151988983,
-0.07132765650749207,
-0.010145922191441059,
-0.09958124905824661,
0.013116397894918919,
-0.03812795877456665,
0.12976385653018951,
-0.018836000934243202,
0.21703095734119415,
-0.0481681302189827,
0.021577343344688416,
-0.11106083542108536,
-0.056776631623506546,
-0.03115173615515232,
0.029183221980929375,
0.0009365202276967466,
-0.08368915319442749,
-0.07627318054437637,
0.10105091333389282,
-0.14644265174865723,
-0.042103663086891174,
0.08625141531229019,
-0.013475104235112667,
-0.030679767951369286,
-0.04511629417538643,
0.021981552243232727,
0.05345672369003296,
0.009127459488809109,
-0.16025696694850922,
0.04936178773641586,
-0.11535122990608215,
0.03607608750462532,
-0.11691199243068695,
-0.033429767936468124,
0.01793915033340454,
-0.005176543723791838,
0.10894066840410233,
-0.0031993852462619543,
0.009716223925352097,
-0.011973016895353794,
-0.020981259644031525,
-0.014636530540883541,
0.11723802238702774,
-0.01890162192285061,
-0.09240298718214035,
-0.007323177997022867,
0.06575805693864822,
-0.07731657475233078,
-0.04774194210767746,
0.05744447186589241,
-0.07330173254013062,
0.010316383093595505,
0.09402298182249069,
-0.050295639783144,
-0.0570380836725235,
0.05341238155961037,
-0.14120694994926453,
0.10278994590044022,
0.04797432944178581,
0.032700315117836,
-0.030293826013803482,
-0.022231344133615494,
0.11181477457284927,
0.0399727039039135,
-0.03998269885778427,
0.06644219905138016,
-0.0372217521071434,
-0.1128968819975853,
0.007208561059087515,
0.003590865759178996,
-0.17337669432163239,
-0.022725259885191917,
-0.1541084349155426,
-0.024966374039649963,
-0.028159936890006065,
0.09325241297483444,
0.24935752153396606,
-0.014377796091139317,
-0.02155289798974991,
-0.21843087673187256,
0.04845487326383591,
0.07948382198810577,
-0.04551620036363602,
-0.05147647485136986
] |
null | null | diffusers |
# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_turbo
These are textual inversion adaption weights for stabilityai/sdxl-turbo. You can find some example images in the following.
| {"license": "creativeml-openrail-m", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "textual_inversion"], "base_model": "stabilityai/sdxl-turbo", "inference": true} | text-to-image | Stelath/textual_inversion_comic_strip_turbo | [
"diffusers",
"tensorboard",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"textual_inversion",
"base_model:stabilityai/sdxl-turbo",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | 2024-02-11T05:27:48+00:00 | [] | [] | TAGS
#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/sdxl-turbo #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us
|
# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_turbo
These are textual inversion adaption weights for stabilityai/sdxl-turbo. You can find some example images in the following.
!img_0
!img_1
!img_2
!img_3
| [
"# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_turbo\nThese are textual inversion adaption weights for stabilityai/sdxl-turbo. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
"TAGS\n#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/sdxl-turbo #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us \n",
"# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_turbo\nThese are textual inversion adaption weights for stabilityai/sdxl-turbo. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
98,
81
] | [
"passage: TAGS\n#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #textual_inversion #base_model-stabilityai/sdxl-turbo #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us \n# Textual inversion text2image fine-tuning - Stelath/textual_inversion_comic_strip_turbo\nThese are textual inversion adaption weights for stabilityai/sdxl-turbo. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3"
] | [
-0.14245744049549103,
-0.05124344304203987,
-0.003561162855476141,
0.02821141667664051,
0.10173054784536362,
-0.008500317111611366,
0.2183244228363037,
0.060730721801519394,
0.07493305951356888,
0.08956734091043472,
0.062048520892858505,
0.07479557394981384,
0.008696458302438259,
0.09377153217792511,
-0.05542415753006935,
-0.21706204116344452,
0.012977397069334984,
0.004522585775703192,
-0.08818671107292175,
0.06622885912656784,
0.0786101445555687,
-0.0671897828578949,
0.08328863233327866,
0.021833907812833786,
-0.09568405151367188,
-0.01053997129201889,
0.05211756005883217,
-0.07582153379917145,
0.10848686099052429,
0.047253161668777466,
0.0631142184138298,
0.14336518943309784,
0.03612580522894859,
-0.1199505403637886,
0.04114723205566406,
0.04893164709210396,
-0.008262273855507374,
0.07136848568916321,
0.02044186182320118,
-0.042385201901197433,
0.07198891788721085,
-0.045663412660360336,
-0.023160919547080994,
0.004308741074055433,
-0.05473412945866585,
-0.030333539471030235,
-0.06320292502641678,
0.005171065218746662,
0.051797568798065186,
0.0035103382542729378,
0.029423963278532028,
0.052296195179224014,
-0.041286688297986984,
0.049446918070316315,
0.2503736615180969,
-0.22670172154903412,
-0.013858292251825333,
0.09466325491666794,
0.06426868587732315,
0.07032260298728943,
-0.0723700150847435,
0.08908766508102417,
0.014160148799419403,
-0.03658835217356682,
0.07911267131567001,
-0.05583454668521881,
0.09555646777153015,
-0.02227638103067875,
-0.10001739114522934,
0.09490320831537247,
0.11416343599557877,
-0.011589981615543365,
-0.07126220315694809,
-0.21030420064926147,
-0.05586058646440506,
0.15523262321949005,
-0.0686480849981308,
-0.029811592772603035,
-0.02254391834139824,
0.00872889719903469,
0.040060341358184814,
-0.040053945034742355,
-0.1056758463382721,
-0.06724616885185242,
-0.045710090547800064,
0.13864614069461823,
-0.012083646841347218,
-0.0032248597126454115,
0.04751839116215706,
0.1122143566608429,
-0.12429890781641006,
-0.14367975294589996,
0.039579518139362335,
-0.06438577175140381,
0.01777467504143715,
0.0065832240507006645,
-0.025027230381965637,
-0.29286956787109375,
0.015244027599692345,
0.061114054173231125,
-0.01698322221636772,
0.011888863518834114,
-0.023508716374635696,
0.0992131382226944,
-0.04435305669903755,
0.03688342124223709,
-0.10120090842247009,
-0.0076295072212815285,
0.042664602398872375,
0.08523062616586685,
0.11880388855934143,
-0.037113334983587265,
-0.06617850065231323,
-0.05055644363164902,
-0.03331633284687996,
0.016941016539931297,
-0.05440369248390198,
0.0633227527141571,
-0.08827736973762512,
-0.021391449496150017,
0.195505291223526,
-0.04644627869129181,
0.02091035433113575,
-0.019250165671110153,
0.043988484889268875,
0.17215143144130707,
0.14914032816886902,
0.03410133719444275,
0.010546304285526276,
0.12822943925857544,
-0.051503557711839676,
0.05061168968677521,
0.014902384951710701,
-0.09784583002328873,
0.004481979180127382,
-0.1635950803756714,
-0.026202308014035225,
-0.11064966022968292,
-0.15122418105602264,
0.06097183749079704,
0.039902519434690475,
-0.021717403084039688,
0.09685827046632767,
0.05025753751397133,
-0.015503273345530033,
0.02207821235060692,
0.019106073305010796,
-0.12426966428756714,
-0.030234061181545258,
0.04751205816864967,
0.015752200037240982,
0.09536869078874588,
-0.019385114312171936,
-0.02221490815281868,
-0.07854211330413818,
0.025134172290563583,
-0.31999626755714417,
0.05102875083684921,
-0.08190842717885971,
0.01252020988613367,
-0.04284637048840523,
-0.01558046042919159,
-0.11414441466331482,
0.07221883535385132,
0.04842391237616539,
0.21346808969974518,
-0.25323590636253357,
-0.07062994688749313,
0.17050214111804962,
-0.2028505653142929,
-0.08055294305086136,
0.10421199351549149,
0.024173853918910027,
0.028823131695389748,
0.0567939318716526,
0.0755373165011406,
0.03154878690838814,
-0.24640288949012756,
0.03496686369180679,
-0.00998093280941248,
-0.07324299961328506,
-0.01651649735867977,
0.02223411202430725,
-0.007569346111267805,
0.07546638697385788,
0.04200666397809982,
-0.0915457233786583,
0.09451112896203995,
-0.028894366696476936,
0.02110428176820278,
-0.0545060820877552,
-0.018613843247294426,
0.10780402272939682,
0.0600709542632103,
0.0292720478028059,
-0.018669571727514267,
-0.08008982241153717,
0.10019111633300781,
-0.00007698758417973295,
-0.0706147849559784,
0.04038843885064125,
-0.035829853266477585,
0.13661730289459229,
-0.13307330012321472,
-0.012712211348116398,
-0.12647104263305664,
-0.024533500894904137,
0.0023715870920568705,
0.18895021080970764,
-0.005123986396938562,
0.038352902978658676,
0.14428432285785675,
0.06467221677303314,
-0.047851063311100006,
-0.012371894903481007,
0.131844624876976,
0.02501583844423294,
-0.06643655151128769,
-0.16442176699638367,
0.05640175938606262,
-0.09404778480529785,
0.07183235138654709,
-0.22242778539657593,
0.05284975841641426,
0.05344303697347641,
0.16738778352737427,
0.11426183581352234,
-0.03836700692772865,
0.046180643141269684,
-0.01760278455913067,
-0.07459621876478195,
-0.04372318461537361,
0.02470509521663189,
0.005980442278087139,
-0.046114109456539154,
0.23178012669086456,
-0.18977439403533936,
0.2089022845029831,
0.128622904419899,
0.018302643671631813,
-0.05888949707150459,
-0.1733081042766571,
0.01825593039393425,
0.011127232573926449,
-0.04387948289513588,
-0.012117398902773857,
-0.031258028000593185,
0.041472677141427994,
0.12522315979003906,
-0.04718593880534172,
0.020269455388188362,
0.05584275349974632,
-0.05098405480384827,
-0.04386785253882408,
0.03357066214084625,
0.0568697452545166,
-0.006486659403890371,
0.014172384515404701,
0.13757900893688202,
-0.03363363817334175,
0.09951292723417282,
-0.04966391995549202,
-0.08515804260969162,
-0.005756439175456762,
0.06433572620153427,
0.08068743348121643,
0.14349831640720367,
0.013225398026406765,
-0.01349915936589241,
0.01573876664042473,
-0.03288155049085617,
0.0009534702403470874,
-0.11643025279045105,
-0.01366094034165144,
0.06456581503152847,
-0.038526713848114014,
0.10070431977510452,
0.08191028237342834,
-0.043154068291187286,
0.10161693394184113,
-0.12527422606945038,
-0.03630031272768974,
-0.011086493730545044,
0.011525986716151237,
-0.10035955905914307,
0.1292913854122162,
-0.073709636926651,
-0.149361252784729,
-0.11871593445539474,
-0.01869051158428192,
0.025292618200182915,
0.03581119328737259,
0.02188003994524479,
-0.021049384027719498,
-0.10964903980493546,
-0.13436655700206757,
0.027840007096529007,
0.1347656100988388,
0.033607326447963715,
-0.00893957819789648,
-0.05798538401722908,
0.03065485693514347,
-0.07854536175727844,
0.00040434690890833735,
-0.01566268876194954,
0.08927545696496964,
0.0638980120420456,
0.05569988116621971,
0.11035540699958801,
0.09678614139556885,
0.011055989190936089,
-0.01142188347876072,
0.025013340637087822,
0.032752737402915955,
-0.029658397659659386,
0.14766187965869904,
0.1895570158958435,
-0.021605025976896286,
0.07227952033281326,
0.09254120290279388,
0.038520731031894684,
-0.008019396103918552,
0.022545598447322845,
-0.0013361916644498706,
-0.1070147231221199,
-0.06690668314695358,
-0.07550245523452759,
-0.07100475579500198,
-0.007965085096657276,
0.0012209725100547075,
0.021655971184372902,
0.08231484889984131,
0.11324454843997955,
0.015811961144208908,
-0.008292418904602528,
0.08124808222055435,
0.06305693835020065,
0.052864428609609604,
-0.015061469748616219,
0.08922699838876724,
-0.04725106060504913,
-0.07335297763347626,
0.0861893892288208,
-0.09313099086284637,
0.07765273749828339,
-0.10305935889482498,
0.08756180852651596,
0.03717676177620888,
0.030018512159585953,
0.08550102263689041,
0.1347166746854782,
-0.07386848330497742,
-0.08633493632078171,
-0.013393307104706764,
-0.10954593867063522,
0.03183705732226372,
0.05569757521152496,
-0.0197493564337492,
-0.03584334999322891,
-0.039264075458049774,
0.09068721532821655,
0.046962395310401917,
-0.021516015753149986,
0.08034506440162659,
-0.26426517963409424,
-0.016257718205451965,
0.007733054459095001,
0.05769210681319237,
-0.013129224069416523,
0.00042059202678501606,
0.1800398975610733,
0.00231671123765409,
0.08308243006467819,
-0.13426974415779114,
0.03270510211586952,
0.022382937371730804,
-0.012493266724050045,
-0.022410079836845398,
0.16334842145442963,
-0.04428732767701149,
-0.04095197841525078,
-0.15473291277885437,
0.05771104246377945,
0.013838069513440132,
0.007884498685598373,
-0.0324123352766037,
0.01954636536538601,
0.05933850258588791,
0.10991702973842621,
0.09754126518964767,
-0.022379737347364426,
0.01875176467001438,
-0.040008220821619034,
-0.11176106333732605,
-0.04204221069812775,
0.05853826925158501,
-0.020736686885356903,
0.03109690360724926,
0.015449419617652893,
-0.06156072020530701,
0.07223731279373169,
-0.0010074892779812217,
-0.2228885143995285,
-0.17272384464740753,
0.03874441608786583,
0.029915200546383858,
-0.11443770676851273,
-0.09519075602293015,
-0.09325627982616425,
-0.15645328164100647,
0.2029343545436859,
0.005754145327955484,
-0.056070175021886826,
-0.13032524287700653,
-0.04035414010286331,
0.0717971920967102,
-0.04716349393129349,
0.04533574357628822,
-0.021676914766430855,
0.0898350179195404,
-0.06824059784412384,
-0.12913736701011658,
0.12350074201822281,
-0.08869798481464386,
-0.08611312508583069,
-0.10879424959421158,
0.125345841050148,
-0.011554110795259476,
-0.04135533794760704,
0.004146195482462645,
0.006517359521239996,
0.07855915278196335,
-0.06824924051761627,
0.026756566017866135,
0.09072710573673248,
0.010938170365989208,
0.030732467770576477,
-0.04272746667265892,
-0.02998550422489643,
0.028081482276320457,
0.007936571724712849,
0.106751948595047,
0.09978511184453964,
-0.08475999534130096,
0.11818326264619827,
0.11481847614049911,
-0.009352761320769787,
-0.22061988711357117,
-0.01877761073410511,
-0.05759165808558464,
0.025553617626428604,
0.09888411313295364,
-0.03790224716067314,
0.15726596117019653,
0.04444411024451256,
0.0011562524596229196,
0.1680712103843689,
-0.3095346987247467,
-0.1310221403837204,
0.05365661531686783,
0.1444583684206009,
0.07903905212879181,
-0.15447497367858887,
-0.09294496476650238,
0.01927584782242775,
-0.14017242193222046,
0.06405863910913467,
-0.09034259617328644,
0.0028920695185661316,
-0.026337238028645515,
-0.09362702071666718,
0.014089258387684822,
-0.08911602199077606,
0.10352536290884018,
-0.0718650370836258,
0.03444012254476547,
-0.11265512555837631,
0.045257922261953354,
0.07081097364425659,
-0.045202840119600296,
0.057824477553367615,
-0.22784022986888885,
0.02696375735104084,
-0.07119668275117874,
-0.03296280279755592,
0.024149827659130096,
0.05698951333761215,
-0.0043014888651669025,
-0.03390029817819595,
-0.02625712752342224,
-0.007741021923720837,
-0.03332742676138878,
-0.028123052790760994,
0.06987950950860977,
-0.009176393039524555,
0.07218488305807114,
0.1637265533208847,
0.08257097005844116,
-0.07655007392168045,
-0.08161570131778717,
-0.05916166678071022,
-0.011027165688574314,
0.04022221267223358,
-0.06016784906387329,
0.015609978698194027,
0.09286695718765259,
0.07500410079956055,
0.08809718489646912,
0.03767620772123337,
-0.038202833384275436,
0.04416046291589737,
0.12781934440135956,
-0.12154631316661835,
-0.02559758350253105,
-0.025404179468750954,
0.03650180622935295,
0.04993188753724098,
0.08088180422782898,
0.1433386206626892,
-0.03054465912282467,
0.039771027863025665,
0.012828747741878033,
0.04224374517798424,
0.003878043033182621,
0.12095016986131668,
0.047717396169900894,
0.006388241425156593,
-0.054935961961746216,
0.06732837110757828,
-0.06378944963216782,
-0.11877898871898651,
-0.04424582049250603,
0.06867572665214539,
-0.12307391315698624,
-0.0393323078751564,
0.07038995623588562,
0.1148865818977356,
-0.07867211103439331,
0.0034788160119205713,
-0.09673432260751724,
-0.1496102511882782,
-0.02125626616179943,
0.1106870025396347,
0.04137333109974861,
-0.015653792768716812,
-0.05018879845738411,
-0.010527009144425392,
-0.058097004890441895,
0.091006338596344,
0.13840621709823608,
0.10651224851608276,
-0.21549689769744873,
-0.05885176733136177,
-0.037248753011226654,
-0.07324478775262833,
-0.06821152567863464,
0.01837369054555893,
-0.03949285298585892,
-0.06016400828957558,
-0.12252681702375412,
0.06962399929761887,
-0.15518587827682495,
-0.06929132342338562,
-0.03225189447402954,
-0.05512678250670433,
0.03241955488920212,
-0.012232235632836819,
-0.006135294213891029,
0.0019581709057092667,
-0.011186393909156322,
0.0003338610986247659,
-0.09226890653371811,
-0.03726308047771454,
-0.019157474860548973,
-0.10461296886205673,
0.08408641815185547,
0.050364457070827484,
-0.06484369188547134,
0.013021769933402538,
-0.25940701365470886,
-0.01381830032914877,
0.13956761360168457,
-0.01651940308511257,
-0.010072847828269005,
-0.0024445459712296724,
0.053910866379737854,
0.015519056469202042,
0.0033543328754603863,
-0.03841495141386986,
0.021535539999604225,
-0.06045570224523544,
0.07396908104419708,
-0.09686065465211868,
0.003306408179923892,
-0.07739067077636719,
0.062170468270778656,
0.18369299173355103,
0.06256886571645737,
0.13066451251506805,
-0.13017220795154572,
0.04666774347424507,
-0.15459565818309784,
0.019771995022892952,
0.03480646759271622,
-0.06182631105184555,
0.02431122213602066,
0.026391634717583656,
-0.014100082218647003,
-0.025191474705934525,
0.12335733324289322,
-0.05385037139058113,
-0.13562901318073273,
-0.0006270578014664352,
-0.046520818024873734,
0.1036301925778389,
0.04792496934533119,
0.20230621099472046,
0.019617406651377678,
0.030294764786958694,
-0.13777035474777222,
0.057340048253536224,
0.1237461194396019,
-0.12936393916606903,
0.1373504400253296,
0.11999207735061646,
-0.10935737192630768,
0.12404453009366989,
0.018043003976345062,
-0.0360584482550621,
-0.04795851558446884,
0.0695568174123764,
-0.14267705380916595,
0.08809015899896622,
-0.010154394432902336,
0.08854241669178009,
0.18414223194122314,
-0.03789651393890381,
-0.026585299521684647,
0.051745977252721786,
-0.05862169340252876,
-0.0565977580845356,
-0.19247882068157196,
-0.03118300810456276,
-0.154905304312706,
0.002951014554128051,
-0.04505796357989311,
-0.008493862114846706,
0.0021524843759834766,
0.04154222086071968,
0.05821404233574867,
0.16418874263763428,
0.06072711572051048,
-0.045624930411577225,
0.08672134578227997,
0.004174989648163319,
-0.0847339928150177,
0.12872274219989777,
-0.007464221213012934,
0.008708286099135876,
0.026640336960554123,
-0.0119455112144351,
0.054644033312797546,
0.053451329469680786,
0.02595975436270237,
0.008215338923037052,
-0.07481133192777634,
0.0029361566994339228,
0.00895910244435072,
0.013780754990875721,
0.10855948179960251,
0.05712975561618805,
-0.006236682645976543,
-0.031231453642249107,
0.12762285768985748,
-0.025446053594350815,
-0.04425819218158722,
-0.09788943827152252,
0.0600038543343544,
-0.05264808610081673,
0.049698278307914734,
-0.05451216548681259,
-0.1202768012881279,
0.04943189397454262,
0.16982106864452362,
0.19130025804042816,
-0.0878477692604065,
0.036661550402641296,
-0.04913392663002014,
-0.018612565472722054,
-0.0026886097621172667,
0.036947108805179596,
0.01729687489569187,
0.2611877918243408,
-0.005700382869690657,
-0.02679515816271305,
-0.05806422978639603,
-0.06424764543771744,
-0.08937691897153854,
0.00005418974251369946,
0.0009000952122732997,
-0.01254352554678917,
-0.05845657363533974,
0.08243663609027863,
0.010396072641015053,
-0.1427435427904129,
0.011089321225881577,
-0.1023658886551857,
-0.01035290490835905,
-0.06176687031984329,
0.06977177411317825,
-0.015256326645612717,
-0.018467390909790993,
-0.042171284556388855,
-0.025925079360604286,
0.00796501338481903,
0.0179123617708683,
-0.07291170209646225,
0.11073675006628036,
-0.07406698912382126,
-0.08505081385374069,
0.06228916347026825,
-0.029158156365156174,
0.018630268052220345,
0.05948888882994652,
0.05071447044610977,
-0.05915229022502899,
0.019207561388611794,
-0.019541863352060318,
-0.0908062607049942,
-0.04042109102010727,
0.10616222023963928,
-0.003329879604279995,
-0.010775001719594002,
0.04047250375151634,
-0.15097540616989136,
0.06292669475078583,
-0.009151480160653591,
-0.1487981528043747,
-0.09479585289955139,
0.005479235667735338,
-0.0472220703959465,
0.10243713110685349,
0.012251390144228935,
0.01784883253276348,
0.02619553729891777,
0.0029261624440550804,
0.04662502184510231,
0.03541348874568939,
0.025387125089764595,
0.05158486217260361,
-0.11136765033006668,
0.020147547125816345,
0.015998102724552155,
0.03223465755581856,
-0.21340860426425934,
-0.08060608804225922,
-0.10269590467214584,
-0.01883135922253132,
-0.04235408455133438,
0.06527531147003174,
0.22862009704113007,
0.05944247171282768,
-0.005100826732814312,
-0.11486081779003143,
0.0355098582804203,
0.11229193955659866,
-0.09737351536750793,
-0.015343875624239445
] |
null | null | mlx |
# mlx-community/SOLAR-10.7B-Instruct-v1.0-laser-4bit-mlx
This model was converted to MLX format from [`macadeliccc/SOLAR-10.7B-Instruct-v1.0-laser`]().
Refer to the [original model card](https://huggingface.co/macadeliccc/SOLAR-10.7B-Instruct-v1.0-laser) for more details on the model.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/SOLAR-10.7B-Instruct-v1.0-laser-4bit-mlx")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
| {"license": "cc-by-nc-2.0", "tags": ["mlx"]} | null | mlx-community/SOLAR-10.7B-Instruct-v1.0-laser-4bit-mlx | [
"mlx",
"llama",
"license:cc-by-nc-2.0",
"region:us"
] | 2024-02-11T05:31:54+00:00 | [] | [] | TAGS
#mlx #llama #license-cc-by-nc-2.0 #region-us
|
# mlx-community/SOLAR-10.7B-Instruct-v1.0-laser-4bit-mlx
This model was converted to MLX format from ['macadeliccc/SOLAR-10.7B-Instruct-v1.0-laser']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# mlx-community/SOLAR-10.7B-Instruct-v1.0-laser-4bit-mlx\nThis model was converted to MLX format from ['macadeliccc/SOLAR-10.7B-Instruct-v1.0-laser']().\nRefer to the original model card for more details on the model.",
"## Use with mlx"
] | [
"TAGS\n#mlx #llama #license-cc-by-nc-2.0 #region-us \n",
"# mlx-community/SOLAR-10.7B-Instruct-v1.0-laser-4bit-mlx\nThis model was converted to MLX format from ['macadeliccc/SOLAR-10.7B-Instruct-v1.0-laser']().\nRefer to the original model card for more details on the model.",
"## Use with mlx"
] | [
23,
77,
5
] | [
"passage: TAGS\n#mlx #llama #license-cc-by-nc-2.0 #region-us \n# mlx-community/SOLAR-10.7B-Instruct-v1.0-laser-4bit-mlx\nThis model was converted to MLX format from ['macadeliccc/SOLAR-10.7B-Instruct-v1.0-laser']().\nRefer to the original model card for more details on the model.## Use with mlx"
] | [
-0.02883162535727024,
-0.08302801847457886,
-0.002618461847305298,
0.018568022176623344,
0.08743248879909515,
0.09836868196725845,
0.18862509727478027,
-0.0013444325886666775,
0.03721196576952934,
-0.03304546698927879,
0.10364580899477005,
0.30030450224876404,
0.006940745282918215,
0.01611114665865898,
0.034739941358566284,
-0.1539289504289627,
-0.014860598370432854,
0.026191743090748787,
0.03474649414420128,
0.033943962305784225,
0.09027744829654694,
-0.07220198959112167,
0.1553145796060562,
-0.023494942113757133,
-0.14169228076934814,
0.05946340411901474,
0.0479067899286747,
0.0019588256254792213,
0.04532797262072563,
0.0533674992620945,
-0.01993287168443203,
0.03452717885375023,
0.0934833511710167,
-0.1298721432685852,
-0.002919470891356468,
-0.06370962411165237,
-0.05917222425341606,
0.047694362699985504,
0.026842329651117325,
0.06103590503334999,
0.24854618310928345,
-0.06318646669387817,
-0.01533577125519514,
0.02326960116624832,
-0.025371210649609566,
-0.09783246368169785,
-0.10474786162376404,
-0.014014298096299171,
0.014698052778840065,
-0.047782931476831436,
0.094258613884449,
0.1427963376045227,
0.06472848355770111,
0.09134852141141891,
0.15649473667144775,
-0.21048739552497864,
-0.003643457544967532,
0.3388494551181793,
0.10461436957120895,
0.045400846749544144,
0.039708659052848816,
0.25084254145622253,
0.056757453829050064,
-0.004455468151718378,
0.11248011887073517,
-0.07383961975574493,
0.16107799112796783,
0.09370855987071991,
-0.0895824208855629,
-0.03666752576828003,
0.28830528259277344,
-0.02445761300623417,
-0.03592458367347717,
-0.06459176540374756,
0.020865334197878838,
0.04596537724137306,
-0.0775146484375,
0.05745207145810127,
0.05238010734319687,
0.0018129346426576376,
0.018279192969202995,
-0.1262938231229782,
-0.02493399754166603,
-0.14931336045265198,
-0.10643058270215988,
0.3064642548561096,
-0.007707767188549042,
0.11219745874404907,
-0.06147240847349167,
0.0017338985344395041,
0.004716308321803808,
-0.016097912564873695,
-0.02366928569972515,
-0.018570903688669205,
0.146365687251091,
0.07252274453639984,
-0.06962309032678604,
0.03332769125699997,
0.035502027720212936,
-0.03018428198993206,
0.13299955427646637,
-0.024721479043364525,
0.12184104323387146,
0.08876544237136841,
-0.02133178524672985,
0.009559533558785915,
0.004435752518475056,
0.0881509929895401,
0.006969158072024584,
-0.09450966864824295,
0.08912225812673569,
-0.022407107055187225,
-0.14891482889652252,
-0.015949338674545288,
-0.15933425724506378,
0.14740562438964844,
0.011167598888278008,
0.056157030165195465,
0.022795451804995537,
-0.015398289076983929,
0.05133453384041786,
-0.06356129795312881,
0.04064919427037239,
-0.030575893819332123,
0.021306237205863,
0.08735416829586029,
0.019208509474992752,
-0.0814947858452797,
0.0647459477186203,
-0.031964097172021866,
-0.07053267955780029,
0.04601650685071945,
-0.15416166186332703,
-0.06926218420267105,
0.0221435334533453,
0.06489481776952744,
0.05851718783378601,
-0.16997037827968597,
-0.14285646378993988,
0.06398367136716843,
0.037482574582099915,
-0.048901405185461044,
0.04828969016671181,
0.07017973810434341,
-0.025988100096583366,
0.037991348654031754,
0.018855636939406395,
0.17449666559696198,
-0.009684826247394085,
0.03215520456433296,
0.02250918187201023,
0.08982116729021072,
-0.177150696516037,
0.0330672487616539,
0.07252566516399384,
0.07619678974151611,
0.059428539127111435,
-0.03889619559049606,
-0.05831073597073555,
-0.0020990241318941116,
0.0024626655504107475,
-0.07156550884246826,
0.024646714329719543,
0.0723867192864418,
0.006495040841400623,
0.05252921208739281,
-0.24218404293060303,
0.02145114727318287,
-0.0025730293709784746,
-0.1141933798789978,
-0.10071803629398346,
-0.07305971533060074,
0.060560815036296844,
-0.012215576134622097,
-0.027500197291374207,
0.02290700189769268,
0.009400122798979282,
-0.23604118824005127,
0.007072296924889088,
0.10519976913928986,
-0.06521053612232208,
-0.2563062608242035,
0.15266121923923492,
0.05120748281478882,
-0.24917243421077728,
0.044404082000255585,
-0.12942636013031006,
-0.0381062813103199,
-0.08005461096763611,
-0.058235328644514084,
-0.0928884819149971,
-0.018158307299017906,
-0.031593091785907745,
-0.06863341480493546,
-0.050745174288749695,
-0.03121965005993843,
0.08720166981220245,
0.2116650640964508,
0.14619283378124237,
-0.03724236786365509,
-0.03014572709798813,
-0.13150551915168762,
0.07640144228935242,
-0.1380191445350647,
0.015134681016206741,
-0.014979776926338673,
0.015529305674135685,
-0.01090453751385212,
-0.09220566600561142,
0.010731391608715057,
0.12293501198291779,
-0.016683310270309448,
0.008382808417081833,
-0.038769010454416275,
0.08998903632164001,
-0.012514762580394745,
0.026452351361513138,
-0.01467583142220974,
-0.11058758944272995,
-0.0762060284614563,
0.003765275701880455,
-0.03843168169260025,
-0.09161435067653656,
-0.01886276714503765,
0.039277706295251846,
-0.036145854741334915,
-0.04685145244002342,
0.011081436648964882,
0.06621810048818588,
0.050367169082164764,
0.08500400185585022,
-0.01523478701710701,
0.0961667075753212,
0.010380453430116177,
-0.0557263009250164,
0.17876215279102325,
-0.1473418027162552,
0.09342774748802185,
0.18856260180473328,
-0.08076006174087524,
0.07021425664424896,
0.005913423374295235,
0.010672114789485931,
0.053800735622644424,
-0.01010359637439251,
-0.049640435725450516,
-0.059020522981882095,
-0.09415946155786514,
0.047046955674886703,
-0.054387643933296204,
-0.045825764536857605,
-0.001368243363685906,
0.008441995829343796,
-0.14722251892089844,
0.04809986427426338,
0.3404220938682556,
-0.0507759228348732,
-0.012431928887963295,
0.18421190977096558,
0.028532257303595543,
0.08078566193580627,
-0.017663998529314995,
-0.0076709166169166565,
-0.15979598462581635,
-0.12046320736408234,
0.018259447067975998,
0.1879546046257019,
0.048914387822151184,
-0.0012813692446798086,
0.06864339113235474,
-0.0788981169462204,
0.101302869617939,
-0.12041601538658142,
-0.06440884619951248,
0.009348931722342968,
-0.06026606261730194,
-0.05765112489461899,
0.13613542914390564,
-0.06430643796920776,
0.04625802859663963,
-0.07648112624883652,
0.043396469205617905,
0.029340621083974838,
-0.011320764198899269,
-0.10161910206079483,
0.09311763942241669,
-0.14269274473190308,
-0.13273705542087555,
-0.23682808876037598,
0.0646439865231514,
-0.05517495423555374,
-0.05815131589770317,
-0.06910725682973862,
0.04564328491687775,
-0.05991894379258156,
-0.07948964834213257,
0.04528016597032547,
-0.18086330592632294,
0.04425946995615959,
0.07105480879545212,
0.018770307302474976,
-0.019727172330021858,
-0.15522827208042145,
-0.01563870720565319,
0.030741011723876,
-0.04412797465920448,
0.02729402296245098,
0.02511345036327839,
0.11932140588760376,
0.039068613201379776,
-0.039639707654714584,
0.05183930695056915,
0.0296463705599308,
0.1602664738893509,
-0.0253149326890707,
-0.07682201266288757,
0.24625329673290253,
0.16345900297164917,
-0.04810437187552452,
-0.0407007560133934,
0.13308098912239075,
-0.10664761811494827,
-0.07706176489591599,
-0.05416065827012062,
-0.14083269238471985,
-0.13210435211658478,
-0.10297296941280365,
-0.04690646007657051,
-0.10456430912017822,
-0.023472625762224197,
0.09440314769744873,
-0.029888194054365158,
0.11176665127277374,
0.040305063128471375,
-0.0034245122224092484,
-0.1358766257762909,
0.022440610453486443,
0.11887416988611221,
-0.02155303955078125,
0.017903584986925125,
-0.12794391810894012,
0.08485401421785355,
0.09907625615596771,
0.02713124454021454,
0.11476457864046097,
0.14940328896045685,
-0.07030179351568222,
0.18914073705673218,
-0.008559877052903175,
0.06783565133810043,
0.10718917846679688,
-0.03197003901004791,
-0.011863662861287594,
-0.024130214005708694,
-0.11927012354135513,
0.0026024726685136557,
-0.005924802273511887,
0.0183105431497097,
0.0012766994768753648,
0.00977395847439766,
-0.05523708090186119,
0.03137286379933357,
-0.06335774064064026,
-0.06949339061975479,
-0.1884245127439499,
0.022498581558465958,
0.07841265201568604,
0.07303032279014587,
-0.00926866102963686,
0.005129051394760609,
0.1745983511209488,
0.010724211111664772,
0.10516602545976639,
-0.005381713155657053,
0.05089202895760536,
-0.043105337768793106,
0.006139879114925861,
0.06452064216136932,
0.15576207637786865,
0.0642801821231842,
0.054072678089141846,
-0.2820832431316376,
0.1757415533065796,
0.1077679842710495,
0.03906974196434021,
-0.052263494580984116,
-0.01250775158405304,
0.01267986185848713,
0.15531288087368011,
0.054717522114515305,
0.04879981651902199,
-0.15875078737735748,
-0.1416464000940323,
-0.033747609704732895,
0.04848490655422211,
0.07506096363067627,
0.016331806778907776,
0.012452780269086361,
-0.011287611909210682,
0.018230408430099487,
-0.052979450672864914,
0.04216376692056656,
-0.16402596235275269,
-0.09858708083629608,
0.09473281353712082,
0.14904442429542542,
-0.10593239217996597,
-0.05642828345298767,
-0.012926578521728516,
-0.06789383292198181,
-0.016665063798427582,
-0.052752722054719925,
-0.03783446177840233,
-0.12441206723451614,
-0.0811641663312912,
0.08996196836233139,
-0.033072445541620255,
0.04182227700948715,
0.03284639120101929,
0.07706378400325775,
-0.010634208098053932,
-0.171874538064003,
-0.030667392536997795,
-0.10595113784074783,
0.026504473760724068,
0.06577476114034653,
0.05664419010281563,
-0.12098442763090134,
0.06388624757528305,
0.036910153925418854,
0.014792161993682384,
-0.006643546745181084,
-0.20981605350971222,
0.09132430702447891,
0.10574314743280411,
-0.02800455503165722,
-0.03561818227171898,
-0.06930942833423615,
0.0946250632405281,
0.09399145096540451,
-0.16695433855056763,
0.018158691003918648,
0.08020291477441788,
-0.1054903119802475,
0.015577015466988087,
0.02667768858373165,
-0.1419820338487625,
-0.17591546475887299,
-0.11769378185272217,
-0.14365696907043457,
-0.025008749216794968,
0.08527197688817978,
-0.11653953790664673,
-0.030193617567420006,
0.060709577053785324,
0.01799173839390278,
0.05648403987288475,
-0.32058030366897583,
-0.0815163180232048,
-0.014444508589804173,
0.17345653474330902,
0.1358291059732437,
-0.15702436864376068,
-0.1270088404417038,
-0.06850379705429077,
-0.2341918796300888,
0.14770618081092834,
0.0016579048242419958,
0.10148341208696365,
-0.06256815046072006,
0.0903206542134285,
-0.03646033629775047,
-0.011875693686306477,
0.25330719351768494,
-0.06843454390764236,
0.08500301837921143,
-0.06126052513718605,
-0.13330945372581482,
0.002357292687520385,
0.03105047345161438,
0.11499644070863724,
-0.1259428858757019,
0.053711049258708954,
-0.17446468770503998,
0.0010406483197584748,
0.0009829577757045627,
0.011426128447055817,
-0.06678670644760132,
-0.02741989679634571,
0.007270745933055878,
0.010754338465631008,
-0.08454865217208862,
-0.07191232591867447,
-0.10237912833690643,
-0.04875827953219414,
-0.08644469082355499,
-0.016606977209448814,
0.0513610914349556,
-0.05940219387412071,
-0.07950593531131744,
-0.04748553782701492,
-0.020486945286393166,
0.08689211308956146,
-0.062369681894779205,
-0.031687308102846146,
-0.00175979093182832,
0.03212970495223999,
0.0044995201751589775,
0.02979440987110138,
0.062054868787527084,
0.024421967566013336,
0.10234977304935455,
-0.10817775130271912,
-0.12892645597457886,
-0.05117484927177429,
0.17168745398521423,
0.10423020273447037,
0.08608906716108322,
0.10318399965763092,
-0.046085137873888016,
0.013615078292787075,
-0.018849629908800125,
0.002494102343916893,
-0.07722524553537369,
0.039542388170957565,
0.10049952566623688,
0.056183744221925735,
-0.07355238497257233,
-0.02351134829223156,
-0.050177380442619324,
0.14116479456424713,
-0.06777868419885635,
-0.003180289641022682,
0.03269926458597183,
-0.09359169006347656,
0.04031364619731903,
0.04194747284054756,
-0.19185754656791687,
-0.12053380161523819,
-0.046517934650182724,
-0.11387921869754791,
0.07693032920360565,
0.04614003002643585,
0.04623010382056236,
-0.017078455537557602,
-0.008743172511458397,
-0.05822807177901268,
-0.0005432732286863029,
-0.05422016605734825,
-0.25880420207977295,
-0.007389021571725607,
-0.0891931876540184,
0.11494811624288559,
-0.030257459729909897,
0.0725189819931984,
-0.06753841787576675,
0.023336565122008324,
-0.054558876901865005,
0.036673277616500854,
0.07470341771841049,
0.04454214870929718,
-0.0919611006975174,
0.024434581398963928,
0.03221757709980011,
-0.011546923778951168,
-0.12382998317480087,
0.07222890108823776,
-0.0760999247431755,
-0.015714021399617195,
0.014944730326533318,
0.0907449945807457,
0.01445198617875576,
-0.0249094907194376,
-0.008805286139249802,
0.0002694531576707959,
-0.032017722725868225,
0.010509815998375416,
-0.00025495601585134864,
0.007946022786200047,
-0.17206506431102753,
0.03250207006931305,
0.013668530620634556,
0.09606630355119705,
-0.0403592474758625,
-0.11119277030229568,
0.029062004759907722,
0.02531837858259678,
-0.0018883466254919767,
0.02852608636021614,
0.062109820544719696,
-0.12446454912424088,
-0.07683128118515015,
-0.07894468307495117,
0.03357696160674095,
-0.025626765564084053,
0.03308986872434616,
0.09611061215400696,
0.019604256376624107,
0.017390219494700432,
-0.006319801323115826,
-0.04764268174767494,
-0.07895699143409729,
0.047658585011959076,
-0.01779261790215969,
-0.07663535326719284,
-0.032374534755945206,
-0.02420942299067974,
0.038688112050294876,
0.013162314891815186,
0.33939412236213684,
0.08094527572393417,
-0.13784672319889069,
0.003821031656116247,
0.24456949532032013,
0.03920450061559677,
-0.06881041824817657,
0.2552580237388611,
0.0466136559844017,
0.18115700781345367,
0.049717824906110764,
0.07684896886348724,
0.0020255132112652063,
0.004778372589498758,
0.07228405028581619,
0.10872937738895416,
0.03910006955265999,
0.07079380005598068,
0.1757580041885376,
-0.024404633790254593,
0.0490235760807991,
-0.04527838155627251,
-0.013347486965358257,
0.0584561862051487,
-0.0933680608868599,
0.012575802393257618,
0.06208854168653488,
-0.1178516075015068,
0.08274488151073456,
0.07068418711423874,
0.017562557011842728,
-0.09310701489448547,
-0.15595434606075287,
-0.07345733046531677,
-0.08217108249664307,
0.009836013428866863,
-0.04889337345957756,
0.029403166845440865,
0.12431197613477707,
-0.02790771797299385,
0.03815639764070511,
-0.04250307381153107,
-0.1392013132572174,
0.02714339829981327,
-0.08024173229932785,
-0.04299445450305939,
-0.024264110252261162,
-0.23534616827964783,
-0.00229430734179914,
0.010083602741360664,
-0.07867260277271271,
0.004024146590381861,
0.017542287707328796,
0.02309403009712696,
0.00987230148166418,
-0.01231322530657053,
-0.02927880547940731,
-0.04438919946551323,
-0.1009841039776802,
0.06706291437149048,
0.06435342878103256,
-0.014075721614062786,
-0.04433067888021469,
0.0025653394404798746,
-0.005133192054927349,
0.024301206693053246,
-0.10899822413921356,
0.01520633790642023,
-0.1673755645751953,
-0.10284536331892014,
0.05331547185778618,
0.03192960098385811,
0.04100971296429634,
-0.06334129720926285,
0.2848759889602661,
0.21176113188266754,
0.02818448841571808,
0.04854706674814224,
0.04617977887392044,
0.014183866791427135,
0.03528117761015892,
0.13334845006465912,
-0.010359922423958778,
0.05372700095176697,
-0.01642482355237007,
-0.05769287422299385,
-0.13764134049415588,
0.0644211694598198,
0.0017074568895623088,
-0.003429821925237775,
-0.03651416674256325,
-0.100985087454319,
0.06598810106515884,
0.050744716078042984,
0.08041571825742722,
0.04413121938705444,
0.13234443962574005,
0.021149981766939163,
0.030344495549798012,
-0.061142321676015854,
0.086807020008564,
-0.019378775730729103,
-0.029790768399834633,
-0.12053665518760681,
0.03705289587378502,
-0.006181048694998026,
0.03335658088326454,
-0.26004838943481445,
-0.13605184853076935,
0.0978698804974556,
0.10546523332595825,
0.11670758575201035,
-0.019887650385499,
0.13994018733501434,
0.05374833941459656,
-0.08109714090824127,
-0.08931421488523483,
0.17819133400917053,
0.000985911232419312,
-0.16107936203479767,
0.09439855068922043,
0.005357569083571434,
-0.02498699724674225,
0.058888040482997894,
-0.08677048236131668,
0.16805227100849152,
0.053992997854948044,
0.11108721792697906,
-0.039332740008831024,
0.06295835971832275,
0.020954785868525505,
-0.14143764972686768,
0.09622462093830109,
0.023382941260933876,
-0.007639856077730656,
-0.07968543469905853,
-0.026589950546622276,
0.10250578075647354,
-0.018579015508294106,
-0.1253366619348526,
-0.013197694905102253,
-0.008912167511880398,
-0.05224940925836563,
-0.0924379751086235,
0.015688972547650337,
-0.07139673084020615,
-0.06080547347664833,
-0.02582208253443241,
-0.08022752404212952,
-0.03976556286215782,
-0.005541914142668247,
0.2242787480354309,
-0.012099407613277435,
-0.09183369576931,
-0.32672473788261414,
0.015383290126919746,
0.036501698195934296,
-0.14336849749088287,
-0.049285490065813065
] |
null | null | diffusers |
# VR-MUEPICX API Inference
## Get API Key
Get API key from [ModelsLab API](http://modelslab.com), No Payment needed.
Replace Key in below code, change **model_id** to "vr-muepicx"
Coding in PHP/Node/Java etc? Have a look at docs for more code examples: [View docs](https://modelslab.com/docs)
Try model for free: [Generate Images](https://modelslab.com/models/vr-muepicx)
Model link: [View model](https://modelslab.com/models/vr-muepicx)
View all models: [View Models](https://modelslab.com/models)
import requests
import json
url = "https://modelslab.com/api/v6/images/text2img"
payload = json.dumps({
"key": "your_api_key",
"model_id": "vr-muepicx",
"prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K",
"negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",
"width": "512",
"height": "512",
"samples": "1",
"num_inference_steps": "30",
"safety_checker": "no",
"enhance_prompt": "yes",
"seed": None,
"guidance_scale": 7.5,
"multi_lingual": "no",
"panorama": "no",
"self_attention": "no",
"upscale": "no",
"embeddings": "embeddings_model_id",
"lora": "lora_model_id",
"webhook": None,
"track_id": None
})
headers = {
'Content-Type': 'application/json'
}
response = requests.request("POST", url, headers=headers, data=payload)
print(response.text)
> Use this coupon code to get 25% off **DMGG0RBN** | {"license": "creativeml-openrail-m", "tags": ["modelslab.com", "stable-diffusion-api", "text-to-image", "ultra-realistic"], "pinned": true} | text-to-image | stablediffusionapi/vr-muepicx | [
"diffusers",
"modelslab.com",
"stable-diffusion-api",
"text-to-image",
"ultra-realistic",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | 2024-02-11T05:32:08+00:00 | [] | [] | TAGS
#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# VR-MUEPICX API Inference
!generated from URL
## Get API Key
Get API key from ModelsLab API, No Payment needed.
Replace Key in below code, change model_id to "vr-muepicx"
Coding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs
Try model for free: Generate Images
Model link: View model
View all models: View Models
import requests
import json
url = "URL
payload = URL({
"key": "your_api_key",
"model_id": "vr-muepicx",
"prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K",
"negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",
"width": "512",
"height": "512",
"samples": "1",
"num_inference_steps": "30",
"safety_checker": "no",
"enhance_prompt": "yes",
"seed": None,
"guidance_scale": 7.5,
"multi_lingual": "no",
"panorama": "no",
"self_attention": "no",
"upscale": "no",
"embeddings": "embeddings_model_id",
"lora": "lora_model_id",
"webhook": None,
"track_id": None
})
headers = {
'Content-Type': 'application/json'
}
response = requests.request("POST", url, headers=headers, data=payload)
print(URL)
> Use this coupon code to get 25% off DMGG0RBN | [
"# VR-MUEPICX API Inference\n\n!generated from URL",
"## Get API Key\n\nGet API key from ModelsLab API, No Payment needed. \n\nReplace Key in below code, change model_id to \"vr-muepicx\"\n\nCoding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs\n\nTry model for free: Generate Images\n\nModel link: View model\n\nView all models: View Models\n\n import requests \n import json \n \n url = \"URL \n \n payload = URL({ \n \"key\": \"your_api_key\", \n \"model_id\": \"vr-muepicx\", \n \"prompt\": \"ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K\", \n \"negative_prompt\": \"painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime\", \n \"width\": \"512\", \n \"height\": \"512\", \n \"samples\": \"1\", \n \"num_inference_steps\": \"30\", \n \"safety_checker\": \"no\", \n \"enhance_prompt\": \"yes\", \n \"seed\": None, \n \"guidance_scale\": 7.5, \n \"multi_lingual\": \"no\", \n \"panorama\": \"no\", \n \"self_attention\": \"no\", \n \"upscale\": \"no\", \n \"embeddings\": \"embeddings_model_id\", \n \"lora\": \"lora_model_id\", \n \"webhook\": None, \n \"track_id\": None \n }) \n \n headers = { \n 'Content-Type': 'application/json' \n } \n \n response = requests.request(\"POST\", url, headers=headers, data=payload) \n \n print(URL)\n\n> Use this coupon code to get 25% off DMGG0RBN"
] | [
"TAGS\n#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us \n",
"# VR-MUEPICX API Inference\n\n!generated from URL",
"## Get API Key\n\nGet API key from ModelsLab API, No Payment needed. \n\nReplace Key in below code, change model_id to \"vr-muepicx\"\n\nCoding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs\n\nTry model for free: Generate Images\n\nModel link: View model\n\nView all models: View Models\n\n import requests \n import json \n \n url = \"URL \n \n payload = URL({ \n \"key\": \"your_api_key\", \n \"model_id\": \"vr-muepicx\", \n \"prompt\": \"ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K\", \n \"negative_prompt\": \"painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime\", \n \"width\": \"512\", \n \"height\": \"512\", \n \"samples\": \"1\", \n \"num_inference_steps\": \"30\", \n \"safety_checker\": \"no\", \n \"enhance_prompt\": \"yes\", \n \"seed\": None, \n \"guidance_scale\": 7.5, \n \"multi_lingual\": \"no\", \n \"panorama\": \"no\", \n \"self_attention\": \"no\", \n \"upscale\": \"no\", \n \"embeddings\": \"embeddings_model_id\", \n \"lora\": \"lora_model_id\", \n \"webhook\": None, \n \"track_id\": None \n }) \n \n headers = { \n 'Content-Type': 'application/json' \n } \n \n response = requests.request(\"POST\", url, headers=headers, data=payload) \n \n print(URL)\n\n> Use this coupon code to get 25% off DMGG0RBN"
] | [
70,
16,
550
] | [
"passage: TAGS\n#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us \n# VR-MUEPICX API Inference\n\n!generated from URL"
] | [
-0.07363653928041458,
0.006773008033633232,
-0.004718591459095478,
0.006841793190687895,
0.14092622697353363,
-0.045208971947431564,
0.16082604229450226,
-0.004369713366031647,
0.05182613804936409,
0.009211791679263115,
0.14594298601150513,
0.19449947774410248,
-0.0009060925804078579,
0.1702977418899536,
-0.07170221954584122,
-0.2478323131799698,
0.02157566323876381,
0.014034668914973736,
-0.002898197155445814,
0.037145134061574936,
0.13433605432510376,
-0.07110785692930222,
0.14298486709594727,
0.0035463618114590645,
-0.08225607126951218,
-0.024163296446204185,
-0.0015756824286654592,
-0.0508759431540966,
0.020437948405742645,
0.09651786834001541,
-0.013183771632611752,
0.10599597543478012,
0.032944124191999435,
-0.113890141248703,
0.042125724256038666,
0.02138596586883068,
-0.08929584175348282,
0.04212100803852081,
0.03325799107551575,
0.016406964510679245,
0.16180917620658875,
0.01198816578835249,
-0.031992536038160324,
0.05399472266435623,
-0.06341905146837234,
-0.081980861723423,
0.01232301164418459,
0.022883055731654167,
0.040257591754198074,
-0.001331452513113618,
0.05128278210759163,
0.10542435199022293,
0.02953524887561798,
0.08218450844287872,
0.09995955228805542,
-0.28386038541793823,
-0.033975448459386826,
0.24803055822849274,
0.13879111409187317,
0.03191952779889107,
-0.055531881749629974,
0.11818218231201172,
0.04851383715867996,
-0.017133209854364395,
0.07059112191200256,
-0.04173092916607857,
0.1489609181880951,
-0.03574485704302788,
-0.07744037359952927,
0.03844824060797691,
0.20250390470027924,
0.0797962173819542,
0.004421252757310867,
-0.147877499461174,
-0.0821969211101532,
0.10796861350536346,
-0.1046118438243866,
0.0145260039716959,
0.014696234837174416,
0.027439560741186142,
-0.04755657538771629,
-0.06812318414449692,
-0.08165822923183441,
0.009080076590180397,
-0.05492151156067848,
0.026681603863835335,
-0.004503264091908932,
0.09624752402305603,
-0.09729854762554169,
0.05821806192398071,
-0.06123502925038338,
-0.12970834970474243,
0.005054703913629055,
-0.17698436975479126,
0.0801689475774765,
0.03465369716286659,
0.007833966985344887,
-0.13392376899719238,
0.07701341062784195,
0.003414067905396223,
0.034823596477508545,
-0.033254239708185196,
0.08450627326965332,
0.1269291639328003,
0.047809842973947525,
-0.027455298230051994,
-0.1939748078584671,
-0.011297652497887611,
0.0319860503077507,
-0.06939440965652466,
0.03242046386003494,
-0.03444604203104973,
-0.11953248083591461,
-0.024516107514500618,
-0.10637873411178589,
0.001484973938204348,
0.02143106237053871,
0.05323255434632301,
-0.010171636007726192,
-0.06310717761516571,
0.09387452900409698,
0.052127327769994736,
-0.016414087265729904,
-0.04593583568930626,
-0.028257042169570923,
0.2609037756919861,
0.10159513354301453,
0.01100730337202549,
-0.005516931880265474,
0.09521627426147461,
-0.06890826672315598,
0.02804216369986534,
-0.04733230918645859,
-0.09460734575986862,
0.03426916152238846,
-0.13458220660686493,
0.05179233103990555,
-0.13464011251926422,
-0.11991998553276062,
0.018689949065446854,
0.09846557676792145,
-0.04382136091589928,
-0.01800020970404148,
0.04905671998858452,
-0.04122517257928848,
0.04511620104312897,
-0.004311615135520697,
-0.031042953953146935,
-0.05535319820046425,
0.009236831218004227,
-0.09211055189371109,
0.08905156701803207,
-0.1733054220676422,
0.0407724604010582,
0.04302103817462921,
0.015736550092697144,
-0.09131883084774017,
0.019926903769373894,
-0.09217485040426254,
0.11411476880311966,
-0.03782958909869194,
-0.04708581045269966,
0.05215199664235115,
0.014745257794857025,
0.02443438582122326,
0.13535332679748535,
-0.10461738705635071,
0.01900024339556694,
0.1750355362892151,
-0.07953985780477524,
-0.148619145154953,
0.07274164259433746,
0.0001886318059405312,
0.048230383545160294,
0.021736811846494675,
-0.032819025218486786,
0.02554931864142418,
-0.3408113718032837,
0.13134051859378815,
0.10815135389566422,
-0.095293790102005,
-0.14343984425067902,
0.061897166073322296,
0.06859078258275986,
0.0037617869675159454,
0.06465144455432892,
-0.007865406572818756,
0.0867823138833046,
-0.10750098526477814,
-0.012929772958159447,
-0.049661971628665924,
-0.06644347310066223,
-0.02938353829085827,
0.03368927538394928,
0.0713270902633667,
0.006684655789285898,
-0.015002110041677952,
0.0341862216591835,
0.01303595956414938,
0.014680348336696625,
-0.036469683051109314,
-0.06386422365903854,
0.1466337889432907,
-0.13009002804756165,
-0.0036662009079009295,
-0.04816671088337898,
0.00014430185547098517,
-0.014158905483782291,
0.14234493672847748,
-0.027725333347916603,
0.22092688083648682,
0.0794295147061348,
0.05406294763088226,
0.0007973316824063659,
0.021682288497686386,
0.04409713298082352,
0.052904654294252396,
-0.02355637215077877,
-0.1929526925086975,
0.050168201327323914,
-0.08735919743776321,
-0.04194462671875954,
-0.11572075635194778,
-0.007735860999673605,
-0.02535979449748993,
0.14133276045322418,
0.08202438056468964,
0.02301352471113205,
0.031229816377162933,
-0.02507510781288147,
-0.031537096947431564,
-0.0017329633701592684,
0.11455870419740677,
0.03751157596707344,
0.042309440672397614,
0.2526768147945404,
-0.051614079624414444,
0.3252914547920227,
0.14626693725585938,
-0.14662910997867584,
-0.01809672638773918,
-0.05868064984679222,
-0.0409674309194088,
0.060857806354761124,
-0.022900443524122238,
0.01706438884139061,
-0.06676142662763596,
0.007242096122354269,
0.14843565225601196,
-0.055279847234487534,
0.015714531764388084,
0.09104549884796143,
-0.06467532366514206,
-0.05631972476840019,
0.09321492165327072,
0.19324913620948792,
-0.11019990593194962,
0.0683528259396553,
0.13920196890830994,
0.03345604985952377,
0.15871408581733704,
0.006432073190808296,
-0.031085925176739693,
-0.062197379767894745,
0.043718039989471436,
0.009991033002734184,
0.1594225913286209,
-0.11600519716739655,
-0.0028194282203912735,
0.05383353307843208,
-0.048603788018226624,
0.050151973962783813,
-0.035909492522478104,
-0.036069516092538834,
0.052259497344493866,
0.021790185943245888,
0.07970777899026871,
0.17069236934185028,
-0.06997232139110565,
0.11600843816995621,
-0.06544363498687744,
-0.08272333443164825,
0.010811643674969673,
-0.025638889521360397,
-0.05980486422777176,
0.08625119179487228,
-0.05957644432783127,
-0.05720071122050285,
-0.12110341340303421,
-0.18235568702220917,
-0.0917881578207016,
-0.010973578318953514,
0.027298275381326675,
0.01974407024681568,
-0.0747600719332695,
-0.057782359421253204,
-0.03676609322428703,
-0.02784956619143486,
-0.015790197998285294,
-0.00017637510609347373,
0.054698340594768524,
-0.048168305307626724,
-0.07197342813014984,
-0.029378261417150497,
-0.05118720233440399,
0.07674986124038696,
0.07979542762041092,
0.0017463259864598513,
0.137664332985878,
0.053637001663446426,
-0.005172826815396547,
0.030614694580435753,
0.05718990042805672,
0.2592950463294983,
0.04332840070128441,
0.07438618689775467,
0.2581521272659302,
0.10568146407604218,
0.05469225347042084,
0.1379772573709488,
0.06344711035490036,
-0.0725758746266365,
0.008929730392992496,
-0.06536106020212173,
-0.09903430938720703,
-0.1028590127825737,
-0.1199890747666359,
-0.11327377706766129,
-0.021333087235689163,
-0.004540754482150078,
0.0006319747772067785,
0.03161940723657608,
0.1606092005968094,
0.015065562911331654,
0.040990281850099564,
-0.015943195670843124,
0.06922658532857895,
0.08602935820817947,
-0.05137230455875397,
0.05767928063869476,
-0.10213245451450348,
-0.04083062708377838,
0.12548859417438507,
0.009871595539152622,
0.09712962061166763,
-0.0029569377657026052,
-0.05886935815215111,
0.14219270646572113,
0.009643887169659138,
0.11717637628316879,
0.09606067836284637,
-0.041648849844932556,
-0.049637943506240845,
-0.03841754421591759,
-0.08543246239423752,
0.05695745721459389,
0.07895738631486893,
0.038378454744815826,
-0.09453201293945312,
-0.05290067940950394,
0.050793737173080444,
0.01840062625706196,
0.06896713376045227,
0.10367383062839508,
-0.22014755010604858,
0.014287781901657581,
0.02891814522445202,
0.10829687863588333,
-0.05141707509756088,
0.021697349846363068,
0.14138326048851013,
-0.06417226046323776,
0.07099339365959167,
-0.07137447595596313,
0.12254145741462708,
0.05160244181752205,
-0.01020457036793232,
0.015806427225470543,
0.08030182123184204,
0.03247126564383507,
0.016522156074643135,
-0.1751975119113922,
0.18249180912971497,
-0.007936041802167892,
0.05566268414258957,
-0.01164924819022417,
-0.020280547440052032,
0.03307463973760605,
0.1867382824420929,
0.1627238392829895,
0.017882607877254486,
0.03213157504796982,
0.011301721446216106,
-0.09874320775270462,
-0.012951543554663658,
0.012281359173357487,
0.06056192144751549,
-0.01008934061974287,
0.04305274784564972,
-0.04674924165010452,
-0.0060090357437729836,
0.10344035178422928,
-0.20487119257450104,
-0.1437443047761917,
0.013916326686739922,
0.08079945296049118,
-0.076633021235466,
-0.017720388248562813,
-0.003642627038061619,
-0.11089462786912918,
0.11696624755859375,
-0.04486280679702759,
-0.08793755620718002,
-0.1427106112241745,
-0.061252910643815994,
-0.020362716168165207,
-0.038959380239248276,
0.0499197281897068,
-0.11310168355703354,
0.05764582008123398,
-0.04869132488965988,
-0.14530852437019348,
0.0849347934126854,
-0.14698711037635803,
0.004464568104594946,
-0.09558705985546112,
0.025981051847338676,
-0.055489979684352875,
-0.05502001568675041,
0.018800854682922363,
-0.04381157457828522,
-0.07452666759490967,
-0.15200243890285492,
0.04230806604027748,
0.1607326716184616,
-0.02533261850476265,
-0.017919830977916718,
-0.11706434935331345,
-0.06540660560131073,
0.08829432725906372,
-0.004402305465191603,
0.13990482687950134,
0.18178629875183105,
-0.11886397749185562,
0.08288753032684326,
0.1878420114517212,
-0.024469813331961632,
-0.2582772672176361,
-0.09505271911621094,
-0.07412104308605194,
-0.02401568554341793,
-0.019130229949951172,
-0.05909653753042221,
0.09146647155284882,
-0.047599587589502335,
-0.016772793605923653,
0.16237832605838776,
-0.3492491841316223,
-0.11637341231107712,
0.023897679522633553,
0.14687877893447876,
0.32128745317459106,
-0.11966005712747574,
-0.04835779219865799,
-0.06868498027324677,
-0.35661938786506653,
0.105878084897995,
-0.07467138022184372,
0.05941407009959221,
-0.046103887259960175,
0.018208373337984085,
-0.029999570921063423,
-0.07586422562599182,
0.12904642522335052,
-0.07845083624124527,
0.08229553699493408,
-0.09841422736644745,
0.09594739228487015,
0.10937336832284927,
-0.01713167503476143,
0.08222083002328873,
-0.11777902394533157,
0.07568542659282684,
-0.1694784164428711,
-0.046424902975559235,
-0.039894409477710724,
0.04714584723114967,
-0.024920305237174034,
-0.09051511436700821,
-0.03332039341330528,
0.0040693930350244045,
0.07804962992668152,
-0.0036736170295625925,
-0.023954026401042938,
-0.01988762989640236,
0.03655771538615227,
0.196307972073555,
-0.036141905933618546,
-0.15333235263824463,
-0.12729060649871826,
-0.08734164386987686,
-0.037732694298028946,
0.11229126155376434,
-0.06545784324407578,
-0.05417453870177269,
0.1268707662820816,
-0.004382994491606951,
0.04902402684092522,
0.0407373420894146,
-0.010708773508667946,
0.06255613267421722,
0.06813220679759979,
-0.1302594393491745,
-0.08485527336597443,
-0.044694773852825165,
0.2395191192626953,
0.1621602326631546,
0.0681099072098732,
0.13541093468666077,
-0.07634227722883224,
0.05690741911530495,
-0.04426894336938858,
0.025610191747546196,
-0.009869798086583614,
0.027315059676766396,
0.05227457731962204,
0.018475469201803207,
-0.08269940316677094,
0.014836752787232399,
-0.07506957650184631,
-0.10486201196908951,
-0.0909835696220398,
-0.004823013674467802,
-0.11461154371500015,
-0.0840623527765274,
0.0571383573114872,
0.1175435408949852,
-0.19914793968200684,
-0.028206096962094307,
0.006826504599303007,
-0.137002095580101,
0.08241775631904602,
0.12192331999540329,
0.037727389484643936,
-0.011519168503582478,
0.008860145695507526,
-0.11257033795118332,
-0.02266479656100273,
0.01711427979171276,
0.022314341738820076,
0.04623168706893921,
-0.18325623869895935,
-0.14212508499622345,
-0.039321597665548325,
0.04332193359732628,
-0.09591789543628693,
-0.004827313125133514,
-0.12197750806808472,
-0.0203816257417202,
-0.14330628514289856,
0.04847107455134392,
-0.1121019795536995,
-0.051064103841781616,
-0.03759847581386566,
-0.05742812529206276,
-0.07059617340564728,
0.06098328158259392,
-0.07254234701395035,
-0.009479796513915062,
0.003961324226111174,
0.029049884527921677,
-0.0373418852686882,
-0.033738914877176285,
-0.029053745791316032,
-0.06698514521121979,
0.061769675463438034,
-0.0006114045972935855,
-0.12052829563617706,
-0.0869828537106514,
-0.3060774803161621,
-0.06219791993498802,
0.06208360567688942,
0.023171404376626015,
0.047204867005348206,
0.04199347645044327,
0.10100525617599487,
0.03241363540291786,
-0.01800360158085823,
-0.04468253627419472,
0.06200859323143959,
-0.10049579292535782,
-0.03962818905711174,
-0.050642479211091995,
0.0448225699365139,
-0.05909762904047966,
0.009124591946601868,
0.10436777770519257,
0.07742438465356827,
0.11965247243642807,
-0.07642599940299988,
0.07103148102760315,
-0.06833512336015701,
0.03008817322552204,
0.046505287289619446,
-0.0588969923555851,
0.062369588762521744,
-0.008752056397497654,
-0.012232577428221703,
-0.029437361285090446,
0.30507129430770874,
0.0424397774040699,
-0.15321920812129974,
0.025686057284474373,
-0.04119674488902092,
-0.011782702058553696,
0.01083554606884718,
0.17674775421619415,
-0.004683304112404585,
0.08690929412841797,
-0.18207915127277374,
0.07838873565196991,
0.0915980115532875,
0.0064296722412109375,
0.026178201660513878,
0.15856537222862244,
-0.025476353242993355,
0.08352089673280716,
0.07269570231437683,
0.035818103700876236,
0.03476719558238983,
0.01639103703200817,
-0.03376929089426994,
0.16723208129405975,
-0.10380221158266068,
-0.08754729479551315,
0.165361687541008,
-0.01506885141134262,
0.018256209790706635,
0.04166880249977112,
-0.003582427278161049,
-0.08545379340648651,
-0.1342022716999054,
-0.07482217997312546,
-0.17134219408035278,
0.05090690776705742,
-0.029156187549233437,
0.011143906973302364,
-0.07024382799863815,
0.08808545768260956,
-0.006178468000143766,
-0.05436765402555466,
-0.09919851273298264,
-0.03982366621494293,
0.1221865564584732,
-0.015419583767652512,
-0.07714267075061798,
0.0161726176738739,
0.038464028388261795,
-0.04219794645905495,
-0.05740223824977875,
-0.06196748837828636,
0.07318472117185593,
-0.028160426765680313,
0.045200370252132416,
0.02168944664299488,
-0.031496189534664154,
-0.015654077753424644,
-0.010333772748708725,
-0.019710170105099678,
0.18781116604804993,
0.011718609370291233,
0.007197441533207893,
-0.005181870888918638,
0.10785923153162003,
-0.005903926212340593,
-0.06578321009874344,
-0.13482734560966492,
-0.03615839406847954,
-0.027855128049850464,
0.10707662254571915,
-0.06030023843050003,
-0.0005234284326434135,
-0.042804181575775146,
0.22910703718662262,
0.24948255717754364,
-0.1674509346485138,
0.016798123717308044,
-0.02200864441692829,
0.014445038512349129,
-0.0013321039732545614,
0.08933858573436737,
0.02599141001701355,
0.3055438697338104,
-0.044129375368356705,
-0.030834335833787918,
-0.10444056242704391,
-0.014600085094571114,
-0.07387177646160126,
-0.09608291834592819,
0.05477485805749893,
-0.07468631118535995,
-0.044052157551050186,
0.09808026254177094,
-0.18378223478794098,
0.050198521465063095,
0.0794147402048111,
-0.05035622790455818,
0.0255555659532547,
-0.07263864576816559,
0.04384324699640274,
0.05218107998371124,
0.04874509200453758,
-0.09667663276195526,
-0.030270995572209358,
0.06842026859521866,
-0.0030954184476286173,
-0.10454119741916656,
0.06770211458206177,
0.008798996917903423,
0.007868790999054909,
0.07318587601184845,
-0.025576923042535782,
-0.012277644127607346,
0.09361673146486282,
-0.02968563511967659,
-0.07485472410917282,
0.08060449361801147,
0.0020532114431262016,
-0.07633402943611145,
-0.008174024522304535,
0.03325880691409111,
-0.024678699672222137,
-0.03701269254088402,
-0.037928733974695206,
-0.07512085884809494,
0.029074804857373238,
-0.016043372452259064,
-0.06894060224294662,
-0.0372350849211216,
0.10280013829469681,
-0.04970815032720566,
0.06850117444992065,
0.01340459194034338,
-0.023947181180119514,
-0.05448026582598686,
-0.02407550811767578,
0.09033969044685364,
0.005497055593878031,
-0.17382976412773132,
0.0027217878960072994,
-0.041136324405670166,
-0.019795333966612816,
-0.019605882465839386,
0.08061476051807404,
-0.13914349675178528,
-0.008853208273649216,
-0.1320343166589737,
0.016565654426813126,
-0.03842419385910034,
0.058406077325344086,
0.23019349575042725,
0.019985772669315338,
-0.03221287205815315,
-0.06336218118667603,
0.013878819532692432,
0.051339227706193924,
-0.0037040370516479015,
-0.09847600758075714
] |
null | null | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="sanchitkalra/q-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
| {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- 2.71", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | sanchitkalra/q-Taxi-v3 | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | 2024-02-11T05:36:15+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
| [
"# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
] | [
"TAGS\n#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n",
"# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
] | [
32,
33
] | [
"passage: TAGS\n#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
] | [
0.048862796276807785,
-0.16549694538116455,
-0.005485367961227894,
0.02960980497300625,
0.1345081776380539,
-0.01784728653728962,
0.11895976960659027,
0.07759871333837509,
-0.07461097836494446,
-0.055395450443029404,
0.1418241262435913,
0.09088201075792313,
0.055222880095243454,
0.05699880048632622,
0.09511256217956543,
-0.27440664172172546,
0.048217080533504486,
-0.02918700873851776,
0.05621987581253052,
0.11878681182861328,
0.0670095682144165,
-0.040441032499074936,
0.061956584453582764,
0.11818158626556396,
-0.1018151044845581,
-0.007344264071434736,
0.035402704030275345,
-0.09440053254365921,
0.17413531243801117,
0.07204403728246689,
0.12337774783372879,
0.05132639780640602,
0.179361954331398,
-0.12762396037578583,
0.024310702458024025,
-0.0010275895474478602,
-0.10138072073459625,
-0.03909514099359512,
-0.012415820732712746,
-0.08349097520112991,
0.03230205550789833,
0.23522862792015076,
0.07199250161647797,
0.06632792949676514,
-0.17707863450050354,
-0.06584878265857697,
-0.04375573247671127,
0.069611094892025,
0.14951466023921967,
0.03758616745471954,
-0.033800311386585236,
0.1684885323047638,
-0.2564343810081482,
0.05066783353686333,
0.037275806069374084,
-0.42313119769096375,
0.017119819298386574,
0.1507398933172226,
0.15090937912464142,
0.06909667700529099,
-0.10573802888393402,
0.013512322679162025,
0.051325585693120956,
-0.0005318621988408267,
0.024325110018253326,
0.006554204970598221,
0.15601307153701782,
0.08537693321704865,
-0.1487821787595749,
-0.058576688170433044,
0.17441977560520172,
-0.03788546845316887,
-0.02613203600049019,
-0.039745692163705826,
0.0067160045728087425,
-0.06427708268165588,
-0.004067842848598957,
-0.1777995079755783,
0.00734262028709054,
0.06666424125432968,
-0.014348524622619152,
0.014901017770171165,
-0.035522811114788055,
-0.0966939702630043,
-0.023098144680261612,
-0.08592145889997482,
0.01677769608795643,
-0.006319406442344189,
-0.10187895596027374,
0.05002119392156601,
-0.061138734221458435,
0.0014382408699020743,
-0.05123179033398628,
-0.15047866106033325,
-0.049055423587560654,
-0.03481535613536835,
0.1474713832139969,
-0.0044205985032022,
-0.01873963139951229,
-0.03164304047822952,
0.15474793314933777,
0.049551334232091904,
-0.05370146036148071,
0.05625450983643532,
0.07605006545782089,
0.23867930471897125,
0.10401605814695358,
0.10196955502033234,
-0.06798075139522552,
0.10180158913135529,
-0.12330973148345947,
-0.08915644884109497,
-0.17508824169635773,
0.11820860952138901,
0.00015364694991149008,
0.1317785084247589,
-0.12023144960403442,
0.07898581773042679,
-0.067511186003685,
0.013453764840960503,
0.01636839471757412,
0.0820009782910347,
-0.012399360537528992,
0.10676060616970062,
-0.005061192903667688,
-0.06941985338926315,
0.014177112840116024,
0.05935845896601677,
0.03754841163754463,
-0.038601722568273544,
-0.03192409873008728,
-0.05762290954589844,
-0.05065649375319481,
-0.10128600150346756,
-0.06447898596525192,
0.018573462963104248,
-0.007677143905311823,
-0.1833900660276413,
-0.06407523155212402,
0.00897200871258974,
0.015712225809693336,
-0.03988850116729736,
-0.05148044601082802,
-0.15265507996082306,
-0.042461175471544266,
-0.015450406819581985,
-0.03500641882419586,
-0.06214277446269989,
-0.0383245050907135,
0.046435944736003876,
-0.07560601085424423,
0.013364278711378574,
0.023342855274677277,
0.05405820533633232,
-0.025881100445985794,
0.06068144738674164,
-0.08357544988393784,
0.09493788331747055,
-0.1540430635213852,
-0.03271956741809845,
-0.025445878505706787,
-0.041183918714523315,
0.1752462536096573,
0.06099751964211464,
-0.015994304791092873,
0.15260063111782074,
-0.17141541838645935,
-0.058121129870414734,
0.15596486628055573,
0.008629098534584045,
-0.09967197477817535,
-0.003560945624485612,
-0.09397093951702118,
0.1428760588169098,
0.08571921288967133,
0.2478504776954651,
0.12005335837602615,
-0.22748184204101562,
0.055358242243528366,
0.12515293061733246,
-0.14365963637828827,
0.10365243256092072,
0.07344598323106766,
0.005470725707709789,
-0.18886831402778625,
-0.06843198090791702,
-0.06121627986431122,
0.1053021252155304,
-0.08522345870733261,
-0.0776243582367897,
0.09323626756668091,
-0.05086790770292282,
0.24641476571559906,
-0.028281206265091896,
0.06174173951148987,
-0.026681531220674515,
-0.1389324963092804,
-0.01723906397819519,
0.060955192893743515,
0.05258452147245407,
-0.024835573509335518,
-0.25895482301712036,
0.13646544516086578,
0.048650871962308884,
0.025074828416109085,
0.004106190986931324,
-0.05691491439938545,
0.016934165731072426,
0.1511998474597931,
0.020012924447655678,
0.13717477023601532,
0.027723990380764008,
0.0706823319196701,
-0.006239562761038542,
-0.10560829937458038,
-0.04169593006372452,
0.061916545033454895,
-0.08518962562084198,
-0.06641357392072678,
0.011197872459888458,
-0.06935211271047592,
-0.11783787608146667,
-0.12166737765073776,
-0.026334572583436966,
-0.02980303019285202,
-0.07444227486848831,
0.02368103712797165,
0.06536602973937988,
-0.06702698022127151,
-0.0023908785078674555,
0.007125476840883493,
-0.011537045240402222,
0.16434046626091003,
0.011393417604267597,
-0.007796820718795061,
0.1328643560409546,
-0.11533161997795105,
0.12461213022470474,
0.049438029527664185,
-0.024806302040815353,
-0.04662557691335678,
0.0014137453399598598,
-0.057529181241989136,
0.029044216498732567,
-0.04390640929341316,
0.02774495631456375,
0.20111067593097687,
0.02772962674498558,
0.11389166116714478,
-0.0656520202755928,
0.04385066404938698,
-0.007961965166032314,
-0.009693224914371967,
0.018563594669103622,
0.07608018070459366,
0.07813210040330887,
-0.1324140727519989,
0.02262016013264656,
0.22455167770385742,
0.1385764330625534,
0.18313980102539062,
-0.010877152904868126,
0.06325667351484299,
-0.04875868931412697,
0.027505528181791306,
0.024100203067064285,
0.10314226150512695,
-0.10732068121433258,
-0.0322517491877079,
-0.025407759472727776,
0.023599207401275635,
-0.08197105675935745,
-0.1055799350142479,
-0.090115025639534,
0.01222382951527834,
-0.03125503659248352,
-0.15570329129695892,
0.13300658762454987,
-0.10451057553291321,
0.01802753657102585,
0.04692702740430832,
-0.22163605690002441,
0.11530312895774841,
0.014291439205408096,
-0.10303618758916855,
0.11281087249517441,
-0.12051989883184433,
-0.08699832111597061,
-0.05777236074209213,
-0.18658851087093353,
0.05280197039246559,
0.04673841595649719,
0.05166793242096901,
-0.18521739542484283,
0.024835903197526932,
0.05545609071850777,
0.13426995277404785,
-0.09743253141641617,
-0.07142634689807892,
-0.15038461983203888,
0.016068490222096443,
-0.033661190420389175,
-0.16029728949069977,
-0.005609163548797369,
-0.032781440764665604,
-0.18849676847457886,
-0.04539939761161804,
-0.15086813271045685,
-0.034627582877874374,
0.20464378595352173,
0.026907702907919884,
0.09480511397123337,
-0.07926445454359055,
0.3802889585494995,
-0.042039383202791214,
-0.06146497279405594,
-0.01321389526128769,
-0.07072482258081436,
0.02512686513364315,
0.13271741569042206,
0.0036099457647651434,
-0.017886579036712646,
-0.0037857077550143003,
0.0024592927657067776,
-0.06234965845942497,
-0.13400450348854065,
0.0028710351325571537,
0.03905198723077774,
0.1874423623085022,
0.004639793653041124,
0.06659388542175293,
0.03133883699774742,
0.057546284049749374,
0.07748064398765564,
0.030926106497645378,
0.0011591583024710417,
-0.01591806672513485,
0.06604493409395218,
-0.11684755235910416,
0.042466625571250916,
-0.030429253354668617,
-0.10143838077783585,
-0.013183288276195526,
0.07950251549482346,
0.12755028903484344,
0.17849206924438477,
-0.04790908098220825,
0.17489230632781982,
0.13580141961574554,
0.16576050221920013,
0.049315933138132095,
-0.020801831036806107,
-0.08773037046194077,
-0.06118565797805786,
0.004774159751832485,
-0.031952597200870514,
0.04869702458381653,
0.3231290578842163,
0.037619613111019135,
-0.09036035090684891,
0.11149907857179642,
0.009480619803071022,
0.05359881371259689,
0.022797370329499245,
-0.11162138730287552,
0.11170321702957153,
0.07968773692846298,
-0.06341761350631714,
-0.07602835446596146,
0.16758501529693604,
-0.1109386757016182,
-0.26646625995635986,
-0.11410990357398987,
-0.012305386364459991,
0.07903840392827988,
0.005651174578815699,
0.05498376116156578,
-0.11829282343387604,
-0.16034497320652008,
-0.034191906452178955,
0.1335442066192627,
-0.3077351450920105,
0.2065143585205078,
-0.0198091771453619,
0.06707923114299774,
-0.039657969027757645,
-0.07026876509189606,
0.09694647043943405,
0.13174086809158325,
0.29124146699905396,
0.01396956667304039,
0.04841272905468941,
-0.15176129341125488,
-0.0976925864815712,
0.0018439020495861769,
0.015482662245631218,
-0.02563396655023098,
0.028520405292510986,
-0.0540912002325058,
0.008404579944908619,
-0.018086453899741173,
0.2102297693490982,
-0.11316607892513275,
0.004344627261161804,
-0.06968966871500015,
-0.11707738786935806,
0.19409789144992828,
-0.07178345322608948,
-0.04543264955282211,
-0.14959357678890228,
-0.15512511134147644,
-0.004174166824668646,
-0.02413962036371231,
-0.019664527848362923,
-0.17603960633277893,
-0.18804074823856354,
-0.05204557999968529,
-0.005645004566758871,
-0.003464865731075406,
0.05867868289351463,
-0.07517234236001968,
-0.04805335775017738,
0.1009904220700264,
-0.07743175327777863,
-0.056063808500766754,
-0.1103200614452362,
0.1391381323337555,
0.06248528137803078,
0.16743235290050507,
0.05907081440091133,
0.0006117874872870743,
0.11471151560544968,
-0.02913086675107479,
0.11103474348783493,
-0.11291708797216415,
-0.17145049571990967,
-0.08334989100694656,
-0.018775060772895813,
0.09519003331661224,
-0.04789286106824875,
0.0028788831550627947,
0.2550160884857178,
0.14880181849002838,
-0.0897710770368576,
0.27680760622024536,
0.04414956644177437,
-0.09375058114528656,
-0.18432219326496124,
-0.15961645543575287,
0.03759992495179176,
0.060025621205568314,
0.13095876574516296,
-0.057205069810152054,
-0.08483537286520004,
-0.08492398262023926,
-0.07478608191013336,
-0.13140805065631866,
-0.24232175946235657,
-0.030598774552345276,
0.22874866425991058,
0.08656918257474899,
0.08219650387763977,
-0.012482990510761738,
-0.01186054851859808,
0.00526038184762001,
0.02680150233209133,
0.12018456310033798,
-0.13341329991817474,
0.11107480525970459,
0.022198403254151344,
0.044267985969781876,
0.009712530300021172,
0.07929777354001999,
0.03375575691461563,
-0.003218587953597307,
-0.0006439819699153304,
-0.0988350659608841,
-0.2596651017665863,
0.0816885456442833,
-0.01623627357184887,
-0.09960969537496567,
0.014988959766924381,
0.02061903104186058,
-0.2089255303144455,
0.011128270998597145,
-0.019883770495653152,
-0.03150356933474541,
-0.06483490765094757,
-0.10664787143468857,
-0.056551624089479446,
0.04928823933005333,
0.10853826254606247,
0.011660109274089336,
0.05354316532611847,
-0.0404130220413208,
0.07917837053537369,
0.0826287642121315,
0.15132710337638855,
0.06795957684516907,
-0.190711110830307,
-0.10953907668590546,
-0.0414445661008358,
0.12121522426605225,
-0.12505418062210083,
0.036917757242918015,
0.053161121904850006,
-0.016534561291337013,
0.14621229469776154,
0.1070784479379654,
-0.07452095299959183,
0.11915595084428787,
0.08904775977134705,
-0.04094788804650307,
-0.23367151618003845,
-0.07120766490697861,
0.11133213341236115,
0.07195597887039185,
-0.03961895406246185,
0.018120890483260155,
-0.04960581287741661,
-0.013980977237224579,
0.048759616911411285,
-0.0538676381111145,
-0.07230538129806519,
0.004421027842909098,
0.1247575581073761,
0.1029362753033638,
-0.04655474051833153,
0.01296416949480772,
0.037371400743722916,
0.003788623260334134,
0.04730486497282982,
0.0407949760556221,
-0.08269952982664108,
-0.04124005511403084,
0.02782733179628849,
0.37552911043167114,
-0.010165480896830559,
-0.020456433296203613,
0.018555615097284317,
-0.19949445128440857,
0.09135842323303223,
0.13205479085445404,
0.04697350412607193,
0.004247748292982578,
-0.08139242231845856,
0.026877427473664284,
-0.010625290684401989,
0.09936143457889557,
-0.07806670665740967,
-0.05493134260177612,
-0.21631066501140594,
-0.025010565295815468,
0.017490221187472343,
0.24077683687210083,
-0.08458559215068817,
-0.12801732122898102,
-0.20628872513771057,
0.13128381967544556,
-0.11333390325307846,
-0.03695881739258766,
-0.024473199620842934,
0.03926658630371094,
-0.01989821158349514,
0.06291737407445908,
-0.0710630789399147,
0.006373001262545586,
-0.11024709790945053,
0.055267609655857086,
0.04204455390572548,
0.1229788213968277,
0.014207782223820686,
0.02016810141503811,
0.05822525918483734,
-0.01837925612926483,
0.07173580676317215,
-0.06203491613268852,
-0.04550490900874138,
0.14224006235599518,
-0.020255116745829582,
-0.04152837023139,
-0.0483345128595829,
-0.036874305456876755,
0.11981741338968277,
-0.05059147998690605,
-0.007141099311411381,
-0.054929375648498535,
-0.06906463205814362,
0.03462086617946625,
-0.009175732731819153,
-0.008798843249678612,
0.06801853328943253,
0.04024988040328026,
-0.026994358748197556,
0.005263668950647116,
0.03447828069329262,
-0.10330043733119965,
-0.04955084249377251,
0.16955432295799255,
-0.0749620869755745,
0.10274054110050201,
-0.031069839373230934,
0.018015999346971512,
0.005847334861755371,
-0.022399673238396645,
-0.015360680408775806,
-0.1457086056470871,
-0.06137600541114807,
-0.09489979594945908,
0.11565322428941727,
0.08146517723798752,
0.03358805552124977,
0.04274565726518631,
0.019532648846507072,
-0.04414922371506691,
-0.038583990186452866,
0.12961317598819733,
0.08133101463317871,
0.012996876612305641,
0.01137041300535202,
0.01941833831369877,
-0.020302120596170425,
0.0028480992186814547,
-0.01250747125595808,
-0.07239153981208801,
-0.05874783173203468,
0.09400010108947754,
0.1600283533334732,
-0.06127211079001427,
-0.13325586915016174,
-0.020593497902154922,
0.04988488554954529,
0.0014717020094394684,
-0.08777432143688202,
0.04833676666021347,
0.15805292129516602,
-0.05623878911137581,
0.03216489031910896,
-0.09984751045703888,
-0.07263360917568207,
-0.16060975193977356,
-0.10029061883687973,
-0.06092562898993492,
-0.28350353240966797,
0.09752398729324341,
0.006392303854227066,
-0.014731393195688725,
0.059529416263103485,
0.051305368542671204,
-0.052508849650621414,
0.07068239152431488,
-0.18146829307079315,
-0.007054794579744339,
0.03497592359781265,
-0.13212306797504425,
0.02475893869996071,
-0.2378365397453308,
0.10198072344064713,
-0.04623803123831749,
-0.1519704908132553,
-0.04004510119557381,
0.0641569048166275,
-0.09540136158466339,
-0.01822364516556263,
-0.0475153923034668,
-0.01922670193016529,
0.01624443754553795,
-0.009348669089376926,
-0.031147832050919533,
0.13716529309749603,
0.02827494591474533,
-0.03268734738230705,
0.005254602525383234,
0.0223685409873724,
0.03955082967877388,
-0.0969657450914383,
-0.05986930429935455,
0.08311155438423157,
-0.031056145206093788,
0.14728976786136627,
0.000341245875461027,
0.04181376099586487,
-0.06758682429790497,
0.2593761384487152,
0.2023983597755432,
-0.12479214370250702,
0.008118697442114353,
-0.021801479160785675,
0.012670028023421764,
-0.041751839220523834,
0.13110700249671936,
0.013386172242462635,
0.12186761200428009,
-0.17513342201709747,
-0.01036517322063446,
-0.0818324014544487,
-0.04501292482018471,
0.06702108681201935,
0.14714950323104858,
0.15742522478103638,
0.03436789661645889,
-0.07328428328037262,
0.06722653657197952,
-0.30119743943214417,
0.20540550351142883,
-0.1346001923084259,
-0.01498429011553526,
-0.040251150727272034,
-0.058389630168676376,
0.061147745698690414,
0.11309876292943954,
0.10832664370536804,
-0.021150551736354828,
-0.0905047357082367,
-0.04486766457557678,
-0.039378076791763306,
-0.13019338250160217,
-0.02718670479953289,
0.1654091775417328,
0.06799814850091934,
0.31520840525627136,
-0.017577875405550003,
0.07702425122261047,
0.034410297870635986,
0.06451138854026794,
0.004519328009337187,
0.09537279605865479,
0.07960964739322662,
-0.06345855444669724,
-0.07373003661632538,
-0.001637450186535716,
0.05033271387219429,
0.14567798376083374,
-0.03826142102479935,
-0.18691548705101013,
0.15858715772628784,
0.07192251086235046,
-0.13762691617012024,
-0.05777517706155777,
0.08409425616264343,
-0.0739973932504654,
0.0550808347761631,
0.08115427941083908,
0.015876613557338715,
-0.017793258652091026,
-0.004664506763219833,
0.06074233725667,
0.024694660678505898,
-0.02343848906457424,
0.003570882137864828,
-0.08337053656578064,
-0.04151543974876404,
0.07267895340919495,
-0.0844460055232048,
-0.20546193420886993,
-0.0957019031047821,
-0.07551700621843338,
0.030557552352547646,
-0.0649830624461174,
0.12575586140155792,
0.1717868149280548,
0.0593598335981369,
-0.03307248651981354,
-0.10721943527460098,
-0.035562749952077866,
0.07602505385875702,
-0.044773899018764496,
-0.09409699589014053
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# codet5p-220m-v22
This model is a fine-tuned version of [Salesforce/codet5p-220m](https://huggingface.co/Salesforce/codet5p-220m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1831
- Bleu Score: 0.0066
- Gen Len: 14.4788
## Model description
trained,
- on: chathuranga-jayanath/context-5-finmath-times4j-html-mavendoxia-wro4j-guava-supercsv-len-1000-prompt-1
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 15
- eval_batch_size: 15
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:-------:|
| No log | 1.0 | 341 | 0.1993 | 0.0066 | 14.427 |
| 0.3405 | 2.0 | 682 | 0.1814 | 0.0066 | 14.4741 |
| 0.117 | 3.0 | 1023 | 0.1831 | 0.0066 | 14.4788 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "base_model": "Salesforce/codet5p-220m", "model-index": [{"name": "codet5p-220m-v22", "results": []}]} | text2text-generation | chathuranga-jayanath/codet5p-220m-v22 | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:Salesforce/codet5p-220m",
"license:bsd-3-clause",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T05:43:39+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-Salesforce/codet5p-220m #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| codet5p-220m-v22
================
This model is a fine-tuned version of Salesforce/codet5p-220m on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1831
* Bleu Score: 0.0066
* Gen Len: 14.4788
Model description
-----------------
trained,
* on: chathuranga-jayanath/context-5-finmath-times4j-html-mavendoxia-wro4j-guava-supercsv-len-1000-prompt-1
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 2e-05
* train\_batch\_size: 15
* eval\_batch\_size: 15
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.38.0.dev0
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 15\n* eval\\_batch\\_size: 15\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-Salesforce/codet5p-220m #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 15\n* eval\\_batch\\_size: 15\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
86,
113,
4,
38
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-Salesforce/codet5p-220m #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 15\n* eval\\_batch\\_size: 15\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.13817013800144196,
0.1340845376253128,
-0.002436137292534113,
0.08794578164815903,
0.13089212775230408,
0.021085219457745552,
0.156755730509758,
0.1151466891169548,
-0.07071688771247864,
0.08030302077531815,
0.13427598774433136,
0.1095782220363617,
0.057040147483348846,
0.1884949505329132,
-0.06157611683011055,
-0.1996937394142151,
0.035606902092695236,
0.048088252544403076,
-0.05126730352640152,
0.14501063525676727,
0.0911041647195816,
-0.12246222048997879,
0.07300262898206711,
0.003074042731896043,
-0.17303155362606049,
-0.04393733665347099,
0.0077152252197265625,
-0.060941968113183975,
0.12203802168369293,
0.030594630166888237,
0.13566097617149353,
0.06310729682445526,
0.08071005344390869,
-0.15352597832679749,
0.013233307749032974,
0.05862904712557793,
-0.007201255299150944,
0.09858352690935135,
0.07002287358045578,
0.009848874993622303,
0.0626421645283699,
-0.07626455277204514,
0.05426933243870735,
0.015049370005726814,
-0.11492757499217987,
-0.18329159915447235,
-0.1013702005147934,
0.09848765283823013,
0.07997222989797592,
0.08122128248214722,
-0.0008465058635920286,
0.11083470284938812,
-0.03306781128048897,
0.08993041515350342,
0.20318719744682312,
-0.2969386577606201,
-0.05378171429038048,
-0.009942270815372467,
0.04244193062186241,
0.08002305030822754,
-0.07904220372438431,
-0.04652409628033638,
0.03979869559407234,
0.03674732893705368,
0.13552366197109222,
0.002957004588097334,
-0.008168235421180725,
-0.028866972774267197,
-0.14609697461128235,
-0.09040863066911697,
0.13179773092269897,
0.04057096689939499,
-0.046377021819353104,
-0.07196716219186783,
-0.08101518452167511,
-0.19626769423484802,
-0.020919332280755043,
0.0040512545965611935,
0.007303452584892511,
-0.0314662866294384,
-0.059612005949020386,
-0.014874662272632122,
-0.10297883301973343,
-0.07524170726537704,
-0.023345595225691795,
0.13777953386306763,
0.053325287997722626,
0.009601948782801628,
-0.006480353884398937,
0.11150077730417252,
0.0465686172246933,
-0.15271461009979248,
0.005375328473746777,
0.009492308832705021,
0.0020525516010820866,
-0.014713450334966183,
-0.033094026148319244,
-0.05779668688774109,
0.014671189710497856,
0.10344018042087555,
-0.08894968032836914,
0.02677721343934536,
0.010906411334872246,
0.040924008935689926,
-0.10414917767047882,
0.15053126215934753,
-0.05140473321080208,
-0.0042169056832790375,
0.038570526987314224,
0.1334797739982605,
0.051351148635149,
-0.022601312026381493,
-0.10847271233797073,
-0.02125660702586174,
0.15438741445541382,
0.033922694623470306,
-0.01853981241583824,
0.05159575119614601,
-0.07388348877429962,
-0.029367772862315178,
0.10231391340494156,
-0.0983511283993721,
-0.004706153646111488,
0.019181624054908752,
-0.04198889806866646,
-0.04754728823900223,
0.04318754002451897,
-0.007527508307248354,
-0.035959772765636444,
0.0717344656586647,
-0.08579707890748978,
-0.019045645371079445,
-0.07936901599168777,
-0.12101251631975174,
0.028335094451904297,
-0.0901111289858818,
-0.011592521332204342,
-0.11044954508543015,
-0.17089936137199402,
-0.02874959073960781,
0.007642604876309633,
-0.017109131440520287,
-0.08278599381446838,
-0.0439811646938324,
-0.09162377566099167,
0.027552947402000427,
-0.034027621150016785,
0.08033933490514755,
-0.05007682740688324,
0.13383257389068604,
0.024912940338253975,
0.05181299149990082,
-0.028057802468538284,
0.050133343786001205,
-0.07366211712360382,
0.0527447871863842,
-0.12741908431053162,
0.0615253783762455,
-0.05181216076016426,
0.031970687210559845,
-0.09093045443296432,
-0.10765275359153748,
0.00958961434662342,
-0.0251319482922554,
0.10301969200372696,
0.11303594708442688,
-0.14342692494392395,
-0.06008244678378105,
0.20284830033779144,
-0.11389442533254623,
-0.13018374145030975,
0.11434370279312134,
-0.02538423053920269,
-0.012635480612516403,
0.04052038863301277,
0.1401520073413849,
0.10369621962308884,
-0.0694882869720459,
-0.01829942874610424,
-0.019448401406407356,
0.07264752686023712,
-0.08735969662666321,
0.10612422227859497,
-0.0006521664327010512,
-0.012143968604505062,
0.011608021333813667,
-0.07834497839212418,
0.05643675848841667,
-0.09314209222793579,
-0.07866022735834122,
-0.036461614072322845,
-0.08192969113588333,
0.07289085537195206,
0.04848445951938629,
0.04175180569291115,
-0.08268028497695923,
-0.10891593247652054,
0.04257497563958168,
0.09819907695055008,
-0.10013964027166367,
0.011053277179598808,
-0.07526112347841263,
0.12444154173135757,
-0.09988631308078766,
-0.01839841529726982,
-0.17603906989097595,
-0.0715273842215538,
0.03292419761419296,
-0.02996809408068657,
-0.010177969001233578,
-0.02084093727171421,
0.05957098305225372,
0.09322673082351685,
-0.03638196364045143,
-0.0720992460846901,
-0.07151869684457779,
-0.006540488917380571,
-0.10162797570228577,
-0.1833498179912567,
-0.0659455955028534,
-0.023497574031352997,
0.16856743395328522,
-0.1949644237756729,
0.04050780460238457,
0.018366238102316856,
0.1031557247042656,
0.01741713099181652,
-0.030232038348913193,
-0.011705457232892513,
0.0809197947382927,
-0.03414720669388771,
-0.06398797035217285,
0.07350807636976242,
0.0346452072262764,
-0.09732047468423843,
0.0339738167822361,
-0.1510499268770218,
0.1487603634595871,
0.11981209367513657,
0.010435475036501884,
-0.06762875616550446,
-0.01873883605003357,
-0.064838707447052,
-0.03880820423364639,
-0.018739819526672363,
-0.008709115907549858,
0.12250842154026031,
0.02257273532450199,
0.15438535809516907,
-0.09841567277908325,
-0.04451402649283409,
0.03186994418501854,
-0.0033491910435259342,
0.003595412243157625,
0.11212767660617828,
0.06571557372808456,
-0.09069497138261795,
0.1473689079284668,
0.12969541549682617,
-0.055586077272892,
0.12312699109315872,
-0.061143841594457626,
-0.08182626217603683,
-0.02660929597914219,
0.038397546857595444,
0.0314963236451149,
0.10041458904743195,
-0.08716318011283875,
0.005734212230890989,
0.039848443120718,
-0.0029337862506508827,
0.022183334454894066,
-0.22066791355609894,
-0.011306262575089931,
0.031000811606645584,
-0.06740869581699371,
-0.015517502091825008,
-0.005272195674479008,
0.014112301170825958,
0.09987158328294754,
0.006655449513345957,
-0.048689618706703186,
0.043765272945165634,
0.0005355358589440584,
-0.09288861602544785,
0.20489726960659027,
-0.0775928944349289,
-0.18612319231033325,
-0.16168199479579926,
0.006846515461802483,
-0.043296393007040024,
0.00479649705812335,
0.04524514451622963,
-0.04178847372531891,
-0.04058833420276642,
-0.09001801162958145,
-0.00986923836171627,
0.020177802070975304,
0.02525685541331768,
0.021730788052082062,
-0.014657104387879372,
0.0705665573477745,
-0.10562730580568314,
-0.005806750152260065,
-0.009156053885817528,
-0.03661409020423889,
0.05376778915524483,
0.028895126655697823,
0.1093904972076416,
0.1482575535774231,
-0.02440309338271618,
0.003804659703746438,
-0.032049257308244705,
0.19941158592700958,
-0.05096587911248207,
-0.03285146504640579,
0.15224288403987885,
-0.02973923087120056,
0.07613921165466309,
0.14126549661159515,
0.031182872131466866,
-0.06691235303878784,
0.005351791623979807,
-0.014032810926437378,
-0.031025657430291176,
-0.23527838289737701,
-0.04727789759635925,
-0.05015780031681061,
-0.009247668087482452,
0.10483036190271378,
0.02544335089623928,
0.011080064810812473,
0.07167394459247589,
-0.024827996268868446,
0.06900233775377274,
-0.012547971680760384,
0.08177752047777176,
0.12106040120124817,
0.05407186225056648,
0.13526585698127747,
-0.03796171769499779,
-0.03031342662870884,
0.032749075442552567,
-0.005721605848520994,
0.21944716572761536,
-0.05965622887015343,
0.204241082072258,
0.05609114095568657,
0.19066952168941498,
0.04253256693482399,
0.0919189304113388,
-0.004469532985240221,
0.01269987691193819,
0.0022157502826303244,
-0.0490056537091732,
-0.08262321352958679,
0.0007643277058377862,
-0.041105326265096664,
0.05801159888505936,
-0.12291339784860611,
0.02335808239877224,
0.007260491140186787,
0.2761099338531494,
0.05340450257062912,
-0.3771504759788513,
-0.1113659143447876,
-0.006328204646706581,
-0.010027200914919376,
-0.05451264977455139,
-0.0017061429098248482,
0.13651339709758759,
-0.0853947177529335,
0.02816305309534073,
-0.0815192461013794,
0.08119155466556549,
-0.07184582203626633,
0.003162594512104988,
0.05207091569900513,
0.08075539022684097,
0.008473880589008331,
0.06356548517942429,
-0.24585159122943878,
0.25855788588523865,
-0.003785523120313883,
0.05928806588053703,
-0.053675197064876556,
0.010818847455084324,
0.00849918369203806,
0.024024441838264465,
0.06709374487400055,
-0.012079604901373386,
-0.009113188832998276,
-0.18840967118740082,
-0.130447655916214,
0.013984762132167816,
0.07725654542446136,
-0.03526386246085167,
0.12088940292596817,
-0.03539581969380379,
-0.0036718309856951237,
0.03927183896303177,
-0.025415845215320587,
-0.04963170364499092,
-0.09921935945749283,
0.03454801067709923,
0.011286209337413311,
0.03912663832306862,
-0.10321364551782608,
-0.12880359590053558,
-0.06209909915924072,
0.14822286367416382,
-0.08749973028898239,
-0.08070284873247147,
-0.1127789095044136,
0.07415351271629333,
0.10078989714384079,
-0.10002375394105911,
0.058109838515520096,
-0.011929302476346493,
0.13532079756259918,
0.0025110668502748013,
-0.0595705546438694,
0.06864704191684723,
-0.06040845066308975,
-0.22036202251911163,
-0.04294813796877861,
0.152887225151062,
0.003766177222132683,
0.049150433391332626,
-0.006788444239646196,
0.014817150309681892,
-0.019303197041153908,
-0.08159355819225311,
0.0007365175988525152,
0.037220899015665054,
0.07189353555440903,
0.012765852734446526,
-0.027709027752280235,
-0.025660667568445206,
-0.047338131815195084,
-0.027621321380138397,
0.1604936420917511,
0.2586601674556732,
-0.08836650103330612,
0.03225191310048103,
0.048664651811122894,
-0.0463695302605629,
-0.19247058033943176,
-0.023880593478679657,
0.10505682229995728,
0.039321418851614,
-0.003211382543668151,
-0.12500306963920593,
0.03363393619656563,
0.07841149717569351,
-0.029023868963122368,
0.08673355728387833,
-0.3015138804912567,
-0.13509535789489746,
0.08319550007581711,
0.1637824922800064,
0.09294761717319489,
-0.1592908352613449,
-0.06492163985967636,
-0.004217396955937147,
-0.1688946783542633,
0.14526274800300598,
-0.05317375436425209,
0.10208729654550552,
-0.03524596989154816,
0.054505329579114914,
0.013163826428353786,
-0.06974375247955322,
0.1268744170665741,
-0.02532617561519146,
0.04710755497217178,
-0.05016250163316727,
0.005061679519712925,
0.08707920461893082,
-0.06437256187200546,
0.027200769633054733,
-0.06350232660770416,
0.060938455164432526,
-0.0967506617307663,
-0.03135091811418533,
-0.09268302470445633,
0.020341290161013603,
-0.0462585873901844,
-0.02970557101070881,
-0.0062153819017112255,
0.024918003007769585,
0.046944547444581985,
-0.015338539145886898,
0.11186506599187851,
0.026253530755639076,
0.13606467843055725,
0.14145973324775696,
0.08136428892612457,
-0.01332157850265503,
-0.03839849308133125,
-0.039010923355817795,
-0.03838071599602699,
0.04979245737195015,
-0.11399573087692261,
0.022847045212984085,
0.1334877461194992,
0.029070882126688957,
0.13059329986572266,
0.06178433448076248,
-0.05455152317881584,
0.017719091847538948,
0.07099249958992004,
-0.16275306046009064,
-0.13143540918827057,
-0.01795598305761814,
0.003337729722261429,
-0.1464150995016098,
0.02932007983326912,
0.1228792667388916,
-0.06968381255865097,
-0.02580871619284153,
-0.009162608534097672,
0.006578340660780668,
-0.01212409045547247,
0.17938655614852905,
0.06454893201589584,
0.0733652263879776,
-0.09832535684108734,
0.061546601355075836,
0.06483390927314758,
-0.10383722186088562,
0.01582547277212143,
0.05781358480453491,
-0.1109708696603775,
-0.029032303020358086,
0.04011394456028938,
0.12308702617883682,
-0.043028779327869415,
-0.058991070836782455,
-0.12871690094470978,
-0.12375731021165848,
0.078346848487854,
0.15035448968410492,
0.06770353019237518,
0.05677194893360138,
-0.0038147608283907175,
-0.005632549058645964,
-0.11531254649162292,
0.11642667651176453,
0.061776112765073776,
0.08674874901771545,
-0.13993802666664124,
0.15464025735855103,
0.000007241719231387833,
0.043855875730514526,
-0.013131747022271156,
0.038671720772981644,
-0.09160381555557251,
-0.01912897825241089,
-0.1309206336736679,
0.035433344542980194,
-0.04265296831727028,
-0.005137250293046236,
-0.020434921607375145,
-0.05091683194041252,
-0.04430125653743744,
0.032343342900276184,
-0.08792051672935486,
-0.048834770917892456,
-0.001729518291540444,
0.042336054146289825,
-0.12226737290620804,
-0.02526557445526123,
0.020425623282790184,
-0.09417952597141266,
0.09378136694431305,
0.03685295581817627,
0.028218498453497887,
0.03160644322633743,
-0.06615416705608368,
0.01664777286350727,
0.04525782912969589,
0.01638859324157238,
0.036673370748758316,
-0.10820110142230988,
0.011063155718147755,
0.008688396774232388,
-0.013409464620053768,
0.009221706539392471,
0.09418460726737976,
-0.13006603717803955,
-0.004435230046510696,
-0.009007683955132961,
-0.01273059006780386,
-0.07434383779764175,
0.05375179648399353,
0.0646369680762291,
0.03317141905426979,
0.17918629944324493,
-0.08619310706853867,
0.03559776023030281,
-0.21651756763458252,
-0.0049232072196900845,
-0.019280405715107918,
-0.09030149132013321,
-0.11393540352582932,
-0.03713386505842209,
0.07061479240655899,
-0.040587738156318665,
0.08216632157564163,
-0.03495975211262703,
0.059301603585481644,
0.01638522371649742,
-0.00920852180570364,
0.02296356111764908,
0.028713487088680267,
0.20589904487133026,
0.013000067323446274,
-0.035735491663217545,
0.04536953195929527,
0.005293351598083973,
0.0652744323015213,
0.05559707060456276,
0.16657395660877228,
0.14548726379871368,
0.017668256536126137,
0.07881791889667511,
0.05787524953484535,
-0.039248812943696976,
-0.15302158892154694,
0.03172086551785469,
-0.04838399961590767,
0.0944218710064888,
-0.0014739524340257049,
0.2282247096300125,
0.0927383080124855,
-0.1729506254196167,
0.01884285733103752,
-0.016345474869012833,
-0.08046908676624298,
-0.08180700242519379,
-0.07916534692049026,
-0.0861712172627449,
-0.12315161526203156,
0.0018545679049566388,
-0.11769407242536545,
0.0018925246549770236,
0.09806881844997406,
0.012456439435482025,
-0.01707758940756321,
0.13884995877742767,
0.07147512584924698,
0.0009328175219707191,
0.050274476408958435,
0.020333847030997276,
0.008715378120541573,
-0.05284273624420166,
-0.09561122953891754,
0.03208184987306595,
0.008877982385456562,
0.06503956764936447,
-0.03158256411552429,
-0.022024327889084816,
0.05005520582199097,
0.006718909367918968,
-0.10991553962230682,
0.019452983513474464,
0.01809319481253624,
0.06553766876459122,
0.08045712858438492,
0.01239604502916336,
0.01967806927859783,
-0.011840321123600006,
0.17838968336582184,
-0.04769573733210564,
-0.08273526281118393,
-0.10279514640569687,
0.18252606689929962,
0.017418963834643364,
-0.03689552843570709,
0.06703808903694153,
-0.07867202162742615,
0.01883125491440296,
0.1727457344532013,
0.136507049202919,
-0.05672807618975639,
-0.0015406495658680797,
0.017478516325354576,
-0.011373534798622131,
-0.022498246282339096,
0.11276348680257797,
0.11462873965501785,
0.08515315502882004,
-0.08125177025794983,
-0.04042956605553627,
-0.05896967276930809,
0.009467950090765953,
-0.02229127660393715,
0.0477607287466526,
-0.009678364731371403,
-0.008343844674527645,
-0.03933829814195633,
0.03900953009724617,
-0.03472696244716644,
-0.0968388244509697,
0.030199173837900162,
-0.20077525079250336,
-0.17117908596992493,
-0.029014762490987778,
0.07662872225046158,
-0.009465612471103668,
0.03950132429599762,
-0.011897108517587185,
0.018028365448117256,
0.1146940067410469,
-0.027860280126333237,
-0.06858153641223907,
-0.02376333624124527,
0.059581492096185684,
-0.07646768540143967,
0.1840064525604248,
-0.032643768936395645,
0.07105915993452072,
0.12346643209457397,
0.060517530888319016,
-0.12436340749263763,
0.06462356448173523,
0.05489373579621315,
-0.04747696965932846,
0.05086003243923187,
0.11400395631790161,
-0.02672610804438591,
0.050163738429546356,
0.03728538379073143,
-0.12983743846416473,
-0.0033704140223562717,
-0.05433949828147888,
-0.04048134759068489,
-0.04662461578845978,
-0.029126061126589775,
-0.041026338934898376,
0.1410190761089325,
0.18131999671459198,
-0.05594772472977638,
-0.016739577054977417,
-0.05140336975455284,
0.010728535242378712,
0.053161244839429855,
0.09519433975219727,
-0.004698785953223705,
-0.23947562277317047,
0.008131957612931728,
0.03217427432537079,
0.019089121371507645,
-0.28520041704177856,
-0.0748307928442955,
-0.017914919182658195,
-0.06062142550945282,
-0.11926553398370743,
0.10574068129062653,
0.05681810900568962,
0.054044365882873535,
-0.046874161809682846,
0.0008691250113770366,
-0.08729357272386551,
0.16076433658599854,
-0.1513483226299286,
-0.09183012694120407
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | text-generation | nchen909/llama1_13b_sft_20710 | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T05:44:48+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
56,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.06061961501836777,
0.15481999516487122,
-0.004844071343541145,
0.02074851468205452,
0.0983177199959755,
0.007407687604427338,
0.07119518518447876,
0.11185134947299957,
-0.023851769044995308,
0.1167980208992958,
0.031993988901376724,
0.09781743586063385,
0.11217817664146423,
0.16186554729938507,
0.0015333457849919796,
-0.22897611558437347,
0.049678247421979904,
-0.125278040766716,
-0.0294334813952446,
0.11977242678403854,
0.1422213912010193,
-0.10954539477825165,
0.0752737894654274,
-0.038042325526475906,
-0.005828251596540213,
-0.0323176346719265,
-0.06205610930919647,
-0.05266609415411949,
0.05311284959316254,
0.06794639676809311,
0.07308239489793777,
0.01171939354389906,
0.09106900542974472,
-0.2724283039569855,
0.02348201349377632,
0.0805930644273758,
-0.0006441773730330169,
0.07586129754781723,
0.04993962123990059,
-0.08749990910291672,
0.07524524629116058,
-0.060156844556331635,
0.1498761922121048,
0.07955671846866608,
-0.09018243104219437,
-0.19217631220817566,
-0.07921334356069565,
0.09916994720697403,
0.1890910118818283,
0.05953684076666832,
-0.026427440345287323,
0.11642678081989288,
-0.08593545109033585,
0.013638701289892197,
0.06446459144353867,
-0.06054406240582466,
-0.055855002254247665,
0.06904532760381699,
0.08335285633802414,
0.08567540347576141,
-0.12976622581481934,
-0.010767064057290554,
0.015032444149255753,
0.008952446281909943,
0.08948688954114914,
0.017146794125437737,
0.1335189938545227,
0.040557652711868286,
-0.13501930236816406,
-0.043155476450920105,
0.09761431813240051,
0.03665134683251381,
-0.04888195917010307,
-0.2485782504081726,
-0.023432478308677673,
-0.04339504987001419,
-0.03198111802339554,
-0.03649339824914932,
0.043764639645814896,
-0.014506848528981209,
0.07738617807626724,
-0.004502781666815281,
-0.0837155357003212,
-0.04301247000694275,
0.07241875678300858,
0.06128999963402748,
0.02571401372551918,
-0.015821760520339012,
0.0059297760017216206,
0.12327717989683151,
0.11431120336055756,
-0.126715749502182,
-0.052547648549079895,
-0.06306339055299759,
-0.08449548482894897,
-0.044861067086458206,
0.030838407576084137,
0.037995077669620514,
0.045936476439237595,
0.23867325484752655,
0.007765117567032576,
0.053257301449775696,
0.04455438256263733,
0.014407169073820114,
0.06501194834709167,
0.11008983850479126,
-0.05894824117422104,
-0.09719445556402206,
-0.028582042083144188,
0.10156717151403427,
0.007986726239323616,
-0.04139331728219986,
-0.05712985619902611,
0.07059531658887863,
0.018587570637464523,
0.12360043078660965,
0.08000938594341278,
0.003056557849049568,
-0.0755772516131401,
-0.062465377151966095,
0.17764076590538025,
-0.15825673937797546,
0.04532013460993767,
0.03055616281926632,
-0.0341108962893486,
-0.009745313785970211,
0.012105142697691917,
0.025474950671195984,
-0.021481726318597794,
0.09522198140621185,
-0.05601342022418976,
-0.034448131918907166,
-0.11389608681201935,
-0.03694311901926994,
0.030394554138183594,
0.011153047904372215,
-0.02865210548043251,
-0.03502652049064636,
-0.08865131437778473,
-0.06405586749315262,
0.09101516753435135,
-0.07148737460374832,
-0.04784895107150078,
-0.016645915806293488,
-0.07833752781152725,
0.021804187446832657,
0.01691517047584057,
0.09064167737960815,
-0.0222476739436388,
0.03985358029603958,
-0.0550384595990181,
0.061440225690603256,
0.11723454296588898,
0.027987057343125343,
-0.05787884071469307,
0.061519939452409744,
-0.2424532175064087,
0.10252492874860764,
-0.07715212553739548,
0.04971238598227501,
-0.15203025937080383,
-0.02478341944515705,
0.03986154496669769,
0.01284773275256157,
-0.008251311257481575,
0.14196595549583435,
-0.21994100511074066,
-0.030957341194152832,
0.16964265704154968,
-0.10025953501462936,
-0.08109250664710999,
0.060782887041568756,
-0.05354252830147743,
0.11210215091705322,
0.04557164013385773,
-0.02375967986881733,
0.05775221437215805,
-0.14725260436534882,
-0.011030761525034904,
-0.041942402720451355,
-0.0180682260543108,
0.16207332909107208,
0.0703711211681366,
-0.06047816202044487,
0.07456906884908676,
0.01960151270031929,
-0.014246034435927868,
-0.04887177795171738,
-0.02822130173444748,
-0.1047162413597107,
0.01184528972953558,
-0.06102835759520531,
0.018109694123268127,
-0.021768750622868538,
-0.09445013850927353,
-0.029118487611413002,
-0.17402999103069305,
-0.0031633328180760145,
0.08821269869804382,
-0.011630427092313766,
-0.021509924903512,
-0.11245372891426086,
0.009332616813480854,
0.030967719852924347,
0.0002618339203763753,
-0.13677829504013062,
-0.06033218279480934,
0.026970699429512024,
-0.16097871959209442,
0.029791243374347687,
-0.05741601809859276,
0.04530094936490059,
0.04005871340632439,
-0.03433511033654213,
-0.03489551320672035,
0.010874404571950436,
0.010431389324367046,
-0.01894843392074108,
-0.25422003865242004,
-0.01882786676287651,
-0.0234990194439888,
0.1751047968864441,
-0.22956320643424988,
0.042598169296979904,
0.07489731162786484,
0.1460893303155899,
0.007349682506173849,
-0.03550100699067116,
0.015185600146651268,
-0.07262228429317474,
-0.03268764168024063,
-0.06316669285297394,
-0.01207790058106184,
-0.038400664925575256,
-0.05820201337337494,
0.04906858503818512,
-0.1686294972896576,
-0.030321966856718063,
0.10717973858118057,
0.06342670321464539,
-0.1473218947649002,
-0.02780107781291008,
-0.04056945815682411,
-0.04624456167221069,
-0.06676914542913437,
-0.05461418256163597,
0.11812574416399002,
0.056411582976579666,
0.04860803112387657,
-0.07140495628118515,
-0.07455260306596756,
0.008036690764129162,
-0.01956399530172348,
-0.014917809516191483,
0.09334591031074524,
0.07554110884666443,
-0.12264352291822433,
0.09177418053150177,
0.09668384492397308,
0.08576478064060211,
0.10314212739467621,
-0.014663571491837502,
-0.08914592862129211,
-0.040637146681547165,
0.02245822176337242,
0.016187267377972603,
0.15129362046718597,
-0.012961224652826786,
0.055492039769887924,
0.0358695350587368,
-0.014034898020327091,
0.011105312965810299,
-0.09736533463001251,
0.02655916102230549,
0.030835967510938644,
-0.016302183270454407,
0.03745110332965851,
-0.0447014644742012,
0.019208140671253204,
0.09039704501628876,
0.040895868092775345,
0.040978945791721344,
0.010155045427381992,
-0.04354988783597946,
-0.11037563532590866,
0.1787576973438263,
-0.12389461696147919,
-0.24818050861358643,
-0.13812170922756195,
0.010281167924404144,
0.04737642779946327,
-0.010411068797111511,
0.006690691225230694,
-0.06616118550300598,
-0.1175973042845726,
-0.09878289699554443,
0.018617089837789536,
0.045352302491664886,
-0.07590975612401962,
-0.06842505931854248,
0.06414616107940674,
0.03875524550676346,
-0.13939815759658813,
0.024007495492696762,
0.04662325978279114,
-0.08205481618642807,
-0.0029386086389422417,
0.0791812464594841,
0.06965780258178711,
0.17661017179489136,
0.013885351829230785,
-0.023669935762882233,
0.026634456589818,
0.20819635689258575,
-0.1436755359172821,
0.10975687950849533,
0.13545554876327515,
-0.08767466992139816,
0.08120133727788925,
0.1998777538537979,
0.03777998685836792,
-0.10680917650461197,
0.03608465939760208,
0.028374753892421722,
-0.028325283899903297,
-0.2502254545688629,
-0.06958996504545212,
0.0019060121849179268,
-0.05172049254179001,
0.07064855098724365,
0.08791537582874298,
0.09593888372182846,
0.016860228031873703,
-0.09976044297218323,
-0.07697858661413193,
0.046900223940610886,
0.10824491083621979,
-0.00015424020239152014,
-0.015208319760859013,
0.0904119610786438,
-0.03033481352031231,
0.01743943803012371,
0.09215071052312851,
0.0030607767403125763,
0.17535938322544098,
0.051709048449993134,
0.17189906537532806,
0.07866133749485016,
0.06444311141967773,
0.02004685252904892,
0.007725914940237999,
0.021817529574036598,
0.017227526754140854,
-0.0030957073904573917,
-0.08709781616926193,
-0.0034981227945536375,
0.1202581599354744,
0.049845851957798004,
0.029173865914344788,
0.012042860500514507,
-0.030704669654369354,
0.08337877690792084,
0.1770893782377243,
0.0029054484330117702,
-0.1893385946750641,
-0.07169844210147858,
0.07795937359333038,
-0.08648337423801422,
-0.10729733109474182,
-0.029470939189195633,
0.041069481521844864,
-0.1729043871164322,
0.016882894560694695,
-0.019335895776748657,
0.10788324475288391,
-0.13190391659736633,
-0.01772487722337246,
0.05657728388905525,
0.06932812184095383,
-0.009677323512732983,
0.06694949418306351,
-0.16090403497219086,
0.11770165711641312,
0.01751571334898472,
0.06636732816696167,
-0.09608277678489685,
0.09618937969207764,
-0.007830657996237278,
0.0041499207727611065,
0.1410749852657318,
0.010120149701833725,
-0.05952107161283493,
-0.09608154743909836,
-0.10546442121267319,
-0.009841260500252247,
0.1306990385055542,
-0.14852415025234222,
0.08813067525625229,
-0.02661319263279438,
-0.044553373008966446,
0.003614129964262247,
-0.12497276812791824,
-0.13103094696998596,
-0.18366187810897827,
0.05707118660211563,
-0.12947207689285278,
0.04045100137591362,
-0.10902881622314453,
-0.045833900570869446,
-0.02098964899778366,
0.20040063560009003,
-0.23137451708316803,
-0.06714103370904922,
-0.1551055610179901,
-0.08061286807060242,
0.14446212351322174,
-0.046455029398202896,
0.08550118654966354,
0.0008278203313238919,
0.19068008661270142,
0.021319707855582237,
-0.017237508669495583,
0.1072206199169159,
-0.10052918642759323,
-0.2010865956544876,
-0.09273224323987961,
0.15895552933216095,
0.13766798377037048,
0.03809428587555885,
-0.004381525795906782,
0.03171157464385033,
-0.02098114788532257,
-0.12076930701732635,
0.020226983353495598,
0.17317426204681396,
0.08982043713331223,
0.025265544652938843,
-0.02972041629254818,
-0.11267432570457458,
-0.07061342149972916,
-0.03774050623178482,
0.024755435064435005,
0.18072067201137543,
-0.07222156971693039,
0.18405316770076752,
0.13775517046451569,
-0.05534014105796814,
-0.19904261827468872,
0.021996473893523216,
0.04293542355298996,
0.0070380112156271935,
0.0323902890086174,
-0.20307663083076477,
0.09384101629257202,
0.0008334947633557022,
-0.05131231248378754,
0.1379684954881668,
-0.1823476254940033,
-0.151598259806633,
0.06042521819472313,
0.043563615530729294,
-0.19374065101146698,
-0.12374074012041092,
-0.08848230540752411,
-0.04693066328763962,
-0.15487661957740784,
0.10312657803297043,
0.0020827590487897396,
0.008401188999414444,
0.03778626397252083,
0.02252252586185932,
0.012139533646404743,
-0.04198719933629036,
0.1914343535900116,
-0.025891713798046112,
0.03347287327051163,
-0.0790715217590332,
-0.060851071029901505,
0.062408581376075745,
-0.058187782764434814,
0.0755455270409584,
-0.025226406753063202,
0.015947066247463226,
-0.10598332434892654,
-0.048235729336738586,
-0.02852320298552513,
0.019321219995617867,
-0.09431382268667221,
-0.09348297864198685,
-0.04829427972435951,
0.09367614984512329,
0.09042316675186157,
-0.03652578964829445,
-0.03649144619703293,
-0.078715980052948,
0.038977332413196564,
0.17627815902233124,
0.18159319460391998,
0.04659178853034973,
-0.07959239184856415,
-0.001915142871439457,
-0.014336181804537773,
0.04684065282344818,
-0.22077152132987976,
0.060553863644599915,
0.04557652771472931,
0.016117896884679794,
0.11537692695856094,
-0.0208132341504097,
-0.16198977828025818,
-0.06710557639598846,
0.061360616236925125,
-0.06944561004638672,
-0.17825035750865936,
0.0039279889315366745,
0.07344977557659149,
-0.16578389704227448,
-0.037031736224889755,
0.04200848564505577,
-0.01189455483108759,
-0.0403641052544117,
0.012352054007351398,
0.08063354343175888,
0.007078902795910835,
0.07699975371360779,
0.055281639099121094,
0.09124495089054108,
-0.10227900743484497,
0.07410510629415512,
0.08149529248476028,
-0.08644098788499832,
0.030720343813300133,
0.09573426842689514,
-0.06469762325286865,
-0.0346054881811142,
0.04237886518239975,
0.08354541659355164,
0.024281201884150505,
-0.04682289808988571,
0.0023111123591661453,
-0.09734189510345459,
0.05927345156669617,
0.11483542621135712,
0.03496333956718445,
0.011234734207391739,
0.03813567012548447,
0.04486291855573654,
-0.08093374222517014,
0.11926916986703873,
0.023795632645487785,
0.020354853942990303,
-0.04112942889332771,
-0.040553025901317596,
0.035851649940013885,
-0.026020776480436325,
-0.011440055444836617,
-0.035174157470464706,
-0.0722682997584343,
-0.014069457538425922,
-0.16000694036483765,
-0.0076758842915296555,
-0.03660871088504791,
0.005114538595080376,
0.022510098293423653,
-0.03652830421924591,
0.00792311318218708,
0.012217256240546703,
-0.06868947297334671,
-0.05553458258509636,
-0.023233558982610703,
0.09422210603952408,
-0.16494666039943695,
0.0220257006585598,
0.0823851153254509,
-0.12121747434139252,
0.09289738535881042,
0.016782134771347046,
0.00412249518558383,
0.026962365955114365,
-0.1545863002538681,
0.04763968288898468,
-0.020152103155851364,
0.013473534025251865,
0.04222847521305084,
-0.21637047827243805,
-0.004404853098094463,
-0.04015503451228142,
-0.05566934496164322,
-0.008993052877485752,
-0.0319182425737381,
-0.11338426172733307,
0.09645436704158783,
0.011025024577975273,
-0.08443772792816162,
-0.02965564839541912,
0.03353232145309448,
0.07690354436635971,
-0.027447547763586044,
0.1498211771249771,
-0.004663881380110979,
0.07559948414564133,
-0.17581342160701752,
-0.02282017655670643,
-0.011197620071470737,
0.022367527708411217,
-0.021871577948331833,
-0.01622559316456318,
0.04623444378376007,
-0.02704801969230175,
0.19120801985263824,
-0.024701936170458794,
0.049393873661756516,
0.06364397704601288,
0.009232889860868454,
-0.013832193799316883,
0.11151392012834549,
0.05708572641015053,
0.024334950372576714,
0.022262847051024437,
0.003451440716162324,
-0.04008655622601509,
-0.009981024079024792,
-0.18596695363521576,
0.06803664565086365,
0.14585918188095093,
0.09060460329055786,
-0.012669353745877743,
0.0707244873046875,
-0.10161512345075607,
-0.12005364894866943,
0.10127941519021988,
-0.06415384262800217,
-0.010188822634518147,
-0.06542414426803589,
0.14027701318264008,
0.14953285455703735,
-0.1886233240365982,
0.06583356112241745,
-0.06602055579423904,
-0.0566304549574852,
-0.11457879096269608,
-0.1930263340473175,
-0.057075321674346924,
-0.050602465867996216,
-0.018466074019670486,
-0.05384097993373871,
0.06939727067947388,
0.05750798434019089,
0.01126816775649786,
0.00868057832121849,
0.08568526059389114,
-0.009656033478677273,
0.00248199631460011,
0.030120067298412323,
0.06713981181383133,
0.016768986359238625,
-0.0321255661547184,
0.0179112758487463,
-0.00597198773175478,
0.034156378358602524,
0.059282708913087845,
0.03608176112174988,
-0.028436895459890366,
0.015559280291199684,
-0.034912437200546265,
-0.11309733241796494,
0.042801856994628906,
-0.029640642926096916,
-0.0749855786561966,
0.1347348988056183,
0.026981467381119728,
0.005015076603740454,
-0.023140020668506622,
0.2503887414932251,
-0.07436972856521606,
-0.09334370493888855,
-0.14373961091041565,
0.11701542884111404,
-0.04212593287229538,
0.0635172426700592,
0.03596310690045357,
-0.10810714215040207,
0.017985546961426735,
0.1320217251777649,
0.15442703664302826,
-0.04732590913772583,
0.019251897931098938,
0.028577854856848717,
0.00439635943621397,
-0.04075566306710243,
0.05177190154790878,
0.07100846618413925,
0.14500564336776733,
-0.05157303810119629,
0.08530787378549576,
0.002609728369861841,
-0.1021018698811531,
-0.041973695158958435,
0.11415864527225494,
-0.014296893030405045,
0.017620453611016273,
-0.057136841118335724,
0.124222531914711,
-0.05874236673116684,
-0.23697422444820404,
0.06316976249217987,
-0.0765061303973198,
-0.1432730257511139,
-0.024886758998036385,
0.071670763194561,
-0.016632623970508575,
0.02605951391160488,
0.07167234271764755,
-0.0754380151629448,
0.18880942463874817,
0.03957989811897278,
-0.05233397334814072,
-0.05954399332404137,
0.0744764655828476,
-0.11850855499505997,
0.27879106998443604,
0.010482731275260448,
0.051307905465364456,
0.1042102724313736,
-0.02021743729710579,
-0.13270841538906097,
0.023401619866490364,
0.09579801559448242,
-0.08917027711868286,
0.04087764397263527,
0.21448291838169098,
-0.00629545608535409,
0.11935057491064072,
0.07611140608787537,
-0.07468950748443604,
0.047562725841999054,
-0.11468592286109924,
-0.07639975845813751,
-0.08699081838130951,
0.09244474768638611,
-0.06785612553358078,
0.14258281886577606,
0.12599852681159973,
-0.05530165135860443,
0.011584274470806122,
-0.028389399871230125,
0.045467376708984375,
0.005578654818236828,
0.100032277405262,
0.011115525849163532,
-0.18496567010879517,
0.024811718612909317,
0.016259413212537766,
0.10884406417608261,
-0.18112654983997345,
-0.09105053544044495,
0.046958595514297485,
0.0005061255069449544,
-0.06443515419960022,
0.12483241409063339,
0.057313691824674606,
0.04654949903488159,
-0.0451689288020134,
-0.026830285787582397,
-0.006042256020009518,
0.14264579117298126,
-0.10707559436559677,
-0.005129707511514425
] |
null | null | diffusers | ### My-Pet-Dog named xzg Dreambooth model trained by sj6 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX19932gAS
Sample pictures of this concept:
| {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | text-to-image | sj6/my-pet-dog | [
"diffusers",
"safetensors",
"NxtWave-GenAI-Webinar",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | 2024-02-11T05:45:39+00:00 | [] | [] | TAGS
#diffusers #safetensors #NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
| ### My-Pet-Dog named xzg Dreambooth model trained by sj6 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX19932gAS
Sample pictures of this concept:
!0
| [
"### My-Pet-Dog named xzg Dreambooth model trained by sj6 following the \"Build your own Gen AI model\" session by NxtWave.\n\nProject Submission Code: GoX19932gAS\n\nSample pictures of this concept:\n\n !0"
] | [
"TAGS\n#diffusers #safetensors #NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us \n",
"### My-Pet-Dog named xzg Dreambooth model trained by sj6 following the \"Build your own Gen AI model\" session by NxtWave.\n\nProject Submission Code: GoX19932gAS\n\nSample pictures of this concept:\n\n !0"
] | [
73,
60
] | [
"passage: TAGS\n#diffusers #safetensors #NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us \n### My-Pet-Dog named xzg Dreambooth model trained by sj6 following the \"Build your own Gen AI model\" session by NxtWave.\n\nProject Submission Code: GoX19932gAS\n\nSample pictures of this concept:\n\n !0"
] | [
-0.09905470162630081,
0.15432071685791016,
-0.0018813274800777435,
-0.016953755170106888,
0.09169899672269821,
-0.014527066610753536,
0.1864088773727417,
0.02368113398551941,
0.023486357182264328,
0.01726512983441353,
0.1138320341706276,
0.11711180210113525,
0.01776045374572277,
0.17750920355319977,
-0.007853684946894646,
-0.11134620755910873,
0.04315999895334244,
0.08053060621023178,
0.014734129421412945,
0.042245734483003616,
0.05727648735046387,
-0.08107974380254745,
0.10559976100921631,
-0.009224356152117252,
-0.1719982922077179,
-0.04272021725773811,
-0.04636304825544357,
-0.0329400971531868,
0.048541050404310226,
0.02851725183427334,
0.009429095312952995,
0.09915246814489365,
0.006490052677690983,
-0.00552269397303462,
0.041317813098430634,
0.01701517216861248,
-0.05997397378087044,
0.059809017926454544,
0.06556890159845352,
0.04260235279798508,
0.0901382565498352,
0.015201933681964874,
-0.08736579120159149,
0.029904449358582497,
-0.05981697142124176,
-0.0826246365904808,
0.03994361683726311,
0.13554202020168304,
0.09048748761415482,
0.09124382585287094,
-0.013096369802951813,
0.07461003959178925,
0.042834535241127014,
0.10702258348464966,
0.1707901507616043,
-0.262260764837265,
-0.09288513660430908,
0.20420557260513306,
0.07399240136146545,
0.044443223625421524,
-0.04830650985240936,
0.10081549733877182,
0.09533728659152985,
-0.042682405561208725,
0.01715666987001896,
-0.046761419624090195,
0.0577942356467247,
-0.061357177793979645,
-0.13732920587062836,
0.006105000153183937,
0.2101559042930603,
0.0446619987487793,
-0.05986196920275688,
-0.08278799057006836,
-0.07583584636449814,
0.02073911391198635,
-0.05392071232199669,
-0.015616568736732006,
-0.045685309916734695,
0.009640240110456944,
-0.008358229883015156,
-0.07511928677558899,
-0.1285122036933899,
-0.07298776507377625,
-0.02971109002828598,
0.22078675031661987,
0.014177369885146618,
0.07934035360813141,
-0.13632193207740784,
0.11618956923484802,
-0.014375504106283188,
-0.11258010566234589,
0.027350129559636116,
-0.07789593189954758,
0.02191094122827053,
0.07934469729661942,
0.044307876378297806,
-0.07947663962841034,
0.12714777886867523,
-0.022541407495737076,
0.052385278046131134,
-0.03470468893647194,
0.03286239877343178,
0.08918862044811249,
0.03627210482954979,
-0.030530160292983055,
-0.09068085998296738,
-0.09671592712402344,
0.017489444464445114,
-0.05544691160321236,
-0.004786726087331772,
-0.024485481902956963,
-0.08761554211378098,
0.0003352402418386191,
-0.0409967415034771,
0.034038763493299484,
0.08655465394258499,
0.07322100549936295,
0.0030332047026604414,
-0.0462849922478199,
0.18070721626281738,
0.06181824207305908,
-0.02899206057190895,
-0.020127570256590843,
0.008725153282284737,
0.03594723716378212,
0.023267146199941635,
-0.0012667163973674178,
-0.026667997241020203,
0.034945473074913025,
-0.06790409982204437,
-0.043860726058483124,
-0.03593458980321884,
-0.036201901733875275,
-0.01087469793856144,
-0.14604069292545319,
0.06193825230002403,
-0.18253570795059204,
-0.10986117273569107,
0.044490572065114975,
0.050741955637931824,
-0.0037026156205683947,
-0.08061423152685165,
-0.03605823218822479,
-0.08617832511663437,
0.005151164717972279,
-0.02041533961892128,
0.02752184495329857,
-0.03568816930055618,
0.045593902468681335,
-0.008622660301625729,
0.0684351772069931,
-0.21633245050907135,
0.00045571208465844393,
-0.06218307465314865,
0.002665454987436533,
0.04072458669543266,
-0.0008204085752367973,
-0.03580484166741371,
0.08625364303588867,
0.005513747222721577,
0.016867421567440033,
-0.006428812630474567,
-0.004072252195328474,
0.0036586096975952387,
0.1214621365070343,
-0.07102416455745697,
-0.007788283284753561,
0.1745935082435608,
-0.1301138997077942,
-0.13896822929382324,
0.10374774783849716,
0.06546032428741455,
0.0989302396774292,
0.08280844986438751,
0.1397918313741684,
0.11115650832653046,
-0.22921693325042725,
-0.012997439131140709,
0.004537487402558327,
-0.1495145559310913,
-0.15781156718730927,
0.006722078192979097,
0.11082400381565094,
-0.083562932908535,
0.03839299455285072,
-0.1460711807012558,
0.11381687968969345,
-0.08234109729528427,
-0.01890716701745987,
-0.03827578201889992,
-0.1172371581196785,
0.016310377046465874,
-0.0004638959944713861,
0.038313381373882294,
-0.01956797018647194,
0.0028951684944331646,
-0.17079108953475952,
0.03973725065588951,
0.005682088900357485,
-0.03727490454912186,
-0.10854394733905792,
0.08058760315179825,
-0.08816119283437729,
0.045016512274742126,
-0.010572172701358795,
-0.03441471979022026,
0.044982120394706726,
0.14484980702400208,
0.008546504192054272,
0.16822876036167145,
0.050219565629959106,
0.05595281347632408,
0.0021385441068559885,
-0.09300757199525833,
0.09661733359098434,
0.006744038313627243,
-0.056502100080251694,
-0.14286452531814575,
0.11926261335611343,
-0.06875496357679367,
-0.04487498477101326,
-0.1395207643508911,
0.061440709978342056,
0.014042329974472523,
0.09010312706232071,
0.036031756550073624,
-0.022090135142207146,
0.03643567115068436,
-0.03887534141540527,
-0.0469510555267334,
0.003399278735741973,
0.07693470269441605,
0.06489095091819763,
-0.08603346347808838,
0.1880749762058258,
-0.0961158499121666,
0.18119612336158752,
0.10686973482370377,
0.0035256296396255493,
0.004184429999440908,
0.025801751762628555,
-0.07068951427936554,
0.01065449696034193,
0.01981026493012905,
-0.007367560639977455,
0.02159731648862362,
-0.05265417695045471,
0.08701860904693604,
-0.05468148738145828,
-0.028286471962928772,
0.06534428149461746,
-0.05160050466656685,
-0.0029460936784744263,
0.07912102341651917,
0.028485435992479324,
-0.12633489072322845,
0.1326064020395279,
0.1011742353439331,
0.019876254722476006,
0.22542846202850342,
0.01976790279150009,
0.00453357445076108,
-0.06851907074451447,
0.09135764092206955,
0.015124651603400707,
0.21219460666179657,
-0.1158159002661705,
0.04083970561623573,
0.025131376460194588,
0.0029104759451001883,
0.0639120563864708,
-0.14319661259651184,
-0.06168895214796066,
-0.030824532732367516,
-0.040199752897024155,
0.11571034789085388,
0.0918874442577362,
-0.12648263573646545,
0.09509368985891342,
-0.08003227412700653,
-0.06572956591844559,
0.053877558559179306,
-0.008500904776155949,
-0.06415106356143951,
0.07548584789037704,
-0.05188742280006409,
-0.20265305042266846,
-0.1088600605726242,
-0.06672976911067963,
-0.08558215200901031,
-0.002326267771422863,
0.08007899671792984,
-0.06719309091567993,
-0.0014693188713863492,
-0.02740277722477913,
-0.05949099734425545,
-0.07963448762893677,
0.07638333737850189,
0.07053498178720474,
0.007419064175337553,
-0.020081622526049614,
-0.03951345384120941,
0.003098832443356514,
-0.07341470569372177,
-0.005241548176854849,
0.1280544102191925,
0.039554137736558914,
0.1562986969947815,
0.0700640007853508,
0.012003583833575249,
-0.027753978967666626,
-0.0006863069138489664,
0.22769702970981598,
-0.051076967269182205,
0.05980798602104187,
0.14592045545578003,
0.045072685927152634,
0.06886858493089676,
0.12594352662563324,
0.024553894996643066,
-0.08457604050636292,
0.029791438952088356,
-0.05771717056632042,
-0.11303380131721497,
-0.1350129246711731,
-0.059772782027721405,
-0.06923149526119232,
0.15030480921268463,
-0.014790957793593407,
0.09516160935163498,
0.11941628903150558,
0.16328290104866028,
-0.008953128010034561,
-0.04061231389641762,
-0.03546310216188431,
0.08719731122255325,
-0.06540245562791824,
-0.05128215253353119,
0.03565511852502823,
-0.06878314167261124,
-0.041237205266952515,
0.08580437302589417,
0.061338383704423904,
0.14719802141189575,
0.03624895587563515,
-0.00287670292891562,
0.09558967500925064,
0.11551062017679214,
0.12174926698207855,
0.09339923411607742,
-0.03411033749580383,
-0.07132702320814133,
-0.00966983288526535,
-0.08069509267807007,
0.09116003662347794,
0.056725893169641495,
-0.05591711029410362,
-0.03822461888194084,
0.05394008383154869,
0.021986672654747963,
-0.0014808856649324298,
0.111414335668087,
0.02686135098338127,
-0.19930927455425262,
0.013174341060221195,
0.003698306391015649,
0.04814966768026352,
-0.05257517471909523,
-0.0092725595459342,
0.2389068305492401,
-0.02630470134317875,
0.07054194062948227,
-0.02205941081047058,
0.06213846802711487,
0.034909963607788086,
0.015413079410791397,
-0.09509395807981491,
0.027717579156160355,
-0.01251730602234602,
0.04962186887860298,
-0.24812878668308258,
0.12648726999759674,
-0.009552915580570698,
0.07410715520381927,
-0.02210710570216179,
-0.016488078981637955,
-0.03304996341466904,
0.1414407640695572,
0.16573843359947205,
0.01321819145232439,
-0.04724228382110596,
-0.011563199572265148,
-0.10208750516176224,
0.03203698992729187,
0.021818511188030243,
-0.007451264653354883,
0.02441018633544445,
0.07703640311956406,
-0.011629614979028702,
-0.017175333574414253,
0.035548143088817596,
-0.17727333307266235,
-0.09953533113002777,
0.005929080303758383,
0.23592373728752136,
0.09500349313020706,
-0.03900957852602005,
0.03601604700088501,
-0.06173980236053467,
0.11273719370365143,
-0.24737222492694855,
-0.08797136694192886,
-0.07753346115350723,
-0.061850178986787796,
-0.05642806366086006,
-0.048971280455589294,
-0.011689416132867336,
-0.06820365786552429,
0.06869710236787796,
-0.05967369303107262,
-0.12977686524391174,
0.003777960315346718,
-0.18067540228366852,
-0.14062997698783875,
-0.11083962023258209,
0.042628951370716095,
0.06564287841320038,
0.0011039238888770342,
0.0023204644676297903,
-0.07929325103759766,
-0.04463697597384453,
-0.10068532824516296,
0.06077028438448906,
0.11344468593597412,
-0.07536426186561584,
-0.05531395226716995,
-0.06320278346538544,
-0.15667074918746948,
-0.04163495823740959,
-0.08264598250389099,
0.08482780307531357,
0.22342807054519653,
-0.05970299243927002,
0.08898099511861801,
0.2116217464208603,
-0.06852244585752487,
-0.22905240952968597,
-0.11058267205953598,
-0.01781739667057991,
-0.013471062295138836,
-0.042006656527519226,
-0.12406577169895172,
0.13060329854488373,
0.03844691440463066,
-0.054340727627277374,
0.22408293187618256,
-0.24097712337970734,
-0.062127530574798584,
0.020075608044862747,
0.14647315442562103,
0.3359638750553131,
-0.1688724309206009,
-0.040256012231111526,
0.03617124259471893,
-0.12074946612119675,
0.21195702254772186,
0.00025230515166185796,
0.06719500571489334,
-0.04173005372285843,
-0.013047900050878525,
-0.005606882739812136,
-0.04459446296095848,
0.10694649070501328,
-0.03514831140637398,
0.026848291978240013,
-0.0707554742693901,
0.04924161732196808,
0.15470705926418304,
-0.004142519552260637,
0.02243104949593544,
-0.13656798005104065,
0.007135263178497553,
-0.10972810536623001,
-0.004909795243293047,
-0.059129513800144196,
0.002229408361017704,
-0.024191446602344513,
-0.12469855695962906,
-0.05558537691831589,
-0.009405349381268024,
0.006067667156457901,
0.019186777994036674,
-0.022889934480190277,
-0.01764427125453949,
0.010956126265227795,
0.1343582719564438,
0.00016155469347722828,
-0.08328896760940552,
-0.043836116790771484,
-0.09866592288017273,
-0.04454736039042473,
0.14776037633419037,
-0.032119765877723694,
-0.031105341389775276,
0.0964280366897583,
0.0039468081668019295,
0.03395837917923927,
0.030344566330313683,
-0.0644373968243599,
0.041225384920835495,
0.11352148652076721,
-0.17278490960597992,
-0.14437465369701385,
-0.03347927704453468,
0.1534440964460373,
0.08650689572095871,
0.13507643342018127,
0.12569688260555267,
-0.04686002805829048,
0.023393547162413597,
-0.047913480550050735,
0.030740072950720787,
-0.021642476320266724,
0.06442781537771225,
-0.043751634657382965,
0.05019192770123482,
-0.07388808578252792,
-0.0002223549090558663,
-0.006310486234724522,
-0.006622865330427885,
-0.022068170830607414,
0.008481727913022041,
-0.09138756990432739,
-0.06800553947687149,
0.02602532133460045,
0.14208070933818817,
-0.09605851024389267,
-0.11139021068811417,
-0.03612314909696579,
-0.07911112904548645,
0.030094875022768974,
0.01722545735538006,
0.005058996845036745,
0.008667095564305782,
0.05878870189189911,
0.007861410267651081,
-0.05962708219885826,
0.02333543635904789,
-0.026702750474214554,
0.10479134321212769,
-0.2308259755373001,
-0.052218448370695114,
0.0012049105716869235,
0.04862484708428383,
-0.07976505160331726,
-0.01821790635585785,
-0.1094716489315033,
0.015058347024023533,
0.025181017816066742,
0.0911964625120163,
-0.11095578968524933,
-0.07614384591579437,
-0.020773323252797127,
-0.020899133756756783,
-0.02748367190361023,
0.026448119431734085,
-0.038119006901979446,
0.051700517535209656,
0.044118817895650864,
0.01756492257118225,
0.006662724539637566,
-0.018579449504613876,
-0.04192554950714111,
-0.01774861477315426,
0.08600179105997086,
-0.0010466111125424504,
-0.07771792262792587,
-0.026117773726582527,
-0.26215800642967224,
0.028060724958777428,
0.10513308644294739,
0.005166682414710522,
-0.024554938077926636,
0.10832416266202927,
0.008524834178388119,
0.028788454830646515,
0.0018350702011957765,
-0.02201477810740471,
0.029370002448558807,
-0.1257377713918686,
-0.02739916741847992,
-0.029011761769652367,
0.023900756612420082,
-0.07160649448633194,
-0.03410128504037857,
0.08388891816139221,
0.05417615920305252,
0.11521792411804199,
-0.09080177545547485,
0.029462601989507675,
-0.0238654725253582,
0.03108496591448784,
0.0758393257856369,
-0.0859290361404419,
0.05579749494791031,
-0.052165526896715164,
-0.022381573915481567,
0.02232857421040535,
0.10738955438137054,
-0.029342668130993843,
-0.25415489077568054,
-0.023180587217211723,
-0.10654128342866898,
0.013421732001006603,
-0.03439192473888397,
0.25384289026260376,
-0.0016050048870965838,
0.014635675586760044,
-0.1301407814025879,
0.08738158643245697,
0.07605177909135818,
0.031326014548540115,
0.01847795583307743,
0.03274058923125267,
0.04035195708274841,
0.05975784361362457,
0.03984135761857033,
-0.004885810427367687,
-0.10281463712453842,
0.018641117960214615,
-0.1695116013288498,
0.12851879000663757,
-0.047209907323122025,
0.08975037187337875,
0.1831081360578537,
0.003100553760305047,
-0.01994115673005581,
0.10984695702791214,
0.017037509009242058,
-0.014549964107573032,
-0.21917158365249634,
-0.03560583293437958,
-0.13954536616802216,
0.011845204047858715,
-0.03450346738100052,
-0.038245685398578644,
-0.038587797433137894,
0.05545703321695328,
-0.07072962075471878,
0.029350608587265015,
0.13510289788246155,
-0.031639464199543,
0.08100204914808273,
-0.02005935087800026,
-0.04873959347605705,
0.021853795275092125,
0.011234770528972149,
0.012010683305561543,
0.04444584622979164,
0.0120514165610075,
0.05203193798661232,
-0.012272762134671211,
0.06476375460624695,
0.03652065619826317,
-0.028658784925937653,
-0.031251177191734314,
-0.005578153301030397,
0.034621644765138626,
0.11684147268533707,
0.033169738948345184,
-0.039910782128572464,
0.02113877423107624,
0.09646406024694443,
0.014231003820896149,
-0.04044613242149353,
-0.05482238531112671,
0.0453517809510231,
-0.12284336984157562,
0.056356798857450485,
-0.023660244420170784,
-0.017724143341183662,
-0.07693692296743393,
0.24708864092826843,
0.1482892632484436,
-0.03861561790108681,
0.015790991485118866,
-0.08782882243394852,
0.010521632619202137,
-0.058819208294153214,
0.08849099278450012,
0.03275210037827492,
0.3485138714313507,
-0.028891215100884438,
0.008544636890292168,
-0.0976739451289177,
-0.010477873496711254,
-0.09508576989173889,
-0.11362966895103455,
0.00810701958835125,
-0.03999623283743858,
-0.0870242640376091,
0.0493907704949379,
-0.1836540251970291,
-0.045127253979444504,
0.0843619629740715,
0.016962813213467598,
-0.013504581525921822,
-0.03466986492276192,
0.08052665740251541,
0.02289334312081337,
0.04154689982533455,
-0.08555149286985397,
0.04531046003103256,
0.0016500314231961966,
-0.05439621955156326,
-0.07024908810853958,
0.0819401890039444,
-0.01572991907596588,
-0.16081281006336212,
0.1789879947900772,
-0.03308327496051788,
0.024170560762286186,
0.06388276815414429,
-0.07410632073879242,
-0.16019995510578156,
0.10554498434066772,
-0.0665283352136612,
-0.10368763655424118,
-0.0012381125707179308,
0.07823662459850311,
0.009245526045560837,
0.0051195053383708,
0.022499240934848785,
-0.02869669534265995,
-0.04462038725614548,
0.0875253826379776,
0.035916078835725784,
-0.08429848402738571,
0.10313571244478226,
-0.05611560866236687,
0.09181742370128632,
-0.03808962553739548,
-0.042971618473529816,
-0.03508488088846207,
-0.03536601364612579,
0.03693263977766037,
-0.0050501711666584015,
-0.03085748292505741,
0.04025783762335777,
-0.1498527228832245,
-0.02271198108792305,
0.08690031617879868,
0.06389764696359634,
-0.18097622692584991,
0.0018488701898604631,
-0.15797998011112213,
0.0020151715725660324,
-0.049812059849500656,
-0.01733490452170372,
0.2427050769329071,
-0.005077694542706013,
-0.004548105876892805,
-0.12396873533725739,
-0.05738803744316101,
0.03945409134030342,
0.007073080167174339,
-0.13391004502773285
] |
null | null | transformers |
# MiniCPM-2B-Hephaestus
MiniCPM-2B-Hephaestus is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [gmonsoon/MiniCPM-2B-Hercules-v2.0](https://huggingface.co/gmonsoon/MiniCPM-2B-Hercules-v2.0)
* [gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2](https://huggingface.co/gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2)
## 🧩 Configuration
```yaml
models:
- model: gmonsoon/MiniCPM-2B-Hercules-v2.0
parameters:
density: 0.5
weight: 0.5
- model: gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2
parameters:
density: 0.5
weight: 0.5
merge_method: dare_ties
base_model: gmonsoon/MiniCPM-2B-Hercules-v2.0
parameters:
normalize: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "gmonsoon/MiniCPM-2B-Hephaestus"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "gmonsoon/MiniCPM-2B-Hercules-v2.0", "gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2"], "base_model": ["gmonsoon/MiniCPM-2B-Hercules-v2.0", "gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2"]} | text-generation | indischepartij/MiniCPM-3B-Hephaestus | [
"transformers",
"safetensors",
"llama",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"gmonsoon/MiniCPM-2B-Hercules-v2.0",
"gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2",
"conversational",
"base_model:gmonsoon/MiniCPM-2B-Hercules-v2.0",
"base_model:gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T05:49:37+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #merge #mergekit #lazymergekit #gmonsoon/MiniCPM-2B-Hercules-v2.0 #gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2 #conversational #base_model-gmonsoon/MiniCPM-2B-Hercules-v2.0 #base_model-gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# MiniCPM-2B-Hephaestus
MiniCPM-2B-Hephaestus is a merge of the following models using LazyMergekit:
* gmonsoon/MiniCPM-2B-Hercules-v2.0
* gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2
## Configuration
## Usage
| [
"# MiniCPM-2B-Hephaestus\n\nMiniCPM-2B-Hephaestus is a merge of the following models using LazyMergekit:\n* gmonsoon/MiniCPM-2B-Hercules-v2.0\n* gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2",
"## Configuration",
"## Usage"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #merge #mergekit #lazymergekit #gmonsoon/MiniCPM-2B-Hercules-v2.0 #gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2 #conversational #base_model-gmonsoon/MiniCPM-2B-Hercules-v2.0 #base_model-gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# MiniCPM-2B-Hephaestus\n\nMiniCPM-2B-Hephaestus is a merge of the following models using LazyMergekit:\n* gmonsoon/MiniCPM-2B-Hercules-v2.0\n* gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2",
"## Configuration",
"## Usage"
] | [
150,
70,
4,
3
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #merge #mergekit #lazymergekit #gmonsoon/MiniCPM-2B-Hercules-v2.0 #gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2 #conversational #base_model-gmonsoon/MiniCPM-2B-Hercules-v2.0 #base_model-gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# MiniCPM-2B-Hephaestus\n\nMiniCPM-2B-Hephaestus is a merge of the following models using LazyMergekit:\n* gmonsoon/MiniCPM-2B-Hercules-v2.0\n* gmonsoon/MiniCPM-2B-OpenHermes-2.5-v2## Configuration## Usage"
] | [
-0.02464080974459648,
0.03871772810816765,
-0.007161885034292936,
-0.007599781733006239,
0.045807141810655594,
0.03389443829655647,
0.15204405784606934,
0.11393547058105469,
-0.0058275978080928326,
0.07281916588544846,
0.04231114685535431,
0.05355644226074219,
0.03506099432706833,
0.05847737193107605,
-0.03676280379295349,
-0.21903268992900848,
0.05018598586320877,
-0.014788861386477947,
-0.11674975603818893,
0.05288799852132797,
0.1054023876786232,
-0.06881019473075867,
0.11013129353523254,
0.011589773930609226,
-0.05969458073377609,
-0.005367260426282883,
0.00840732455253601,
-0.02211080864071846,
0.06471024453639984,
0.0468398854136467,
-0.0021284634713083506,
0.028526900336146355,
-0.0064507354982197285,
-0.12347172200679779,
0.004336172249168158,
0.021512383595108986,
0.003861162578687072,
0.07026377320289612,
0.06482084840536118,
-0.05510186031460762,
0.15128694474697113,
-0.1170288622379303,
0.03264428302645683,
0.05553822964429855,
-0.08203229308128357,
-0.14748719334602356,
-0.06174337863922119,
0.05409211292862892,
0.09076064079999924,
-0.013492665253579617,
-0.004894597921520472,
0.1397697478532791,
-0.06453468650579453,
0.02358621545135975,
0.22888518869876862,
-0.3236493468284607,
-0.018189160153269768,
0.1428678035736084,
0.039310798048973083,
0.01984851062297821,
0.02596428245306015,
0.03328048065304756,
-0.0019742154981940985,
0.005515784956514835,
0.06964313983917236,
-0.06058397889137268,
0.0957045927643776,
-0.03906344994902611,
-0.11149731278419495,
-0.0011315614683553576,
0.18676823377609253,
-0.015471224673092365,
0.023603148758411407,
-0.12296507507562637,
-0.10851186513900757,
0.05742799863219261,
-0.05525228753685951,
-0.02563660964369774,
0.07623255252838135,
-0.041996702551841736,
0.0826297476887703,
-0.06984647363424301,
-0.0573330819606781,
-0.04292838275432587,
-0.07471570372581482,
0.15485228598117828,
0.015603550709784031,
0.01913764886558056,
-0.033950354903936386,
0.05417027324438095,
-0.07164667546749115,
-0.12322299927473068,
-0.06624281406402588,
-0.06793539226055145,
0.014073353260755539,
-0.02029464766383171,
-0.03596203401684761,
-0.046614870429039,
0.0905214250087738,
0.16681110858917236,
-0.06762522459030151,
0.04758557304739952,
0.07436016947031021,
0.021662941202521324,
-0.0011337560135871172,
0.012813524343073368,
-0.03148166835308075,
-0.11747772991657257,
0.05760306492447853,
0.0644470825791359,
0.12779082357883453,
0.005392453167587519,
-0.0814337283372879,
-0.03796170651912689,
0.013432732783257961,
0.05890846252441406,
0.05731308087706566,
0.07871585339307785,
-0.04481139034032822,
-0.0731237456202507,
0.17863766849040985,
-0.11077426373958588,
0.0012311672326177359,
0.0007462972425855696,
0.010304792784154415,
0.05826490744948387,
0.04510015994310379,
0.04468222334980965,
-0.041877225041389465,
0.1111363023519516,
-0.05243585631251335,
-0.031723782420158386,
-0.021185390651226044,
-0.03981616348028183,
-0.007220723200589418,
-0.019669225439429283,
-0.03886284679174423,
-0.12538203597068787,
-0.14564265310764313,
0.04098150134086609,
0.034898921847343445,
-0.06314682215452194,
-0.05177516117691994,
-0.02050143852829933,
-0.010697601363062859,
-0.00567030580714345,
-0.0029461511876434088,
0.031034665182232857,
-0.015688519924879074,
-0.03343290835618973,
0.04238015040755272,
0.08835869282484055,
-0.06313562393188477,
0.02272024005651474,
-0.10971724987030029,
0.10270731151103973,
-0.12911824882030487,
0.034651849418878555,
-0.06147657707333565,
0.03658594936132431,
-0.12514227628707886,
-0.0018856655806303024,
-0.033404480665922165,
0.0016567213460803032,
-0.010808678343892097,
0.15499204397201538,
-0.07712703198194504,
-0.10578865557909012,
0.24752099812030792,
-0.15193799138069153,
-0.15305496752262115,
0.034593742340803146,
0.07303135842084885,
0.03101976402103901,
0.07422968000173569,
0.169653058052063,
0.055618785321712494,
-0.07128199934959412,
0.010233748704195023,
0.052884217351675034,
0.05611569806933403,
0.035071998834609985,
0.12580452859401703,
-0.13071556389331818,
-0.004390772897750139,
0.044707041233778,
-0.08511098474264145,
-0.010438266210258007,
0.002277140039950609,
-0.05995989218354225,
-0.059037160128355026,
-0.048144254833459854,
0.0866812989115715,
-0.030813327059149742,
0.032981909811496735,
-0.07515060156583786,
-0.05169714242219925,
0.09196338057518005,
0.10375329852104187,
-0.04693296179175377,
0.0425223633646965,
-0.10884897410869598,
0.11627993732690811,
-0.05719353258609772,
0.03998313471674919,
-0.0919124111533165,
-0.04000956565141678,
0.0286262109875679,
-0.10477390885353088,
-0.004072133917361498,
0.0036375655326992273,
0.1096469834446907,
0.050765510648489,
-0.0465119369328022,
-0.02380594238638878,
0.0959281325340271,
0.02401527762413025,
-0.008362469263374805,
-0.18798881769180298,
-0.08977032452821732,
-0.03705447167158127,
0.18785078823566437,
-0.09478884935379028,
0.03916497528553009,
0.047216787934303284,
0.13760289549827576,
0.05287715420126915,
0.0052055492997169495,
0.010048176161944866,
-0.025003967806696892,
-0.01621309481561184,
-0.06540072709321976,
0.09915022552013397,
-0.005691323895007372,
-0.08044178783893585,
0.10332127660512924,
-0.16437195241451263,
0.11265935003757477,
0.13139773905277252,
0.024429073557257652,
0.019244708120822906,
-0.01807406358420849,
-0.012409611605107784,
-0.050379812717437744,
0.04601477459073067,
-0.08501404523849487,
0.029493670910596848,
0.053082190454006195,
0.11470770835876465,
-0.07772015035152435,
-0.07420988380908966,
-0.0017851018346846104,
-0.06824801862239838,
-0.017336871474981308,
0.03042118065059185,
0.05049203708767891,
-0.11018726974725723,
0.09685888141393661,
0.23875539004802704,
0.015151034109294415,
0.1096058264374733,
0.007649974897503853,
-0.025394681841135025,
-0.03497694432735443,
-0.00781257078051567,
0.03979133814573288,
-0.012403394095599651,
-0.12602171301841736,
0.005127611104398966,
0.04996264725923538,
0.017275495454669,
0.06488408148288727,
-0.06942732632160187,
0.0279830489307642,
0.044410210102796555,
-0.025008171796798706,
0.13823844492435455,
0.07490488886833191,
-0.03203173354268074,
0.08806784451007843,
0.030689366161823273,
0.08895757794380188,
0.006592386402189732,
-0.036117322742938995,
-0.10283008962869644,
0.15504704415798187,
-0.09800862520933151,
-0.1855669617652893,
-0.05658126249909401,
-0.04785377159714699,
-0.06379815191030502,
0.014290605671703815,
0.036957092583179474,
-0.06157798692584038,
-0.07034914195537567,
-0.1218542829155922,
0.10475575178861618,
0.02049371227622032,
-0.021387184038758278,
-0.04483061283826828,
0.027346640825271606,
0.04553845897316933,
-0.128742054104805,
-0.036371927708387375,
0.035769663751125336,
-0.1417596936225891,
0.036562662571668625,
-0.0006055022240616381,
0.012582422234117985,
0.12209177017211914,
0.052787985652685165,
-0.012980158440768719,
0.0051970756612718105,
0.17189231514930725,
0.004365244880318642,
0.033876221626996994,
0.19813492894172668,
-0.005271037109196186,
0.03533829376101494,
0.139762744307518,
0.0284635741263628,
-0.05033627152442932,
-0.04380584508180618,
-0.034780386835336685,
-0.007306532934308052,
-0.17658784985542297,
-0.14901188015937805,
-0.05355948582291603,
0.08016950637102127,
0.059217821806669235,
0.04229900613427162,
0.023523617535829544,
0.06558069586753845,
-0.08003950119018555,
0.03843836858868599,
-0.0006792565691284835,
0.07250895351171494,
0.19082818925380707,
0.03172959387302399,
0.07776960730552673,
-0.04889373108744621,
-0.014248124323785305,
0.07811834663152695,
0.05526096373796463,
0.09687204658985138,
0.04997691139578819,
0.1712011992931366,
0.0496835894882679,
0.015168425627052784,
0.037240248173475266,
0.041965585201978683,
-0.02221977710723877,
-0.010918782092630863,
-0.01907016709446907,
-0.13618306815624237,
-0.029739627614617348,
0.05852103978395462,
0.002440120093524456,
0.034298013895750046,
-0.011206193827092648,
0.054915931075811386,
0.0941351130604744,
0.1946847140789032,
0.09038367867469788,
-0.19751301407814026,
-0.04921580106019974,
0.11308082193136215,
0.030142854899168015,
0.00836075097322464,
0.008537028916180134,
0.08092138916254044,
-0.10862258821725845,
0.14222504198551178,
-0.03246790170669556,
0.029773719608783722,
-0.04718310758471489,
0.027276715263724327,
0.03465937823057175,
0.09586206078529358,
0.04786182940006256,
0.055465519428253174,
-0.1836332380771637,
0.10671975463628769,
0.03856967017054558,
-0.0048672654666006565,
-0.029415186494588852,
0.04866555705666542,
0.017841624096035957,
0.1314631998538971,
0.12066622078418732,
0.03685035929083824,
-0.05418109521269798,
0.01336610410362482,
-0.08427564799785614,
0.03730856254696846,
0.055689532309770584,
-0.0962548777461052,
0.06564366072416306,
-0.08898384869098663,
-0.0648958832025528,
-0.016429146751761436,
0.01175684854388237,
-0.11807739734649658,
-0.13451051712036133,
0.1052342876791954,
0.008568000048398972,
-0.05091850832104683,
-0.13032333552837372,
-0.023182041943073273,
-0.017128311097621918,
0.2400975376367569,
-0.08659191429615021,
-0.13196294009685516,
-0.07037718594074249,
-0.05919888988137245,
0.08698420971632004,
-0.06502299010753632,
0.08909895271062851,
-0.02602754719555378,
0.1056719422340393,
-0.023108022287487984,
-0.17753425240516663,
0.07592955231666565,
-0.09983384609222412,
-0.12179425358772278,
-0.02096259593963623,
0.19555993378162384,
-0.09053194522857666,
0.04121291637420654,
-0.0028738330584019423,
0.05284751579165459,
0.0030238127801567316,
-0.07721482962369919,
0.034057699143886566,
0.18995341658592224,
-0.014974206686019897,
0.02612193301320076,
-0.02311643958091736,
-0.10751000046730042,
0.04982795938849449,
-0.00540713407099247,
0.1731613576412201,
0.3084169030189514,
-0.034989673644304276,
0.11019517481327057,
0.0501423254609108,
-0.03985438495874405,
-0.2222016304731369,
-0.05949033424258232,
0.0029172280337661505,
-0.03707174211740494,
0.060054242610931396,
-0.12889133393764496,
0.1258600354194641,
0.09461924433708191,
-0.02894045040011406,
0.13621293008327484,
-0.33444011211395264,
-0.1169523224234581,
0.018385030329227448,
0.06463275104761124,
0.011093780398368835,
-0.13317246735095978,
-0.10786095261573792,
-0.07684445381164551,
-0.23372235894203186,
0.12485029548406601,
-0.1486075222492218,
0.04994891211390495,
-0.041386596858501434,
-0.03400526940822601,
0.030881037935614586,
-0.03642892464995384,
0.1299433708190918,
-0.017040295526385307,
-0.005159236490726471,
-0.05507395416498184,
-0.05325230211019516,
0.11720560491085052,
-0.02668602205812931,
0.028985198587179184,
-0.1602042317390442,
0.01279024500399828,
0.004632053431123495,
-0.005751318763941526,
-0.044759657233953476,
0.06928619742393494,
-0.06367746740579605,
-0.054655712097883224,
-0.006459407042711973,
0.03646297752857208,
0.05338399484753609,
0.03944217786192894,
0.1004721000790596,
-0.043313365429639816,
0.05262203887104988,
0.1951368898153305,
0.1204058825969696,
-0.05811283364892006,
-0.015574020333588123,
-0.02074345573782921,
-0.023761820048093796,
0.07507185637950897,
-0.14416301250457764,
0.03912120684981346,
0.019396930932998657,
0.012267298065125942,
0.03107926808297634,
0.02570953033864498,
-0.07070435583591461,
-0.03128848969936371,
0.08336391299962997,
-0.18684685230255127,
-0.14227476716041565,
-0.023108597844839096,
0.06041228771209717,
-0.029650401324033737,
0.06180497631430626,
0.1429038941860199,
0.00004188962702755816,
-0.03429025039076805,
0.006548729259520769,
0.030165260657668114,
-0.07686521857976913,
0.12873174250125885,
-0.02880757674574852,
0.05168629810214043,
-0.09284773468971252,
0.061213988810777664,
0.010261774063110352,
-0.09325195848941803,
-0.021815119311213493,
0.11775996536016464,
-0.09084174036979675,
-0.07676573097705841,
-0.05988697707653046,
0.050933197140693665,
0.04264269396662712,
-0.015507758595049381,
-0.03152639418840408,
-0.13018332421779633,
-0.015066588297486305,
0.02572159841656685,
0.07836152613162994,
0.020696308463811874,
0.034922145307064056,
0.004187394864857197,
0.005625935737043619,
0.08637914061546326,
-0.048841312527656555,
0.09064937382936478,
-0.10667063295841217,
0.04933857545256615,
-0.024601629003882408,
-0.007677032146602869,
-0.02469361200928688,
0.024549953639507294,
-0.10013385862112045,
-0.06640352308750153,
-0.12449643760919571,
0.0009774924255907536,
-0.11920753121376038,
-0.038174621760845184,
-0.004293904174119234,
0.0471775084733963,
-0.025759855285286903,
-0.0004504988028202206,
-0.05022948607802391,
-0.05605132132768631,
-0.06639747321605682,
0.037424005568027496,
-0.0662747472524643,
0.04111381620168686,
0.024687284603714943,
-0.11354530602693558,
0.07656928151845932,
-0.011297386139631271,
0.01017716247588396,
-0.010046297684311867,
-0.11132771521806717,
-0.08678588271141052,
0.04402071237564087,
0.02026430144906044,
0.04729365557432175,
-0.09091421216726303,
-0.03556456416845322,
0.01698301173746586,
0.0038530933670699596,
-0.01673036441206932,
0.10204848647117615,
-0.0987401232123375,
0.10085040330886841,
-0.059133172035217285,
-0.04440333694219589,
-0.03574909269809723,
-0.06492145359516144,
0.023283913731575012,
-0.030250204727053642,
0.1343764066696167,
-0.07027043402194977,
0.02161603793501854,
-0.17054302990436554,
-0.006972321774810553,
-0.0040699802339077,
-0.07878442853689194,
-0.10431038588285446,
0.011875146068632603,
0.025772301480174065,
-0.02712882123887539,
0.18978777527809143,
-0.013283105567097664,
-0.040866538882255554,
0.058341581374406815,
0.0036524361930787563,
0.0402819998562336,
0.07697602361440659,
0.19259381294250488,
0.07103017717599869,
-0.002282868605107069,
-0.04370157793164253,
0.012860553339123726,
0.01924751326441765,
-0.05866244435310364,
0.15639114379882812,
0.13479925692081451,
-0.05132291838526726,
0.07119909673929214,
0.045612867921590805,
-0.0566646009683609,
-0.1096751019358635,
0.03814460337162018,
0.0013979366049170494,
0.09427357465028763,
-0.03353899344801903,
0.10224446654319763,
0.14327308535575867,
-0.14679749310016632,
0.006405299995094538,
-0.04864013195037842,
0.015213045291602612,
-0.13410326838493347,
-0.12893015146255493,
-0.10408291965723038,
-0.14509087800979614,
-0.027618905529379845,
-0.09084837883710861,
-0.008518392220139503,
0.041871167719364166,
-0.014430851675570011,
-0.017009830102324486,
0.15621700882911682,
-0.05971286818385124,
-0.033479224890470505,
0.01933525688946247,
0.0007653113570995629,
-0.03699933737516403,
0.016798142343759537,
-0.023009005934000015,
-0.012022675015032291,
0.03875105455517769,
0.002246382413432002,
0.031306587159633636,
-0.05136023089289665,
0.05576464533805847,
-0.041419800370931625,
-0.11049460619688034,
0.0001943679671967402,
0.011258559301495552,
-0.046008024364709854,
-0.00922380480915308,
0.02731461264193058,
-0.04417851194739342,
-0.004813236650079489,
0.12559828162193298,
-0.08194604516029358,
-0.14509916305541992,
-0.0357845239341259,
0.1142415851354599,
-0.021821241825819016,
0.07514279335737228,
0.049368519335985184,
-0.07393602281808853,
-0.058734506368637085,
0.18205420672893524,
0.28567662835121155,
-0.03651206195354462,
0.035111356526613235,
0.0037660521920770407,
0.011040877550840378,
-0.016329847276210785,
0.10641217231750488,
0.003467593574896455,
0.14065584540367126,
-0.0429520383477211,
0.009010913781821728,
0.030841799452900887,
-0.05638011172413826,
-0.12268010526895523,
0.04008172079920769,
0.02414514869451523,
0.00958348996937275,
0.05006084591150284,
0.018287232145667076,
-0.03269989416003227,
0.03289671987295151,
0.029967697337269783,
-0.1577080935239792,
-0.10699652880430222,
-0.04825371503829956,
0.0915956199169159,
0.022005079314112663,
0.08755598217248917,
-0.018441217020154,
-0.09874125570058823,
0.12659958004951477,
-0.009804602712392807,
-0.12548932433128357,
-0.0589013434946537,
0.0642305240035057,
-0.14645494520664215,
0.15958477556705475,
-0.0017617868725210428,
0.01548035442829132,
0.07218071818351746,
0.0044859605841338634,
-0.13328160345554352,
0.013480418361723423,
0.03894300013780594,
-0.07121869176626205,
0.05829799920320511,
0.07773217558860779,
-0.02056233584880829,
0.10618826001882553,
0.06605666875839233,
-0.13625280559062958,
0.013455257751047611,
0.17065279185771942,
-0.030230041593313217,
-0.038723696023225784,
0.010772570967674255,
-0.07186371833086014,
0.11420904844999313,
0.13338349759578705,
-0.05035288259387016,
-0.02053179405629635,
-0.043483611196279526,
0.05234973877668381,
0.058711033314466476,
0.12213461846113205,
-0.06142779067158699,
-0.15180262923240662,
-0.00003946256038034335,
-0.005301513243466616,
0.0652705654501915,
-0.19241568446159363,
-0.052309550344944,
-0.07444898784160614,
0.012754101306200027,
-0.1214158684015274,
0.059064533561468124,
0.14434105157852173,
0.005075825843960047,
-0.03162582591176033,
-0.11238988488912582,
-0.0003938363224733621,
0.10956893861293793,
-0.12123744934797287,
-0.09305596351623535
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": [], "datasets": "ArianAskari/SOLID"} | text-generation | ArianAskari/SOLID-SFT-WoDPO-MixQV2-Zephyr-7b-beta | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"en",
"dataset:ArianAskari/SOLID",
"arxiv:1910.09700",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T05:50:12+00:00 | [
"1910.09700"
] | [
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #conversational #en #dataset-ArianAskari/SOLID #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #conversational #en #dataset-ArianAskari/SOLID #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
81,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #conversational #en #dataset-ArianAskari/SOLID #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]"
] | [
-0.08591114729642868,
0.18951410055160522,
-0.0033713625743985176,
0.022266317158937454,
0.09957055747509003,
-0.0011251148534938693,
0.059102218598127365,
0.12024262547492981,
0.022303961217403412,
0.1301860213279724,
0.051019661128520966,
0.15435779094696045,
0.107495978474617,
0.20398804545402527,
0.0019805266056209803,
-0.15283428132534027,
0.039414722472429276,
-0.09943387657403946,
0.027260450646281242,
0.11693242192268372,
0.13333328068256378,
-0.11049968749284744,
0.06592319905757904,
-0.03267781436443329,
-0.002022090833634138,
-0.06199624016880989,
-0.07250470668077469,
-0.028583087027072906,
0.04150979593396187,
0.021239934489130974,
0.05376110598444939,
-0.010742194019258022,
0.08744451403617859,
-0.2901124060153961,
0.022842584177851677,
0.0485212616622448,
-0.0017796496395021677,
0.07630124688148499,
0.09095916152000427,
-0.05410704389214516,
0.08763454109430313,
-0.08292148262262344,
0.1270849108695984,
0.10611572116613388,
-0.07227595895528793,
-0.1651565134525299,
-0.075367771089077,
0.1111975684762001,
0.1790151745080948,
0.06474190205335617,
-0.03376016765832901,
0.12017020583152771,
-0.03213946148753166,
0.03724733740091324,
0.044842761009931564,
-0.05471503362059593,
-0.05572173371911049,
0.042899828404188156,
0.12484990805387497,
0.04225701466202736,
-0.12191780656576157,
-0.0019060199847444892,
0.025276480242609978,
0.04046973958611488,
0.10134588927030563,
0.02000250853598118,
0.16189776360988617,
0.020992033183574677,
-0.14044798910617828,
-0.052640270441770554,
0.04825855419039726,
0.0181200560182333,
-0.041390545666217804,
-0.25917497277259827,
-0.005468228831887245,
-0.044545650482177734,
-0.03781736269593239,
-0.06377661973237991,
0.03515990078449249,
0.0037296300288289785,
0.11075441539287567,
-0.052958954125642776,
-0.08164630830287933,
-0.025297194719314575,
0.07798552513122559,
0.07309716939926147,
0.01828034594655037,
-0.025118820369243622,
0.03161930665373802,
0.09600728005170822,
0.09970615804195404,
-0.11522892117500305,
-0.04717804491519928,
-0.06340683251619339,
-0.07976372539997101,
-0.02989640273153782,
0.053809188306331635,
0.06479813903570175,
0.055789828300476074,
0.24224527180194855,
0.004872492980211973,
0.036379262804985046,
0.025253843516111374,
-0.00022044511570129544,
0.04856210947036743,
0.07400048524141312,
-0.0510658398270607,
-0.16834498941898346,
-0.019700143486261368,
0.100941002368927,
-0.0020966820884495974,
-0.037669647485017776,
-0.04390076920390129,
0.03787677735090256,
0.08134777098894119,
0.1052965372800827,
0.14250242710113525,
0.012465027160942554,
-0.0721745640039444,
-0.07178683578968048,
0.2067420929670334,
-0.1490723341703415,
0.03175797685980797,
0.010890942066907883,
-0.015492487698793411,
-0.06279323995113373,
0.0093216672539711,
0.02679617889225483,
-0.03862566500902176,
0.07456154376268387,
-0.06362278759479523,
-0.04901086166501045,
-0.11192686855792999,
-0.018724525347352028,
0.05105894058942795,
-0.020058566704392433,
-0.040508586913347244,
-0.05080017074942589,
-0.09641260653734207,
-0.09262187778949738,
0.09625022113323212,
-0.05899379402399063,
-0.05469419062137604,
-0.03942353278398514,
-0.0762234777212143,
0.033354345709085464,
0.0025586688425391912,
0.08315546065568924,
-0.028627494350075722,
0.05162280797958374,
-0.035812459886074066,
0.05065896362066269,
0.10143027454614639,
0.03564368188381195,
-0.06475099921226501,
0.06836478412151337,
-0.16765567660331726,
0.09521768242120743,
-0.07747264951467514,
0.03799491003155708,
-0.16434603929519653,
-0.0023962759878486395,
0.049202632158994675,
0.030180253088474274,
0.017385808750987053,
0.147915780544281,
-0.17594081163406372,
-0.013952301815152168,
0.17978331446647644,
-0.10041902214288712,
-0.13655312359333038,
0.04058404639363289,
-0.05704823508858681,
0.1869451254606247,
0.05159022659063339,
-0.012890767306089401,
0.06855574250221252,
-0.14087168872356415,
-0.06638427823781967,
-0.06036901846528053,
-0.01128858420997858,
0.10120076686143875,
0.0734618604183197,
-0.06581661850214005,
0.057426828891038895,
0.0201321542263031,
-0.04840515926480293,
-0.02343326434493065,
-0.036143478006124496,
-0.09638531506061554,
0.02645096741616726,
-0.09498225152492523,
0.020638953894376755,
-0.014116978272795677,
-0.07909931987524033,
-0.0003651797887869179,
-0.1623964011669159,
-0.0196976438164711,
0.08402704447507858,
0.006334508303552866,
-0.017391294240951538,
-0.09774032235145569,
0.020764444023370743,
-0.021108895540237427,
-0.003496028482913971,
-0.13055238127708435,
-0.058796193450689316,
0.028371669352054596,
-0.15084494650363922,
0.015560870990157127,
-0.15134941041469574,
0.04931439459323883,
0.018444349989295006,
-0.04701909422874451,
-0.039214152842760086,
0.028308270499110222,
0.015857039019465446,
-0.04085249826312065,
-0.22762233018875122,
-0.03304901346564293,
-0.05571984872221947,
0.1221156045794487,
-0.1838909536600113,
0.04857059568166733,
0.032088082283735275,
0.14346154034137726,
-0.005432146601378918,
-0.06627129018306732,
0.029376499354839325,
-0.06572920083999634,
-0.01405918225646019,
-0.06108192354440689,
0.01643037609755993,
-0.02216598205268383,
-0.046639952808618546,
0.04501141235232353,
-0.17690297961235046,
-0.0629289373755455,
0.1101449504494667,
0.03948267921805382,
-0.1271558403968811,
-0.06403711438179016,
-0.019428426399827003,
-0.0843457356095314,
-0.038206472992897034,
-0.08128256350755692,
0.08287390321493149,
0.06362864375114441,
0.02629874460399151,
-0.05784231796860695,
-0.08279623091220856,
0.009589358232915401,
0.0030292565934360027,
-0.01637669838964939,
0.07914599031209946,
0.027421679347753525,
-0.17498062551021576,
0.10552344471216202,
0.07292444258928299,
0.05943441763520241,
0.09095818549394608,
-0.006180671975016594,
-0.09002769738435745,
-0.04325848072767258,
0.04754214361310005,
0.02575576864182949,
0.13144296407699585,
-0.0943843424320221,
0.021420160308480263,
0.03651288524270058,
-0.046079859137535095,
0.04347645863890648,
-0.053194209933280945,
0.023470405489206314,
0.0021141006145626307,
0.0005579995340667665,
0.061772480607032776,
-0.0396815687417984,
-0.0008660968160256743,
0.058744706213474274,
0.0760321319103241,
0.03436155244708061,
0.037537723779678345,
-0.04949759319424629,
-0.12246540188789368,
0.13930481672286987,
-0.10360046476125717,
-0.21216371655464172,
-0.15138190984725952,
-0.01332154218107462,
0.037512268871068954,
-0.009922226890921593,
0.001954267732799053,
-0.042666688561439514,
-0.09381214529275894,
-0.07360909134149551,
0.024256350472569466,
0.041591908782720566,
-0.06499204784631729,
-0.05179423838853836,
0.0589577816426754,
0.03201922029256821,
-0.1158737987279892,
0.015236659906804562,
0.05508697032928467,
-0.04298005998134613,
-0.012654871679842472,
0.079257532954216,
0.10421723127365112,
0.1528315544128418,
0.020987221971154213,
-0.014384711161255836,
0.04109276086091995,
0.20888066291809082,
-0.1427038609981537,
0.0986129492521286,
0.13800325989723206,
-0.07164572924375534,
0.07148110121488571,
0.20800955593585968,
0.032779235392808914,
-0.0758822038769722,
0.033028408885002136,
0.036740660667419434,
-0.019172044470906258,
-0.24666911363601685,
-0.0681489035487175,
-0.009638508781790733,
-0.07870946079492569,
0.08955040574073792,
0.07775488495826721,
0.1054048165678978,
0.03622778132557869,
-0.09216933697462082,
-0.08375802636146545,
0.05951887369155884,
0.1228976622223854,
-0.01720024272799492,
-0.0013506599934771657,
0.09191402047872543,
-0.004085235763341188,
0.019875019788742065,
0.08268055319786072,
-0.0001765630440786481,
0.15473893284797668,
0.027463169768452644,
0.1784254014492035,
0.08076410740613937,
0.07750341296195984,
-0.02370513416826725,
0.033715397119522095,
0.031207602471113205,
0.050495922565460205,
0.0058638532646000385,
-0.07994958758354187,
-0.018029509112238884,
0.13463029265403748,
0.017555976286530495,
0.010689089074730873,
0.024890149012207985,
-0.03097381815314293,
0.06426969915628433,
0.19360235333442688,
-0.02228063903748989,
-0.20124611258506775,
-0.08559868484735489,
0.07746205478906631,
-0.08731615543365479,
-0.13906006515026093,
-0.013039813376963139,
0.014492535963654518,
-0.15630744397640228,
0.015714148059487343,
-0.04881053790450096,
0.10320991277694702,
-0.11320079863071442,
-0.021100979298353195,
0.07428882271051407,
0.048650771379470825,
0.0035275998525321484,
0.048808757215738297,
-0.17617353796958923,
0.1045973002910614,
0.031072931364178658,
0.08414750546216965,
-0.09890686720609665,
0.08970693498849869,
0.011286185123026371,
-0.07314646989107132,
0.18064577877521515,
-0.010738139040768147,
-0.0694650188088417,
-0.09453598409891129,
-0.11837100237607956,
-0.02726702019572258,
0.10227955877780914,
-0.14026488363742828,
0.09417592734098434,
-0.03641578182578087,
-0.03401083126664162,
0.005219758953899145,
-0.07935810834169388,
-0.11700950562953949,
-0.17629259824752808,
0.06388171017169952,
-0.10724657773971558,
0.04094449058175087,
-0.09698031842708588,
-0.05551959201693535,
0.009462553076446056,
0.21563945710659027,
-0.2205141931772232,
-0.09556426107883453,
-0.13847346603870392,
-0.06836716830730438,
0.14751750230789185,
-0.05964501202106476,
0.09806060045957565,
0.0017309810500591993,
0.14051106572151184,
-0.009076863527297974,
-0.007576607633382082,
0.08575788140296936,
-0.09029825031757355,
-0.1891731321811676,
-0.05288151279091835,
0.1325221061706543,
0.14185570180416107,
0.024270936846733093,
-0.008372500538825989,
0.030560052022337914,
-0.02933473512530327,
-0.1015915721654892,
0.032950110733509064,
0.19625476002693176,
0.0920095443725586,
-0.004152963869273663,
-0.025343650951981544,
-0.1535644680261612,
-0.08521492779254913,
-0.061786215752363205,
-0.0005300347693264484,
0.1992185264825821,
-0.06171563267707825,
0.16717329621315002,
0.16103315353393555,
-0.06240608170628548,
-0.21536792814731598,
-0.016204072162508965,
0.032778676599264145,
-0.006342306267470121,
0.02949732355773449,
-0.16765886545181274,
0.07935850322246552,
-0.038786835968494415,
-0.07533682882785797,
0.11726700514554977,
-0.13281740248203278,
-0.13774770498275757,
0.1007973849773407,
0.04325760155916214,
-0.18878419697284698,
-0.13924741744995117,
-0.11246135085821152,
-0.021350998431444168,
-0.10132578015327454,
0.08525710552930832,
0.004764101002365351,
-0.00354272173717618,
0.029304277151823044,
0.015254397876560688,
0.04497908428311348,
-0.06542695313692093,
0.18087945878505707,
-0.03826899826526642,
0.0029263384640216827,
-0.08073239773511887,
-0.09020382165908813,
0.038588058203458786,
-0.06295407563447952,
0.09007441997528076,
-0.017774123698472977,
0.013888939283788204,
-0.08299001306295395,
-0.05981450155377388,
-0.06696662306785583,
0.02645951695740223,
-0.08893732726573944,
-0.09624781459569931,
-0.018495704978704453,
0.10162613540887833,
0.11547663807868958,
-0.015178020112216473,
0.023715490475296974,
-0.07661876082420349,
0.060629528015851974,
0.24850469827651978,
0.1865287870168686,
0.07004489004611969,
-0.03249715268611908,
-0.004796118009835482,
-0.03821421414613724,
0.039546530693769455,
-0.1689022332429886,
0.04890618100762367,
0.05118025466799736,
0.013387631624937057,
0.08358875662088394,
-0.009707284159958363,
-0.15496408939361572,
-0.07026869803667068,
0.07576935738325119,
-0.04827704280614853,
-0.18592816591262817,
-0.01683025248348713,
0.06391692906618118,
-0.20023861527442932,
-0.041615214198827744,
0.05948876589536667,
-0.0005087462486699224,
-0.03974737226963043,
0.016980772837996483,
0.10129724442958832,
-0.004164275713264942,
0.08713217824697495,
0.06588397920131683,
0.08972740918397903,
-0.0916028693318367,
0.06921800225973129,
0.1018603965640068,
-0.060369823127985,
0.043673500418663025,
0.11816508322954178,
-0.04888302460312843,
-0.04832867905497551,
0.06316325813531876,
0.06346286088228226,
0.0069361296482384205,
-0.04177531599998474,
0.020308077335357666,
-0.023852862417697906,
0.04984608665108681,
0.10398845374584198,
0.017023544758558273,
0.008761642500758171,
0.0681496411561966,
0.05425215885043144,
-0.06768125295639038,
0.13304312527179718,
0.0572650283575058,
0.020188961178064346,
-0.05409325286746025,
-0.03502468764781952,
-0.003865145845338702,
-0.015512671321630478,
-0.018833089619874954,
-0.0005200320156291127,
-0.07575608789920807,
-0.007251439616084099,
-0.16512878239154816,
0.04271606355905533,
-0.12122757732868195,
0.000758568465244025,
0.01757586933672428,
-0.028753815218806267,
0.015823930501937866,
0.004630325362086296,
-0.05824412778019905,
-0.07961151748895645,
-0.01621859520673752,
0.10554816573858261,
-0.15987098217010498,
0.000006971866241656244,
0.08041578531265259,
-0.10180455446243286,
0.08254267275333405,
-0.004729445558041334,
0.005627367179840803,
0.001556327915750444,
-0.15077221393585205,
0.052106812596321106,
-0.03683033213019371,
-0.008052549324929714,
-0.0028627223800867796,
-0.1978321224451065,
-0.022987497970461845,
-0.03588982671499252,
-0.06754298508167267,
0.0010133404284715652,
0.0021536697167903185,
-0.10626740008592606,
0.06582276523113251,
0.02484598383307457,
-0.04247516021132469,
-0.031127311289310455,
0.03359273448586464,
0.09694145619869232,
-0.026543520390987396,
0.08433426171541214,
-0.015508226118981838,
0.07229591906070709,
-0.1663266271352768,
0.011730297468602657,
-0.018677784129977226,
0.040602993220090866,
-0.022090008482336998,
-0.03073965571820736,
0.04723985120654106,
-0.01781122200191021,
0.16422079503536224,
-0.04028577730059624,
0.05164588615298271,
0.049013588577508926,
-0.007309996988624334,
0.014953473582863808,
0.08314485102891922,
0.05880444124341011,
-0.0014755617594346404,
0.0019702643621712923,
0.029677774757146835,
-0.023262159898877144,
-0.060997169464826584,
-0.15071363747119904,
0.02580154687166214,
0.19596615433692932,
0.09773294627666473,
0.0013188386801630259,
0.04597467929124832,
-0.1274193972349167,
-0.09621517360210419,
0.1213398426771164,
-0.031184211373329163,
-0.03826535493135452,
-0.09135549515485764,
0.17124825716018677,
0.12666195631027222,
-0.18048261106014252,
0.07708001136779785,
-0.05411146208643913,
-0.04289722442626953,
-0.09348294138908386,
-0.21678252518177032,
-0.056193772703409195,
-0.018026480451226234,
-0.020782630890607834,
-0.046267107129096985,
0.048903029412031174,
0.05317362770438194,
-0.013364640064537525,
-0.014126998372375965,
0.08278103172779083,
0.00421117153018713,
-0.018623115494847298,
0.047679562121629715,
0.05786889046430588,
0.008600653149187565,
-0.0751769170165062,
0.007157966960221529,
-0.010349872522056103,
0.06228027120232582,
0.07416076213121414,
0.023152993991971016,
-0.050502710044384,
0.02431231550872326,
-0.014113523066043854,
-0.12686440348625183,
0.0414765328168869,
-0.013578114099800587,
-0.040865086019039154,
0.19634321331977844,
0.025065679103136063,
0.0008438621880486608,
-0.015283580869436264,
0.2330462485551834,
-0.06837407499551773,
-0.08385100960731506,
-0.13369156420230865,
0.05355008319020271,
-0.06361609697341919,
0.02434631623327732,
0.024886183440685272,
-0.10945887118577957,
0.015274260193109512,
0.15641985833644867,
0.1469704508781433,
-0.0210683923214674,
0.010695376433432102,
0.03625712916254997,
0.0054151699878275394,
-0.044735491275787354,
0.019756468012928963,
0.041862256824970245,
0.17302173376083374,
-0.06642885506153107,
0.08851856738328934,
0.015724120661616325,
-0.09131169319152832,
-0.004371588584035635,
0.08552920818328857,
-0.026815932244062424,
0.043405547738075256,
-0.07227680832147598,
0.12302740663290024,
-0.07759073376655579,
-0.2301245927810669,
0.03242829814553261,
-0.06911255419254303,
-0.1213684231042862,
-0.030683457851409912,
0.042058832943439484,
-0.013241901062428951,
0.016053473576903343,
0.08648666739463806,
-0.028633546084165573,
0.17428931593894958,
0.027320576831698418,
-0.07319273054599762,
-0.04112134128808975,
0.05919177085161209,
-0.12016452848911285,
0.2961375415325165,
0.0057159005664289,
0.04355718195438385,
0.11353806406259537,
-0.021398240700364113,
-0.15568998456001282,
-0.014709829352796078,
0.0977022722363472,
-0.08142223209142685,
0.07461071759462357,
0.21640299260616302,
-0.011462527327239513,
0.11084781587123871,
0.06922407448291779,
-0.07168732583522797,
0.028895165771245956,
-0.06540285050868988,
-0.0845891535282135,
-0.11322290450334549,
0.08100200444459915,
-0.0810452401638031,
0.16764654219150543,
0.10923725366592407,
-0.06698185205459595,
0.00631897896528244,
-0.02422751858830452,
0.06645002961158752,
-0.009003838524222374,
0.12591047585010529,
-0.002101090969517827,
-0.20487265288829803,
0.04100646451115608,
0.04141320660710335,
0.11466335505247116,
-0.20673632621765137,
-0.07495803385972977,
0.05126289278268814,
-0.009052442386746407,
-0.0788300558924675,
0.1133040115237236,
0.05219925194978714,
0.012903459370136261,
-0.041713688522577286,
-0.07311321794986725,
-0.011673279106616974,
0.1296810805797577,
-0.11166002601385117,
-0.02372674085199833
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tinystories_1layer_attn_mlp_C10k_k16
This model is a fine-tuned version of [roneneldan/TinyStories-1Layer-21M](https://huggingface.co/roneneldan/TinyStories-1Layer-21M) on the roneneldan/TinyStories dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1329
- Accuracy: 0.5091
- Multicode K: 1
- Dead Code Fraction/layer0: 0.1880
- Mse/layer0: 604.5097
- Input Norm/layer0: 31.9987
- Output Norm/layer0: 19.3897
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Multicode K | Dead Code Fraction/layer0 | Mse/layer0 | Input Norm/layer0 | Output Norm/layer0 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------:|:-------------------------:|:----------:|:-----------------:|:------------------:|
| 3.0494 | 0.05 | 500 | 2.9927 | 0.4177 | 1 | 0.0 | 805.1676 | 31.9986 | 10.3600 |
| 2.6986 | 0.1 | 1000 | 2.7080 | 0.4472 | 1 | 0.0084 | 739.3244 | 31.9985 | 12.7165 |
| 2.5145 | 0.15 | 1500 | 2.5252 | 0.4637 | 1 | 0.0546 | 697.1179 | 31.9984 | 14.4889 |
| 2.4197 | 0.2 | 2000 | 2.4093 | 0.4758 | 1 | 0.0988 | 670.0254 | 31.9983 | 15.7288 |
| 2.3541 | 0.25 | 2500 | 2.3404 | 0.4837 | 1 | 0.1337 | 651.1297 | 31.9983 | 16.6602 |
| 2.2742 | 0.3 | 3000 | 2.2907 | 0.4903 | 1 | 0.1499 | 642.6360 | 31.9983 | 17.3243 |
| 2.2488 | 0.35 | 3500 | 2.2565 | 0.4945 | 1 | 0.1575 | 640.3158 | 31.9983 | 17.7566 |
| 2.2287 | 0.4 | 4000 | 2.2333 | 0.4967 | 1 | 0.1613 | 638.8423 | 31.9983 | 18.0223 |
| 2.2576 | 0.45 | 4500 | 2.2155 | 0.4992 | 1 | 0.1676 | 639.7464 | 31.9983 | 18.1919 |
| 2.1901 | 1.02 | 5000 | 2.2026 | 0.5014 | 1 | 0.1696 | 638.1766 | 31.9984 | 18.3119 |
| 2.1686 | 1.07 | 5500 | 2.1935 | 0.5026 | 1 | 0.1716 | 638.6084 | 31.9984 | 18.4013 |
| 2.2158 | 1.12 | 6000 | 2.1833 | 0.5037 | 1 | 0.1779 | 632.9326 | 31.9985 | 18.5149 |
| 2.1843 | 1.17 | 6500 | 2.1760 | 0.5039 | 1 | 0.1797 | 631.2925 | 31.9985 | 18.5986 |
| 2.1339 | 1.22 | 7000 | 2.1696 | 0.5048 | 1 | 0.1819 | 627.9791 | 31.9985 | 18.7053 |
| 2.187 | 1.27 | 7500 | 2.1584 | 0.5063 | 1 | 0.1867 | 622.1227 | 31.9986 | 18.8338 |
| 2.1302 | 1.32 | 8000 | 2.1508 | 0.5071 | 1 | 0.1875 | 617.7162 | 31.9986 | 18.9493 |
| 2.1471 | 1.37 | 8500 | 2.1444 | 0.5082 | 1 | 0.1885 | 613.7248 | 31.9986 | 19.0666 |
| 2.1556 | 1.42 | 9000 | 2.1392 | 0.5087 | 1 | 0.1880 | 610.3757 | 31.9987 | 19.1817 |
| 2.1067 | 1.47 | 9500 | 2.1351 | 0.5091 | 1 | 0.1875 | 608.6866 | 31.9987 | 19.2836 |
| 2.1536 | 2.04 | 10000 | 2.1329 | 0.5091 | 1 | 0.1880 | 604.5097 | 31.9987 | 19.3897 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"tags": ["generated_from_trainer"], "datasets": ["roneneldan/TinyStories"], "metrics": ["accuracy"], "base_model": "roneneldan/TinyStories-1Layer-21M", "model-index": [{"name": "tinystories_1layer_attn_mlp_C10k_k16", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "roneneldan/TinyStories", "type": "roneneldan/TinyStories"}, "metrics": [{"type": "accuracy", "value": 0.5091345939349958, "name": "Accuracy"}]}]}]} | null | empty-michael/tinystories_1layer_attn_mlp_C10k_k16 | [
"transformers",
"safetensors",
"codebook",
"generated_from_trainer",
"dataset:roneneldan/TinyStories",
"base_model:roneneldan/TinyStories-1Layer-21M",
"model-index",
"endpoints_compatible",
"region:us"
] | 2024-02-11T05:52:11+00:00 | [] | [] | TAGS
#transformers #safetensors #codebook #generated_from_trainer #dataset-roneneldan/TinyStories #base_model-roneneldan/TinyStories-1Layer-21M #model-index #endpoints_compatible #region-us
| tinystories\_1layer\_attn\_mlp\_C10k\_k16
=========================================
This model is a fine-tuned version of roneneldan/TinyStories-1Layer-21M on the roneneldan/TinyStories dataset.
It achieves the following results on the evaluation set:
* Loss: 2.1329
* Accuracy: 0.5091
* Multicode K: 1
* Dead Code Fraction/layer0: 0.1880
* Mse/layer0: 604.5097
* Input Norm/layer0: 31.9987
* Output Norm/layer0: 19.3897
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0005
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 6
* total\_train\_batch\_size: 96
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* lr\_scheduler\_warmup\_ratio: 0.05
* training\_steps: 10000
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 6\n* total\\_train\\_batch\\_size: 96\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* training\\_steps: 10000",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #safetensors #codebook #generated_from_trainer #dataset-roneneldan/TinyStories #base_model-roneneldan/TinyStories-1Layer-21M #model-index #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 6\n* total\\_train\\_batch\\_size: 96\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* training\\_steps: 10000",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
68,
143,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #codebook #generated_from_trainer #dataset-roneneldan/TinyStories #base_model-roneneldan/TinyStories-1Layer-21M #model-index #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 6\n* total\\_train\\_batch\\_size: 96\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* training\\_steps: 10000### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.1427208036184311,
0.0928536206483841,
-0.0015165897784754634,
0.08736862987279892,
0.14331917464733124,
0.023079343140125275,
0.11496444791555405,
0.12609268724918365,
-0.1296195685863495,
0.06880030035972595,
0.10729473829269409,
0.07446970045566559,
0.034057047218084335,
0.13748157024383545,
-0.02492658421397209,
-0.2932393252849579,
-0.0006850690697319806,
0.03176175057888031,
-0.16296768188476562,
0.1341649442911148,
0.10501854866743088,
-0.13349094986915588,
0.06188073754310608,
0.021184440702199936,
-0.17486560344696045,
-0.0204275194555521,
0.0035872419830411673,
-0.06924527138471603,
0.12227379530668259,
0.005048343911767006,
0.13170123100280762,
0.02206193096935749,
0.1116531491279602,
-0.16663934290409088,
0.003742594737559557,
0.0760497897863388,
0.03534633666276932,
0.103624626994133,
0.07383224368095398,
-0.007223800756037235,
0.11977588385343552,
-0.07846616953611374,
0.0771399438381195,
0.038534797728061676,
-0.11868589371442795,
-0.2936166822910309,
-0.09597252309322357,
0.10686114430427551,
0.11891821026802063,
0.07926082611083984,
-0.010992521420121193,
0.12241638451814651,
-0.07727458328008652,
0.08771038055419922,
0.2575841248035431,
-0.264460951089859,
-0.09444991499185562,
0.03419385850429535,
0.06244109198451042,
0.02615269087255001,
-0.12429973483085632,
-0.030395111069083214,
0.04911570996046066,
0.029942765831947327,
0.12244575470685959,
0.0077237519435584545,
-0.002444346435368061,
0.006352856755256653,
-0.13839247822761536,
-0.04908985272049904,
0.1041133776307106,
0.048685796558856964,
-0.04810893535614014,
-0.07920894026756287,
-0.05394892767071724,
-0.2198343724012375,
-0.043643493205308914,
-0.002096504671499133,
0.026887046173214912,
-0.0704030990600586,
-0.12843050062656403,
0.01766837388277054,
-0.09454387426376343,
-0.10397537052631378,
0.027722490951418877,
0.20352081954479218,
0.05319840833544731,
-0.002289779484272003,
-0.02611999213695526,
0.13985134661197662,
0.04767604544758797,
-0.16909873485565186,
0.010354789905250072,
0.013267727568745613,
-0.029709618538618088,
-0.01625419408082962,
-0.048848435282707214,
-0.0031734418589621782,
-0.002788185141980648,
0.14660118520259857,
-0.09242497384548187,
0.018809620290994644,
0.055089425295591354,
0.02185944840312004,
-0.09779052436351776,
0.17848339676856995,
-0.0868491530418396,
-0.03989754617214203,
-0.012850018218159676,
0.1273372918367386,
0.033567752689123154,
-0.0005690930993296206,
-0.06986527889966965,
0.011454710736870766,
0.1179632842540741,
0.05575818940997124,
-0.01741158217191696,
0.039344657212495804,
-0.035880155861377716,
-0.020287055522203445,
0.06577835977077484,
-0.0814819186925888,
0.027539687231183052,
0.009875603020191193,
-0.093332938849926,
-0.030225951224565506,
0.004722116980701685,
0.011037462390959263,
0.009640300646424294,
0.15143641829490662,
-0.11145686358213425,
-0.015388463623821735,
-0.10856721550226212,
-0.09940771013498306,
0.004387720953673124,
-0.041865184903144836,
0.0032310890965163708,
-0.07270010560750961,
-0.13851788640022278,
-0.023137176409363747,
0.028849173337221146,
-0.03998667001724243,
-0.06678109616041183,
-0.016477061435580254,
-0.13576927781105042,
0.027743201702833176,
0.00177243840880692,
0.14283621311187744,
-0.03736152872443199,
0.13489359617233276,
0.06829281151294708,
0.052464015781879425,
0.043802618980407715,
0.037481747567653656,
-0.09402017295360565,
0.04919546842575073,
-0.19987794756889343,
0.017924105748534203,
-0.0644998550415039,
0.058357518166303635,
-0.09742729365825653,
-0.143999382853508,
0.026995908468961716,
-0.010778951458632946,
0.0970960259437561,
0.13285478949546814,
-0.14218385517597198,
-0.08641616255044937,
0.16941776871681213,
-0.10413183271884918,
-0.12730462849140167,
0.1013922244310379,
-0.0172781590372324,
-0.009817617945373058,
0.02886291779577732,
0.10630343854427338,
0.07930628210306168,
-0.07536567002534866,
-0.032195910811424255,
-0.0469699390232563,
0.11808676272630692,
-0.012076347135007381,
0.10127712786197662,
0.0001989877491723746,
0.03600086644291878,
0.015347549691796303,
-0.07418037205934525,
0.03421930596232414,
-0.1198313906788826,
-0.0859973207116127,
-0.04198027774691582,
-0.1020248532295227,
0.07987182587385178,
0.08548548072576523,
0.053649064153432846,
-0.10202443599700928,
-0.1325303614139557,
0.048700109124183655,
0.12574981153011322,
-0.06569425761699677,
0.010603513568639755,
-0.06457137316465378,
0.07860417664051056,
-0.05729639530181885,
-0.031086988747119904,
-0.17346547544002533,
-0.07056047022342682,
0.025671333074569702,
-0.02661392278969288,
-0.03808639943599701,
-0.04191436991095543,
0.08546493947505951,
0.09579308331012726,
-0.08789122104644775,
-0.07877176254987717,
-0.1093599870800972,
-0.01456625945866108,
-0.09250259399414062,
-0.22198353707790375,
-0.1106719821691513,
-0.015302890911698341,
0.15440000593662262,
-0.22502847015857697,
0.03990902751684189,
0.003970857709646225,
0.14267101883888245,
0.04547465220093727,
-0.04069756343960762,
-0.017060738056898117,
0.07552860677242279,
-0.029863271862268448,
-0.0710531622171402,
0.032956380397081375,
0.0012123447377234697,
-0.08350325375795364,
-0.043385397642850876,
-0.10206148773431778,
0.15040777623653412,
0.11483018100261688,
0.002948116511106491,
-0.1129549965262413,
0.014061725698411465,
-0.10655707865953445,
-0.039317645132541656,
-0.03353830799460411,
-0.0026832714211195707,
0.08680707961320877,
0.03252439573407173,
0.13041584193706512,
-0.08020678162574768,
-0.07084659487009048,
0.039797093719244,
-0.010002939961850643,
0.0030750941950827837,
0.11480752378702164,
0.06378575414419174,
-0.022090336307883263,
0.13651549816131592,
0.11249257624149323,
-0.0831790491938591,
0.1295938342809677,
-0.07920429110527039,
-0.09474200755357742,
-0.031101077795028687,
-0.0032030893489718437,
0.03807775676250458,
0.1596013456583023,
-0.0775018110871315,
-0.010468847118318081,
0.02220463566482067,
-0.008190188556909561,
0.01611928641796112,
-0.20957612991333008,
-0.03072412870824337,
0.029416438192129135,
-0.03172522038221359,
-0.018130585551261902,
-0.015093371272087097,
0.012212231755256653,
0.10276545584201813,
0.007573721930384636,
-0.029629217460751534,
0.0031130528077483177,
0.004753184504806995,
-0.05634910613298416,
0.22618846595287323,
-0.06477365642786026,
-0.10604535788297653,
-0.14339931309223175,
0.052183981984853745,
-0.05443239584565163,
-0.00948934443295002,
0.030826985836029053,
-0.09915557503700256,
-0.013822183944284916,
-0.05761626362800598,
0.04819132015109062,
-0.010141021572053432,
0.03641188517212868,
-0.018388288095593452,
0.023841632530093193,
0.07195461541414261,
-0.12572604417800903,
0.028331100940704346,
-0.030761174857616425,
-0.07173223048448563,
0.026793545112013817,
0.06349815428256989,
0.11156251281499863,
0.15850140154361725,
-0.003981476649641991,
0.001335806562565267,
-0.028384899720549583,
0.18641436100006104,
-0.10070398449897766,
-0.02048688940703869,
0.14964048564434052,
0.020254982635378838,
0.05217835307121277,
0.12276909500360489,
0.06563150137662888,
-0.07288464158773422,
0.011836974881589413,
0.03656035661697388,
-0.011488928459584713,
-0.2115372270345688,
-0.027212979272007942,
-0.0274808369576931,
0.006669946480542421,
0.09494884312152863,
0.021370412781834602,
0.01938004232943058,
0.07099730521440506,
-0.038754187524318695,
0.023232270032167435,
-0.05578233301639557,
0.08585502952337265,
0.03535287454724312,
0.05448516830801964,
0.1344396322965622,
-0.02970203012228012,
-0.05264557898044586,
0.017945200204849243,
-0.03145478665828705,
0.2106904238462448,
-0.06345292180776596,
0.11603541672229767,
0.04637392982840538,
0.17587614059448242,
0.006773447152227163,
0.09779130667448044,
0.004587813280522823,
-0.04138965904712677,
0.026442069560289383,
-0.06167450547218323,
-0.030262263491749763,
0.017521556466817856,
-0.023635102435946465,
0.1120404601097107,
-0.14974868297576904,
-0.0010311417281627655,
0.042423315346241,
0.3176218569278717,
0.07321605086326599,
-0.32419759035110474,
-0.138931006193161,
0.00010303646558895707,
-0.04219553619623184,
-0.0416065976023674,
0.01061533484607935,
0.13261553645133972,
-0.10863595455884933,
0.03191738575696945,
-0.0904303640127182,
0.06704594194889069,
-0.035136133432388306,
0.0040921662002801895,
0.08836092799901962,
0.09154655784368515,
-0.006715493276715279,
0.059014130383729935,
-0.2194989174604416,
0.30516383051872253,
0.00046415746328420937,
0.08946186304092407,
-0.04262220114469528,
0.02720935083925724,
0.02510744333267212,
0.03505585715174675,
0.06826917082071304,
-0.017315905541181564,
-0.018663356080651283,
-0.21600569784641266,
-0.07448412477970123,
0.013043462298810482,
0.13503015041351318,
-0.10918860882520676,
0.142440527677536,
-0.02933075651526451,
-0.02469303086400032,
0.05290646106004715,
-0.0591571107506752,
-0.07664243876934052,
-0.06301698833703995,
0.02368047647178173,
-0.03233569860458374,
0.03472321107983589,
-0.1331157386302948,
-0.13131831586360931,
-0.026353178545832634,
0.14868046343326569,
-0.07680072635412216,
-0.06176472827792168,
-0.13706545531749725,
0.09433876723051071,
0.1654699146747589,
-0.07686979323625565,
0.0659388080239296,
0.002686527092009783,
0.1363891065120697,
0.01893439330160618,
-0.019674044102430344,
0.08935816586017609,
-0.08811002224683762,
-0.27187636494636536,
-0.05372493341565132,
0.1663394570350647,
0.023533502593636513,
0.05626297742128372,
-0.03199402242898941,
0.04599889740347862,
-0.006251951213926077,
-0.0846172645688057,
0.022936062887310982,
-0.02487189695239067,
0.06599704921245575,
0.019678296521306038,
-0.028709175065159798,
0.02892252802848816,
-0.04337923228740692,
-0.03018556721508503,
0.10400800406932831,
0.28809019923210144,
-0.10663153976202011,
-0.020142007619142532,
0.06138116493821144,
-0.020342808216810226,
-0.1614188253879547,
0.041121628135442734,
0.10889091342687607,
0.017251256853342056,
0.012129346840083599,
-0.1682458072900772,
0.09659277647733688,
0.08794926851987839,
-0.04136419668793678,
0.1054219976067543,
-0.3174614906311035,
-0.1284540295600891,
0.08076886832714081,
0.14426645636558533,
-0.010534805245697498,
-0.18509933352470398,
-0.054972413927316666,
0.0003896755224559456,
-0.13757027685642242,
0.0965939462184906,
-0.05156590789556503,
0.10130331665277481,
-0.03449876233935356,
0.04863034188747406,
0.02673615887761116,
-0.07195471227169037,
0.12816974520683289,
-0.025346677750349045,
0.08634641766548157,
-0.014668766409158707,
-0.043707333505153656,
0.11021697521209717,
-0.05219544470310211,
0.002198521513491869,
-0.04261365532875061,
0.05824848264455795,
-0.0986405536532402,
-0.009679066017270088,
-0.12367493659257889,
0.03573448956012726,
-0.07562904804944992,
-0.0797441154718399,
-0.021718157455325127,
0.059946030378341675,
0.013052289374172688,
-0.032499153167009354,
0.13264796137809753,
0.027682485058903694,
0.22052118182182312,
0.09716156870126724,
0.061130963265895844,
0.00022795534459874034,
-0.0681326687335968,
0.00023525732103735209,
-0.020272575318813324,
0.06555870920419693,
-0.15111222863197327,
0.003884339239448309,
0.12664920091629028,
0.08329649269580841,
0.09578403830528259,
0.07274699211120605,
-0.060866039246320724,
0.0062814028933644295,
0.08716686069965363,
-0.14390067756175995,
-0.09953535348176956,
-0.03348235785961151,
-0.0033263221848756075,
-0.17708982527256012,
0.08171175420284271,
0.08942249417304993,
-0.08681795746088028,
-0.028607796877622604,
-0.008255038410425186,
0.010090570896863937,
-0.021116144955158234,
0.22544708847999573,
0.08420906960964203,
0.10432098060846329,
-0.09389691799879074,
0.07477806508541107,
0.04499118775129318,
-0.11933844536542892,
-0.009000282734632492,
0.09169396758079529,
-0.06460365653038025,
-0.011782103218138218,
0.045167502015829086,
0.0681045651435852,
-0.03902518376708031,
-0.03193504363298416,
-0.16594181954860687,
-0.12410809099674225,
0.047064609825611115,
0.14494843780994415,
0.0716811940073967,
0.03725602105259895,
-0.011961055919528008,
0.049882546067237854,
-0.14991405606269836,
0.13477957248687744,
0.07296713441610336,
0.1016014963388443,
-0.1590171903371811,
0.19196510314941406,
-0.0013365151826292276,
0.023383760824799538,
-0.004544202703982592,
0.03839836269617081,
-0.10830473899841309,
-0.0016795062692835927,
-0.09979812800884247,
-0.06425579637289047,
-0.03683732450008392,
-0.014589156024158001,
-0.017878083512187004,
-0.05707336217164993,
-0.059387482702732086,
0.025752831250429153,
-0.10971939563751221,
-0.048916302621364594,
0.007309883367270231,
0.028876708820462227,
-0.12996730208396912,
0.002767542377114296,
0.045193228870630264,
-0.11225279420614243,
0.08658892661333084,
0.036302026361227036,
0.061559390276670456,
0.04351304471492767,
-0.055650025606155396,
0.017979253083467484,
0.016311582177877426,
-0.027212686836719513,
0.0532345212996006,
-0.11976342648267746,
-0.0013006580993533134,
-0.05392713472247124,
0.0370226614177227,
0.00471116229891777,
0.05074775218963623,
-0.15426872670650482,
-0.007754310499876738,
0.006572543643414974,
-0.036421384662389755,
-0.06558121740818024,
0.02653515711426735,
0.08360546827316284,
0.0017856742488220334,
0.16569817066192627,
-0.06867902725934982,
0.04632985219359398,
-0.23411749303340912,
-0.01262479368597269,
-0.03839752823114395,
-0.09488602727651596,
-0.10369598120450974,
0.0023597029503434896,
0.07665007561445236,
-0.05371939018368721,
0.06704661250114441,
-0.040583692491054535,
0.11093387007713318,
0.04265524074435234,
-0.056894633919000626,
0.04133264720439911,
0.05432044342160225,
0.20766696333885193,
0.03615161404013634,
-0.031383972615003586,
0.05947268009185791,
0.03498215600848198,
0.058403074741363525,
0.08380220830440521,
0.1897994577884674,
0.12569020688533783,
-0.0029247503262013197,
0.08545498549938202,
0.054891426116228104,
-0.0869484543800354,
-0.1766701340675354,
0.020183591172099113,
-0.02866048365831375,
0.09494864195585251,
-0.028734609484672546,
0.19014079868793488,
0.1284549981355667,
-0.18478016555309296,
0.035088468343019485,
-0.04770935699343681,
-0.07069061696529388,
-0.07724463194608688,
-0.0005874586058780551,
-0.05958721786737442,
-0.16453677415847778,
0.014516535215079784,
-0.12984305620193481,
0.005271578673273325,
0.10069485008716583,
0.00788656622171402,
0.0032435068860650063,
0.18824750185012817,
0.0634949803352356,
0.03936341404914856,
0.08104729652404785,
0.04469269514083862,
-0.006016010418534279,
-0.03054700791835785,
-0.07709376513957977,
-0.007159472443163395,
-0.030213963240385056,
0.03784759342670441,
-0.06682688742876053,
-0.12823395431041718,
0.05442993342876434,
0.03741549327969551,
-0.11372457444667816,
0.034677546471357346,
-0.004740211181342602,
0.08321423828601837,
0.04950818791985512,
-0.0013635661453008652,
0.026920802891254425,
-0.037120867520570755,
0.2737017273902893,
-0.112966388463974,
-0.07178103923797607,
-0.12471073120832443,
0.28461870551109314,
0.01873808726668358,
-0.040398016571998596,
0.043228209018707275,
-0.11093214899301529,
-0.02385694533586502,
0.1718362420797348,
0.15403702855110168,
-0.00889883004128933,
-0.012285460717976093,
0.03674745559692383,
-0.02542375773191452,
-0.07355037331581116,
0.086836077272892,
0.11223731935024261,
0.09199944138526917,
-0.08736537396907806,
-0.031379397958517075,
-0.03675229102373123,
-0.05621577799320221,
-0.023002270609140396,
0.10122302174568176,
0.01673530600965023,
-0.008552123792469501,
-0.04920465499162674,
0.08205211907625198,
-0.02352670207619667,
-0.14466388523578644,
0.08133859932422638,
-0.21995815634727478,
-0.1830068826675415,
-0.034446172416210175,
0.0761496052145958,
0.0047757248394191265,
0.08784312754869461,
0.018430985510349274,
-0.02109127677977085,
0.08245525509119034,
0.0024655999150127172,
-0.03825851157307625,
-0.13087008893489838,
0.09678521752357483,
-0.08138369023799896,
0.23545010387897491,
-0.05219677463173866,
0.017960725352168083,
0.1358920931816101,
0.02598200924694538,
-0.12488558143377304,
0.019987376406788826,
0.09769989550113678,
-0.12739786505699158,
0.021976394578814507,
0.19036978483200073,
-0.022611692547798157,
0.0799170508980751,
0.016966767609119415,
-0.16703958809375763,
0.01455504260957241,
-0.06053576618432999,
-0.03396418318152428,
-0.06901168823242188,
-0.012831798754632473,
-0.03051784262061119,
0.12870869040489197,
0.23845095932483673,
-0.06587786972522736,
-0.008823822252452374,
-0.06762471795082092,
0.025558197870850563,
0.07716938853263855,
0.09436311572790146,
-0.011944021098315716,
-0.2799100875854492,
0.02755082957446575,
0.05118163675069809,
-0.007441577035933733,
-0.2528579831123352,
-0.07177888602018356,
0.061844244599342346,
-0.06615975499153137,
-0.0890522450208664,
0.08278193324804306,
0.07865016162395477,
0.04891858622431755,
-0.03703828901052475,
-0.03996887803077698,
-0.0874246135354042,
0.17323128879070282,
-0.184309720993042,
-0.08285930007696152
] |
null | null | transformers | # Design Extractor #
Fine-tuned on BERT for design meeting sentence classification.
Trained on a small dataset consisting of six different one-hour meetings between different software engineering groups
(Jolak et al., [2018](https://doi.org/10.1109/MS.2018.290100920)).
---
license: apache-2.0
---
| {} | text-classification | Southstreamer/design_extractor_bert | [
"transformers",
"safetensors",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T05:52:34+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us
| # Design Extractor #
Fine-tuned on BERT for design meeting sentence classification.
Trained on a small dataset consisting of six different one-hour meetings between different software engineering groups
(Jolak et al., 2018).
---
license: apache-2.0
---
| [
"# Design Extractor #\n\nFine-tuned on BERT for design meeting sentence classification. \nTrained on a small dataset consisting of six different one-hour meetings between different software engineering groups \n(Jolak et al., 2018).\n\n---\nlicense: apache-2.0\n---"
] | [
"TAGS\n#transformers #safetensors #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us \n",
"# Design Extractor #\n\nFine-tuned on BERT for design meeting sentence classification. \nTrained on a small dataset consisting of six different one-hour meetings between different software engineering groups \n(Jolak et al., 2018).\n\n---\nlicense: apache-2.0\n---"
] | [
37,
59
] | [
"passage: TAGS\n#transformers #safetensors #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us \n# Design Extractor #\n\nFine-tuned on BERT for design meeting sentence classification. \nTrained on a small dataset consisting of six different one-hour meetings between different software engineering groups \n(Jolak et al., 2018).\n\n---\nlicense: apache-2.0\n---"
] | [
-0.0063800751231610775,
0.013178927823901176,
-0.0010975068435072899,
0.02809162065386772,
0.08557765930891037,
-0.0725787803530693,
0.16375406086444855,
0.01773730479180813,
-0.03322986513376236,
-0.0018095395062118769,
0.11348922550678253,
0.1400706022977829,
-0.004763436503708363,
0.14472775161266327,
-0.1152058020234108,
-0.1855570673942566,
0.10526785254478455,
0.059198684990406036,
0.04926087334752083,
0.1000586524605751,
0.1583111584186554,
-0.09882292151451111,
0.04742859676480293,
0.04716489464044571,
-0.11623584479093552,
0.0006567039526998997,
0.0009753596968948841,
-0.10506710410118103,
0.0874096006155014,
0.09094490855932236,
0.17055130004882812,
0.09200157225131989,
-0.05903825908899307,
-0.13121777772903442,
0.030560022220015526,
-0.02914566360414028,
-0.025734644383192062,
0.02293355204164982,
0.05101919546723366,
-0.04635041207075119,
-0.04304318130016327,
-0.01062336191534996,
0.019555462524294853,
0.07215861976146698,
-0.10506793111562729,
0.07891713082790375,
-0.019466126337647438,
-0.029842255637049675,
0.16571806371212006,
0.0613284632563591,
-0.0185809675604105,
0.08086831122636795,
-0.08540350943803787,
0.10734289139509201,
0.07453083246946335,
-0.32312777638435364,
-0.08823235332965851,
0.021454105153679848,
0.10496982932090759,
-0.04071146994829178,
-0.039107002317905426,
0.03063300997018814,
0.054174650460481644,
-0.012372154742479324,
0.030287165194749832,
-0.08244401216506958,
-0.17261424660682678,
-0.02738530933856964,
-0.10783734917640686,
0.074672169983387,
0.34917569160461426,
0.05841612443327904,
-0.015797385945916176,
-0.09212537109851837,
-0.018012285232543945,
0.055924590677022934,
-0.019151339307427406,
-0.05053994059562683,
-0.04012264683842659,
0.0010798658477142453,
-0.028490006923675537,
0.004856569692492485,
-0.14828139543533325,
-0.045118048787117004,
-0.1090438961982727,
0.12474537640810013,
-0.03715271130204201,
-0.01539985928684473,
-0.1612035632133484,
-0.0020171566866338253,
-0.007005595602095127,
-0.07672809064388275,
-0.0048933872021734715,
-0.08311706781387329,
-0.0038627805188298225,
-0.05588076636195183,
-0.03321437910199165,
-0.09472820907831192,
0.12191201001405716,
0.055963288992643356,
0.12784363329410553,
0.03431585431098938,
-0.005893092602491379,
0.00912055466324091,
0.022268695756793022,
0.18954555690288544,
0.07940654456615448,
-0.0726509541273117,
0.020353225991129875,
-0.01508906576782465,
-0.00554811954498291,
-0.009371908381581306,
-0.09738795459270477,
-0.00464254803955555,
0.016750860959291458,
0.03480849042534828,
-0.03383682668209076,
0.14557011425495148,
-0.05773760750889778,
0.034012552350759506,
0.0025831449311226606,
-0.06242026761174202,
-0.01688726618885994,
0.018706945702433586,
0.09139297157526016,
-0.07727634906768799,
0.005420258734375238,
0.07108316570520401,
-0.016231095418334007,
-0.021952904760837555,
-0.04468752071261406,
-0.08428032696247101,
-0.03070972114801407,
-0.09627608954906464,
-0.018368005752563477,
0.005061807576566935,
0.010777346789836884,
-0.15908943116664886,
-0.08348014950752258,
-0.018795643001794815,
0.038863737136125565,
0.0072653042152523994,
-0.04751317948102951,
-0.08796637505292892,
0.021636998280882835,
0.009242270141839981,
-0.07350433617830276,
-0.03926935791969299,
-0.06373538821935654,
0.05282389745116234,
-0.020805511623620987,
0.047813232988119125,
-0.16266542673110962,
0.08433897793292999,
-0.07939682900905609,
-0.035523559898138046,
-0.06290202587842941,
0.08845233172178268,
-0.04350478574633598,
0.178453266620636,
-0.06463516503572464,
0.017163069918751717,
0.06323890388011932,
0.07591067254543304,
-0.06265786290168762,
0.16801652312278748,
-0.06779472529888153,
-0.043449219316244125,
0.09900417923927307,
-0.08118358254432678,
-0.1753324270248413,
0.05399150028824806,
-0.02636529505252838,
0.20447510480880737,
0.18153637647628784,
0.1792846918106079,
0.10031118243932724,
0.052095331251621246,
0.024024879559874535,
0.06700988113880157,
-0.013744213618338108,
-0.0749903991818428,
0.045759860426187515,
0.05834798514842987,
-0.18152053654193878,
0.045551907271146774,
-0.04107849299907684,
0.001995441038161516,
-0.011976554058492184,
-0.06257012486457825,
0.052045855671167374,
-0.030594075098633766,
0.02680196240544319,
-0.01431955024600029,
0.05508801341056824,
-0.09873387217521667,
-0.01997699961066246,
0.08749924600124359,
0.0038658606354147196,
-0.05055072903633118,
-0.04306140914559364,
-0.05993550270795822,
0.019802160561084747,
0.01874460279941559,
0.029359107837080956,
-0.14634913206100464,
-0.07774549722671509,
-0.004915053956210613,
0.11142455041408539,
0.013760962523519993,
0.19799119234085083,
0.049223367124795914,
-0.026815736666321754,
0.023219864815473557,
-0.029480382800102234,
0.10387572646141052,
0.04063233733177185,
-0.05190557613968849,
-0.10434423387050629,
0.07687754929065704,
-0.09421022236347198,
0.02795616164803505,
-0.09143488109111786,
0.018860649317502975,
0.0551622100174427,
0.0024242536164820194,
0.04757760465145111,
0.046553097665309906,
0.010963036678731441,
-0.00528355548158288,
-0.05935202166438103,
0.055920109152793884,
0.1117994412779808,
0.025320878252387047,
-0.09046241641044617,
0.12638424336910248,
-0.10785863548517227,
0.08001416176557541,
0.09542229771614075,
-0.13940361142158508,
-0.017858531326055527,
-0.10602493584156036,
-0.04711103066802025,
0.020506668835878372,
-0.008013548329472542,
-0.06997523456811905,
0.18813979625701904,
-0.049360789358615875,
0.12146735936403275,
-0.05116375535726547,
-0.033094439655542374,
-0.04355897009372711,
-0.03310370072722435,
-0.05675434693694115,
0.13033773005008698,
-0.05539000406861305,
-0.198562353849411,
0.14891116321086884,
0.1870032250881195,
-0.048529043793678284,
0.20956313610076904,
-0.003873375942930579,
0.04361031949520111,
0.06408800929784775,
0.07503539323806763,
-0.016634095460176468,
-0.02603253908455372,
-0.18605656921863556,
-0.07406672835350037,
0.06449887901544571,
-0.023296089842915535,
-0.004927588161081076,
-0.11746962368488312,
-0.014798510819673538,
0.003464232664555311,
0.00031033859704621136,
-0.030957220122218132,
0.013475564308464527,
-0.043004050850868225,
0.0774383619427681,
0.02636478655040264,
-0.13855457305908203,
0.049633558839559555,
-0.05171968415379524,
-0.09921754151582718,
0.1749756783246994,
-0.0497594028711319,
-0.29492661356925964,
-0.13855203986167908,
-0.14218547940254211,
-0.0947730764746666,
0.040751148015260696,
0.15481160581111908,
-0.14667710661888123,
-0.0665808692574501,
-0.05410508066415787,
0.030434096232056618,
0.04438156634569168,
0.03662208467721939,
0.04674817994236946,
0.021682923659682274,
-0.028016073629260063,
-0.11258197575807571,
-0.06090841442346573,
-0.04507037624716759,
0.017793433740735054,
0.06813561171293259,
-0.11540763825178146,
0.09884702414274216,
0.05917956680059433,
0.006591004319489002,
0.028774553909897804,
-0.0746016576886177,
0.16693930327892303,
-0.0012331691104918718,
-0.027211135253310204,
0.15801465511322021,
-0.08426079899072647,
0.038711100816726685,
0.202259361743927,
-0.022621164098381996,
-0.06663435697555542,
0.08343996107578278,
-0.027293162420392036,
-0.045338187366724014,
-0.1820186972618103,
-0.06288562715053558,
-0.09128465503454208,
0.08167868852615356,
0.04729108884930611,
0.01394795160740614,
-0.00947723537683487,
0.06314048916101456,
-0.00996551476418972,
-0.008819072507321835,
0.13329057395458221,
0.07464690506458282,
0.08727533370256424,
-0.04894382134079933,
0.14396734535694122,
-0.05429140105843544,
-0.13111242651939392,
0.018789760768413544,
-0.021080130711197853,
0.026990318670868874,
0.14035965502262115,
0.09433392435312271,
0.049181681126356125,
-0.0927155613899231,
0.10587286949157715,
0.13157087564468384,
-0.030702762305736542,
-0.033855706453323364,
-0.03358963131904602,
-0.09019823372364044,
-0.09223476052284241,
0.1027534082531929,
-0.015027671121060848,
-0.030860120430588722,
-0.047916654497385025,
-0.07972224056720734,
0.060364093631505966,
0.24479492008686066,
0.12859517335891724,
-0.23013566434383392,
-0.03993823379278183,
0.11933524161577225,
-0.0862494632601738,
-0.11554565280675888,
0.06730999797582626,
0.0022742627188563347,
-0.019214684143662453,
0.07107214629650116,
-0.02520001493394375,
0.12583723664283752,
-0.06316282600164413,
0.0726625993847847,
-0.140508770942688,
-0.10594671219587326,
0.012411173433065414,
0.08826855570077896,
-0.25380152463912964,
0.2017979472875595,
0.017874877899885178,
0.02770078368484974,
-0.04051392897963524,
0.023955168202519417,
0.0018228519475087523,
0.08349920064210892,
0.12705442309379578,
-0.053876958787441254,
0.0048223636113107204,
-0.03737592324614525,
-0.07792625576257706,
0.09486106783151627,
0.006495223846286535,
-0.08455303311347961,
0.013592966832220554,
-0.07120310515165329,
-0.002048955298960209,
0.015435623936355114,
-0.10303673893213272,
-0.06831958144903183,
-0.09833966940641403,
0.02204127050936222,
0.06005834415555,
0.21974241733551025,
-0.003205470507964492,
-0.030029118061065674,
-0.09521358460187912,
0.2097521275281906,
-0.13384214043617249,
-0.02373531274497509,
-0.11511480063199997,
-0.06488253176212311,
-0.10257857292890549,
-0.03673582896590233,
0.04034258425235748,
-0.08780145645141602,
0.0461244061589241,
-0.03234633803367615,
-0.08079452812671661,
0.07770216464996338,
-0.10151097923517227,
0.036127690225839615,
-0.0736888200044632,
0.10345831513404846,
-0.018899906426668167,
0.0024628026876598597,
0.05837776139378548,
-0.002749426756054163,
-0.10454481095075607,
-0.027163607999682426,
-0.011872812174260616,
0.0013847945956513286,
0.11869415640830994,
-0.007218490354716778,
-0.12861068546772003,
-0.214090496301651,
-0.07047636061906815,
0.010381742380559444,
0.2346830815076828,
0.12871740758419037,
-0.04453379288315773,
0.06750036031007767,
0.21549907326698303,
0.03296804800629616,
-0.32355332374572754,
-0.053947437554597855,
0.014572523534297943,
0.020966004580259323,
-0.027499716728925705,
-0.07518503069877625,
0.1235521137714386,
-0.005511630326509476,
-0.027704665437340736,
-0.043232232332229614,
0.06653807312250137,
-0.08055996894836426,
0.1939275711774826,
0.09238798171281815,
0.35083290934562683,
-0.12865190207958221,
-0.054306622594594955,
-0.10736815631389618,
-0.13499407470226288,
0.12520208954811096,
-0.03780684992671013,
0.04590177163481712,
0.061494022607803345,
-0.021415846422314644,
-0.011918356642127037,
-0.01424743514508009,
0.10548386722803116,
-0.05027966946363449,
0.056702494621276855,
-0.07420298457145691,
-0.14046379923820496,
-0.04938522353768349,
-0.05288293957710266,
0.05388755723834038,
-0.12574782967567444,
0.025968143716454506,
-0.073759526014328,
-0.03665180504322052,
-0.025242425501346588,
0.11586325615644455,
0.036044035106897354,
-0.08862779289484024,
0.0020595663227140903,
-0.04519706591963768,
-0.03866664320230484,
0.03109712153673172,
0.3072396218776703,
-0.13887640833854675,
0.08682391047477722,
0.012117314152419567,
0.2475762516260147,
-0.07464879751205444,
-0.01305230613797903,
-0.057567816227674484,
-0.07237657904624939,
0.13906142115592957,
-0.13136500120162964,
0.06966564059257507,
0.08530059456825256,
-0.03284270688891411,
0.13381724059581757,
0.06503014266490936,
0.06629129499197006,
-0.005269027780741453,
0.13731525838375092,
-0.22971588373184204,
-0.05087801441550255,
-0.06244603171944618,
0.06142079457640648,
-0.024090435355901718,
0.14587832987308502,
0.14026996493339539,
0.025121202692389488,
-0.010709240101277828,
-0.013562584295868874,
0.04800140857696533,
0.0027251990977674723,
0.031012775376439095,
-0.05856038257479668,
0.05245828256011009,
-0.08720234036445618,
-0.02491944096982479,
0.06300832331180573,
-0.1338261514902115,
-0.0048396047204732895,
-0.036850228905677795,
-0.1264593005180359,
-0.10409940779209137,
0.07693806290626526,
0.1725948303937912,
-0.022263355553150177,
-0.0280901025980711,
-0.09044480323791504,
-0.16328226029872894,
0.037343788892030716,
0.2923855781555176,
0.06760834902524948,
0.04974304139614105,
-0.00487970095127821,
-0.000961929268669337,
0.06443292647600174,
0.063504658639431,
-0.06157112121582031,
0.016926918178796768,
-0.11003267019987106,
-0.03332514688372612,
-0.0018156975274905562,
0.07487678527832031,
-0.05556989833712578,
-0.05473487451672554,
-0.170695960521698,
0.030585896223783493,
-0.0945795327425003,
0.024735715240240097,
-0.0999012216925621,
0.015469535253942013,
0.005883832462131977,
-0.0288312416523695,
-0.0687781497836113,
-0.03305432200431824,
-0.07649768143892288,
0.0432346947491169,
-0.028568468987941742,
0.13928328454494476,
-0.030813900753855705,
-0.005158553831279278,
0.07360568642616272,
-0.06723323464393616,
0.10188941657543182,
-0.010349562391638756,
-0.05654057860374451,
0.025835836306214333,
-0.15046140551567078,
-0.06032204627990723,
0.1032090112566948,
0.030570516362786293,
0.037950873374938965,
-0.037282176315784454,
-0.04860162362456322,
0.06383948773145676,
0.0295786801725626,
0.00821459386497736,
0.1309673935174942,
-0.07181401550769806,
0.04666751250624657,
-0.05672822892665863,
-0.130198135972023,
-0.045400429517030716,
-0.036801546812057495,
0.13268697261810303,
0.02621515840291977,
0.18997421860694885,
-0.04004174843430519,
0.019174518063664436,
-0.02276613749563694,
0.043322063982486725,
0.00864458829164505,
-0.20877593755722046,
-0.13374358415603638,
-0.14947162568569183,
-0.00047037206240929663,
-0.051517266780138016,
0.08092045038938522,
0.048437368124723434,
-0.01966947130858898,
0.07370074093341827,
-0.019480591639876366,
0.08423475921154022,
0.06725478917360306,
0.2180735468864441,
0.006324164103716612,
0.022078974172472954,
-0.02405322529375553,
0.04863860085606575,
0.027249012142419815,
0.13073565065860748,
0.14185647666454315,
0.10672736912965775,
-0.11461608856916428,
0.12934042513370514,
0.06445007026195526,
0.06850732862949371,
-0.042253464460372925,
-0.10752616077661514,
-0.0065112244337797165,
0.07612576335668564,
-0.018652714788913727,
0.06490962207317352,
0.15196065604686737,
-0.026256725192070007,
-0.009520779363811016,
-0.05855746194720268,
-0.06203773617744446,
-0.12351462244987488,
-0.08130708336830139,
-0.12700554728507996,
-0.01626540906727314,
-0.012487049214541912,
-0.06998284161090851,
-0.04063274338841438,
0.06097542867064476,
0.034239720553159714,
-0.011220697313547134,
0.11342906951904297,
-0.08681940287351608,
-0.037225306034088135,
0.10029708594083786,
-0.0694543793797493,
0.013610178604722023,
-0.0842578113079071,
-0.029059095308184624,
-0.03145010769367218,
0.06126118078827858,
-0.03367243707180023,
0.04735077545046806,
-0.018924113363027573,
-0.0359761081635952,
-0.04030057042837143,
-0.08800642937421799,
-0.04186323285102844,
0.0476798489689827,
-0.013303752057254314,
0.09016337990760803,
0.019226228818297386,
-0.0231894850730896,
0.10101620852947235,
0.1184520497918129,
-0.06349864602088928,
0.00010553810716373846,
-0.1498224139213562,
0.13306786119937897,
-0.04761343076825142,
0.14799688756465912,
-0.026505719870328903,
-0.04641694948077202,
-0.016303561627864838,
0.2949483394622803,
0.1269966959953308,
0.03054898977279663,
0.03830963000655174,
-0.05791706219315529,
0.03468061983585358,
0.026856770738959312,
0.07827229797840118,
0.0034546840470284224,
0.15749818086624146,
-0.019725169986486435,
-0.08738245815038681,
-0.006592921447008848,
-0.027194876223802567,
-0.02832806669175625,
0.03431650251150131,
0.0465911328792572,
-0.009087631478905678,
-0.034754928201436996,
0.10405269265174866,
0.017677681520581245,
-0.029338357970118523,
-0.07244785130023956,
-0.10775230079889297,
-0.08443193137645721,
-0.0021809395402669907,
0.10656575113534927,
-0.04146171733736992,
0.06904730945825577,
-0.03660935163497925,
-0.041638560593128204,
-0.030046703293919563,
-0.024608664214611053,
-0.09066135436296463,
-0.005366602912545204,
0.11226557940244675,
-0.02123257890343666,
0.0493069663643837,
-0.010003740899264812,
0.05488155409693718,
0.07927916198968887,
-0.012674572877585888,
-0.016251472756266594,
0.10544202476739883,
0.015150831080973148,
-0.05199556425213814,
0.07626784592866898,
0.007103960495442152,
-0.062795490026474,
0.15828946232795715,
0.06092487648129463,
-0.17317813634872437,
0.055588483810424805,
0.05417822301387787,
-0.15975862741470337,
-0.06724998354911804,
0.09470391273498535,
-0.052009668201208115,
0.0862293615937233,
0.11220836639404297,
-0.01571982353925705,
-0.049717098474502563,
-0.02438855729997158,
0.028488023206591606,
0.0036119907163083553,
-0.03615431487560272,
-0.10904047638177872,
-0.1689116507768631,
-0.07266033440828323,
-0.009842664934694767,
0.003962521441280842,
-0.22206299006938934,
-0.004583938512951136,
-0.08309277892112732,
0.06730428338050842,
-0.0820493996143341,
0.04349987581372261,
0.17846548557281494,
-0.014472885988652706,
-0.03458520025014877,
-0.1025485247373581,
0.04370017349720001,
0.07816137373447418,
-0.05642814189195633,
-0.11158137023448944
] |
null | null | transformers |
# medical
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
## Example Images
#### adenocarcinoma
#### largecellcarcinoma
#### normal
#### squamouscellcarcinoma
 | {"tags": ["image-classification", "pytorch", "huggingpics"], "metrics": ["accuracy"]} | image-classification | subh71/medical | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"pytorch",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T05:57:03+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #vit #image-classification #pytorch #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# medical
Autogenerated by HuggingPics️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
## Example Images
#### adenocarcinoma
!adenocarcinoma
#### largecellcarcinoma
!largecellcarcinoma
#### normal
!normal
#### squamouscellcarcinoma
!squamouscellcarcinoma | [
"# medical\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the demo at the github repo.",
"## Example Images",
"#### adenocarcinoma\n\n!adenocarcinoma",
"#### largecellcarcinoma\n\n!largecellcarcinoma",
"#### normal\n\n!normal",
"#### squamouscellcarcinoma\n\n!squamouscellcarcinoma"
] | [
"TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #pytorch #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# medical\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the demo at the github repo.",
"## Example Images",
"#### adenocarcinoma\n\n!adenocarcinoma",
"#### largecellcarcinoma\n\n!largecellcarcinoma",
"#### normal\n\n!normal",
"#### squamouscellcarcinoma\n\n!squamouscellcarcinoma"
] | [
54,
40,
4,
13,
14,
5,
17
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #pytorch #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us \n# medical\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the demo at the github repo.## Example Images#### adenocarcinoma\n\n!adenocarcinoma#### largecellcarcinoma\n\n!largecellcarcinoma#### normal\n\n!normal#### squamouscellcarcinoma\n\n!squamouscellcarcinoma"
] | [
-0.02417708933353424,
0.220903217792511,
-0.007832312025129795,
0.006598911713808775,
0.15457238256931305,
0.014880487695336342,
0.06084051728248596,
0.12733067572116852,
-0.032733213156461716,
0.06343358755111694,
0.17588965594768524,
0.05712299048900604,
0.005511237308382988,
0.24819934368133545,
-0.020840179175138474,
-0.17242927849292755,
-0.1254371702671051,
0.027312064543366432,
-0.022674119099974632,
0.08507207036018372,
0.0700249895453453,
-0.0931040346622467,
0.12353847920894623,
0.02612372674047947,
-0.15569056570529938,
0.01412851270288229,
0.06603440642356873,
-0.09493731707334518,
0.031361423432826996,
0.05395987629890442,
0.07696527987718582,
0.044556330889463425,
-0.042666081339120865,
-0.0008767999825067818,
0.0524233877658844,
-0.021702038124203682,
-0.01320092286914587,
0.05927572771906853,
0.15019941329956055,
0.014963509514927864,
0.1175813153386116,
-0.07153105735778809,
-0.10004876554012299,
0.015780452638864517,
-0.03540566563606262,
-0.003980709705501795,
-0.14660625159740448,
0.012372386641800404,
0.07624846696853638,
0.0720510259270668,
0.00016827684885356575,
0.08875344693660736,
-0.022986361756920815,
0.07266247272491455,
0.30739903450012207,
-0.08768334984779358,
-0.07203172892332077,
0.10556154698133469,
0.023249277845025063,
-0.04373125359416008,
0.05290582403540611,
0.10170076042413712,
0.018175438046455383,
-0.0671803280711174,
0.030583873391151428,
-0.03869413211941719,
-0.032139431685209274,
-0.026001421734690666,
-0.046043746173381805,
0.0005115657113492489,
-0.025837210938334465,
-0.09861575812101364,
0.02948383241891861,
-0.10341613739728928,
-0.05715581774711609,
-0.0404423289000988,
-0.0156633909791708,
0.005537248682230711,
0.06719837337732315,
-0.003193597076460719,
-0.07623302191495895,
-0.08626164495944977,
-0.09071731567382812,
-0.04028012976050377,
-0.07785190641880035,
0.012090710923075676,
-0.030685599893331528,
0.0073488010093569756,
-0.020704973489046097,
0.016147419810295105,
-0.014692847616970539,
-0.04647989198565483,
-0.02285710535943508,
0.011571037583053112,
0.004521778319031,
-0.07018179446458817,
0.005931498948484659,
-0.06208205223083496,
0.19661104679107666,
-0.03499271720647812,
-0.048321980983018875,
-0.007821532897651196,
-0.022321833297610283,
0.0696389228105545,
0.03617331013083458,
-0.011901524849236012,
-0.13835489749908447,
0.023756951093673706,
0.06247176602482796,
0.02092824876308441,
0.09099072217941284,
0.06344644725322723,
-0.08239136636257172,
0.007999616675078869,
0.03890844061970711,
0.09939666092395782,
-0.009274403564631939,
0.043823324143886566,
-0.013290260918438435,
-0.014568633399903774,
0.20304472744464874,
-0.014942116104066372,
-0.012054135091602802,
-0.00031218299409374595,
-0.005982367787510157,
-0.03235085308551788,
0.02603239379823208,
-0.0934213176369667,
-0.019431069493293762,
0.021565143018960953,
-0.03837186098098755,
0.03929544985294342,
-0.04024685174226761,
0.016242200508713722,
0.020746303722262383,
-0.1009344533085823,
-0.08875815570354462,
-0.1401974856853485,
0.06264641880989075,
-0.05194392427802086,
-0.06421426683664322,
-0.09110170602798462,
-0.03427644073963165,
0.0026436445768922567,
-0.007036332972347736,
-0.04867840185761452,
0.018075402826070786,
0.06528719514608383,
-0.02423592284321785,
0.05323876813054085,
0.03219280764460564,
0.1314934939146042,
-0.012371662072837353,
-0.02432086132466793,
-0.06367380917072296,
0.04048388451337814,
-0.2041798084974289,
-0.022764014080166817,
-0.04478377848863602,
0.05569468066096306,
-0.12528379261493683,
-0.02038676105439663,
-0.02503790892660618,
-0.036030661314725876,
0.0678396001458168,
0.1672058403491974,
-0.13193821907043457,
-0.06904889643192291,
0.09799373149871826,
0.04249318316578865,
-0.08485119789838791,
0.09023584425449371,
0.017371557652950287,
-0.020142769441008568,
0.02367071807384491,
0.08231181651353836,
-0.028861427679657936,
0.05878802388906479,
-0.1087559387087822,
-0.10125771909952164,
-0.12498947232961655,
-0.015311633236706257,
0.01432886440306902,
-0.04400710016489029,
-0.08314822614192963,
0.012802988290786743,
0.040095750242471695,
0.07704677432775497,
-0.09154125303030014,
-0.03390221297740936,
-0.0023508055601269007,
-0.12282305955886841,
-0.01826164685189724,
0.029617873951792717,
0.0174587182700634,
-0.06293883919715881,
0.019526895135641098,
-0.2811391353607178,
0.037302277982234955,
0.029876388609409332,
-0.06101498007774353,
-0.08791782706975937,
0.17924773693084717,
-0.0954795628786087,
0.00878820475190878,
-0.08079775422811508,
-0.18971462547779083,
0.02470947802066803,
0.0011332943104207516,
0.005578458774834871,
-0.1588527113199234,
-0.003559821518138051,
-0.006070674397051334,
0.002442211378365755,
0.05743376165628433,
0.22676710784435272,
-0.04697785526514053,
-0.10039224475622177,
0.01705748960375786,
0.12209239602088928,
-0.0365496501326561,
0.04687336087226868,
-0.180586040019989,
0.014250336214900017,
0.054431188851594925,
0.022707872092723846,
0.013312647119164467,
-0.038435522466897964,
0.1207013726234436,
-0.03183655068278313,
-0.07851553708314896,
-0.03998952731490135,
0.10462120175361633,
-0.06540284305810928,
0.006350633688271046,
0.10070973634719849,
-0.07624032348394394,
0.007185911759734154,
0.0759267508983612,
-0.051508933305740356,
-0.1346655935049057,
-0.14166057109832764,
-0.03808562085032463,
0.05916006490588188,
-0.13668866455554962,
0.08983022719621658,
-0.08294448256492615,
0.0180932879447937,
0.1310533732175827,
-0.01292685978114605,
0.0029202664736658335,
0.02747916616499424,
-0.018173830583691597,
-0.05511877313256264,
0.04893391206860542,
0.22571997344493866,
-0.16557571291923523,
0.03806423395872116,
0.13604263961315155,
-0.03472078591585159,
0.06924412399530411,
0.13292136788368225,
0.015151448547840118,
0.0072776745073497295,
-0.04008647799491882,
0.0625387653708458,
0.0006148518878035247,
0.022531606256961823,
-0.010791392996907234,
0.05149329826235771,
-0.16477829217910767,
0.01969088613986969,
-0.05339955538511276,
-0.05167866125702858,
-0.025152772665023804,
-0.06826800107955933,
0.05375348776578903,
0.12041042000055313,
0.023598063737154007,
0.11756876856088638,
-0.0355113185942173,
-0.012347409501671791,
-0.028537267819046974,
0.02484992705285549,
0.0182372834533453,
0.14522510766983032,
0.02848305180668831,
-0.25376877188682556,
0.0022901881020516157,
-0.028766948729753494,
-0.000029790166081511416,
0.13880477845668793,
0.02569742314517498,
-0.08627224713563919,
-0.00844188965857029,
-0.07593657821416855,
-0.11869681626558304,
0.22787915170192719,
0.08049048483371735,
-0.12337895482778549,
0.012719132006168365,
0.04494493082165718,
-0.006382279563695192,
-0.05258176103234291,
-0.04170432314276695,
-0.12585881352424622,
0.13698795437812805,
-0.018848156556487083,
0.10847923904657364,
0.10226708650588989,
-0.0341581255197525,
0.01932385563850403,
-0.04048025608062744,
0.10002129524946213,
-0.11350347846746445,
-0.011241196654736996,
0.14895014464855194,
0.12004050612449646,
0.06388699263334274,
0.03092912957072258,
0.02595934271812439,
-0.021256720647215843,
0.07323365658521652,
0.07234396040439606,
-0.06183576583862305,
-0.13701583445072174,
-0.05457664653658867,
0.03641299530863762,
0.06961347907781601,
0.029550602659583092,
0.09067924320697784,
0.02674945630133152,
0.1639375537633896,
-0.01906699314713478,
-0.07516723871231079,
-0.031757939606904984,
0.016697220504283905,
0.08540903776884079,
0.01932614855468273,
0.10277634859085083,
0.0473867803812027,
-0.08805682510137558,
0.07907313853502274,
0.01499995868653059,
0.16801218688488007,
-0.02400823123753071,
0.12967534363269806,
-0.042750485241413116,
-0.059737056493759155,
0.0467294342815876,
-0.024769732728600502,
0.011068666353821754,
-0.025413786992430687,
-0.0022904546931385994,
-0.06707792729139328,
-0.015479124151170254,
-0.062376536428928375,
0.11829535663127899,
-0.14424844086170197,
0.02679567039012909,
0.05539962649345398,
0.04827778413891792,
0.11712297797203064,
0.04460706561803818,
-0.2476809173822403,
0.024494865909218788,
-0.03709056228399277,
0.0336948037147522,
-0.008951116353273392,
-0.008603512309491634,
0.06435798108577728,
-0.06384456157684326,
0.018662482500076294,
-0.05222031846642494,
0.0547688752412796,
-0.055280640721321106,
-0.0039195651188492775,
0.03792029246687889,
0.02264971099793911,
-0.04245924949645996,
0.1103159636259079,
-0.08199939131736755,
0.08430447429418564,
-0.00941575039178133,
-0.10941512882709503,
-0.07236415147781372,
-0.037575509399175644,
0.10652703791856766,
0.16678540408611298,
0.12954317033290863,
-0.013155002146959305,
0.0088645676150918,
-0.12071220576763153,
-0.13269652426242828,
-0.07650317996740341,
0.06374296545982361,
-0.06962847709655762,
0.08462522178888321,
0.024715332314372063,
-0.0915815532207489,
-0.06666865199804306,
-0.09987670183181763,
-0.13771973550319672,
-0.06750449538230896,
0.033403098583221436,
0.024937529116868973,
-0.01071553397923708,
-0.0276949442923069,
-0.06673993170261383,
-0.061699941754341125,
0.04114240035414696,
0.142769455909729,
-0.012618022970855236,
-0.042293060570955276,
0.06562504917383194,
0.018625278025865555,
-0.07795447111129761,
0.033951226621866226,
-0.02513573132455349,
0.11194421350955963,
0.06142822653055191,
-0.06043308600783348,
0.13616648316383362,
-0.12425791472196579,
-0.16859696805477142,
-0.06038879230618477,
0.15188942849636078,
-0.0679733008146286,
0.0021807525772601366,
0.03568907827138901,
0.03374461829662323,
-0.009738973341882229,
-0.03284725174307823,
0.13278159499168396,
0.055788829922676086,
0.142830953001976,
0.18327030539512634,
0.010292954742908478,
-0.07547574490308762,
-0.05018697679042816,
-0.056377265602350235,
0.1712590754032135,
0.1307818442583084,
0.002698988188058138,
0.07049804925918579,
-0.08753801137208939,
-0.04093275964260101,
-0.2640342116355896,
-0.017289336770772934,
0.050600070506334305,
-0.07457778602838516,
0.11405768245458603,
-0.17223511636257172,
0.09157965332269669,
0.13793672621250153,
-0.015179323963820934,
0.18509389460086823,
-0.09004954993724823,
-0.06684499979019165,
-0.059272635728120804,
0.016410723328590393,
0.06325193494558334,
-0.2268529236316681,
-0.07105150073766708,
-0.1018834039568901,
0.1368328332901001,
0.1814098358154297,
-0.007690050173550844,
0.11689300090074539,
-0.044614896178245544,
0.0020641719456762075,
0.05109122022986412,
-0.05336802825331688,
0.01967644691467285,
-0.10955788195133209,
-0.049216121435165405,
-0.0817701667547226,
-0.15877565741539001,
-0.04633759334683418,
0.06176682561635971,
-0.002457647817209363,
-0.01763784885406494,
0.04307885095477104,
-0.08714964240789413,
-0.03790288418531418,
-0.07344451546669006,
0.08756250888109207,
0.03905864804983139,
0.010913302190601826,
-0.12871825695037842,
0.04074035584926605,
0.0035048178397119045,
0.05220012739300728,
0.09599167853593826,
-0.11280453950166702,
-0.048291414976119995,
0.09203281253576279,
0.07332083582878113,
-0.03595157712697983,
-0.03498231619596481,
0.019281044602394104,
-0.06189805641770363,
0.022805169224739075,
-0.10978559404611588,
0.04022722318768501,
-0.0017126234015449882,
0.028636807575821877,
-0.03952055051922798,
0.06739939749240875,
0.04844236001372337,
0.05590187758207321,
0.13478966057300568,
-0.1341443508863449,
-0.08871982246637344,
-0.03202623873949051,
0.05043308809399605,
-0.0495629608631134,
0.020879752933979034,
0.083599753677845,
-0.003955775406211615,
-0.06906893104314804,
0.03306093439459801,
0.040678173303604126,
0.05116064473986626,
0.20228032767772675,
0.10789687931537628,
-0.028738731518387794,
-0.0200471431016922,
-0.032784491777420044,
0.0915599837899208,
-0.0663672536611557,
-0.08084320276975632,
0.0950690433382988,
-0.06310182809829712,
-0.13613414764404297,
0.06315930187702179,
0.17291241884231567,
-0.10001196712255478,
-0.01012301817536354,
-0.03074241243302822,
0.013385509140789509,
0.05492598935961723,
0.04932186380028725,
0.09335733205080032,
-0.06623911112546921,
0.015426564030349255,
-0.017196273431181908,
-0.05730285122990608,
0.08738311380147934,
0.024112045764923096,
0.09612379223108292,
-0.05273507907986641,
0.03543027490377426,
-0.0907946452498436,
0.08898265659809113,
-0.07974977046251297,
0.05517290160059929,
-0.06520865112543106,
-0.06949695944786072,
-0.005208977963775396,
0.050240956246852875,
-0.10489179939031601,
-0.07348452508449554,
-0.008819944225251675,
0.09363197535276413,
0.032381605356931686,
-0.08496306836605072,
-0.03393157199025154,
-0.031506218016147614,
0.02293180115520954,
0.07075165957212448,
-0.08678514510393143,
0.004463253077119589,
0.0030438562389463186,
0.03624536842107773,
0.17415647208690643,
-0.04111521691083908,
0.02605743147432804,
-0.10327232629060745,
-0.20187246799468994,
-0.11745836585760117,
0.08915989100933075,
0.008461762219667435,
-0.03900899365544319,
-0.09446919709444046,
0.08727040886878967,
-0.0027801613323390484,
0.0168133731931448,
0.030427198857069016,
0.15278463065624237,
-0.05637219175696373,
-0.03500434756278992,
-0.021574443206191063,
0.013079271651804447,
-0.020475788041949272,
0.024462517350912094,
-0.00008590715151512995,
0.017338789999485016,
0.13346804678440094,
-0.11771497875452042,
0.012224745936691761,
-0.0869324803352356,
0.010620730929076672,
-0.030225973576307297,
-0.16573116183280945,
-0.04588468000292778,
0.02077116072177887,
0.09762372821569443,
0.03430590778589249,
0.06138399988412857,
0.10344340652227402,
-0.006149380002170801,
-0.022787705063819885,
0.10002373158931732,
0.189456507563591,
-0.0036437190137803555,
0.10216759890317917,
0.060546573251485825,
-0.017749274149537086,
-0.06338713318109512,
0.0750214084982872,
0.10248000174760818,
0.009387669153511524,
0.0663258358836174,
0.02990148589015007,
-0.08330786973237991,
0.0036523633170872927,
-0.05583757534623146,
-0.09780904650688171,
-0.004206360317766666,
0.02976319007575512,
-0.0621856153011322,
0.07083506137132645,
-0.05442764237523079,
-0.011667368933558464,
0.06810671091079712,
-0.06071232631802559,
-0.01013229414820671,
-0.11352438479661942,
0.01158908847719431,
-0.04424312710762024,
-0.12416911125183105,
-0.08977456390857697,
-0.10417294502258301,
0.026593083515763283,
-0.025282859802246094,
-0.004056749399751425,
0.09592773765325546,
-0.012652883306145668,
-0.06712082028388977,
0.17622347176074982,
-0.09318437427282333,
0.02543715201318264,
0.09660204499959946,
-0.019398421049118042,
0.002941389102488756,
0.07757548987865448,
-0.0679638683795929,
-0.041611362248659134,
-0.02211279235780239,
0.01865534670650959,
0.01746721751987934,
-0.005362991243600845,
0.02436535246670246,
-0.10376377403736115,
-0.04946858063340187,
-0.0607127770781517,
0.04081584885716438,
0.018045563250780106,
0.047639720141887665,
-0.014068321324884892,
0.09130639582872391,
0.007276912219822407,
0.189412459731102,
-0.025655459612607956,
0.07887303829193115,
-0.03756975382566452,
-0.05503098666667938,
-0.03556642681360245,
0.06593918055295944,
-0.1163940280675888,
-0.041629623621702194,
0.023056253790855408,
0.2110159546136856,
0.2098768800497055,
-0.13644006848335266,
-0.01768220029771328,
0.03119680844247341,
0.01425256859511137,
0.07736071944236755,
0.06750594824552536,
0.08160588145256042,
0.06317296624183655,
-0.0006209764978848398,
-0.020496834069490433,
0.025901226326823235,
0.02529153786599636,
-0.23547051846981049,
0.02558007463812828,
0.08612335473299026,
0.028986137360334396,
-0.013825494796037674,
0.059302788227796555,
0.010274813510477543,
-0.011410743929445744,
0.033613722771406174,
-0.17111711204051971,
-0.07121692597866058,
-0.005295875016599894,
0.12099889665842056,
0.011574280448257923,
0.05031704157590866,
-0.05791556090116501,
0.050438519567251205,
0.03901679441332817,
-0.046815212815999985,
-0.15374664962291718,
0.01003437489271164,
-0.026553424075245857,
-0.11085427552461624,
0.2765398621559143,
-0.01708894409239292,
0.05193869024515152,
0.13062764704227448,
-0.09174814820289612,
-0.1263059824705124,
0.07228481769561768,
0.00405155448243022,
-0.08071520179510117,
0.1835857331752777,
0.08063872903585434,
-0.004404417704790831,
-0.12529458105564117,
0.009274664334952831,
-0.027161680161952972,
0.017387641593813896,
-0.033042218536138535,
0.15045851469039917,
-0.07921811193227768,
0.14239276945590973,
-0.14277848601341248,
0.009310701861977577,
0.09582803398370743,
0.02906126156449318,
0.050824232399463654,
0.009352459572255611,
0.08957646787166595,
0.035047274082899094,
0.09139475971460342,
-0.049229156225919724,
-0.08407130837440491,
-0.015437878668308258,
-0.09094923734664917,
0.03464827314019203,
-0.11539772897958755,
0.021660855039954185,
-0.13670244812965393,
0.016612008213996887,
-0.034276798367500305,
0.06724889576435089,
0.12246069312095642,
-0.0038053151220083237,
-0.006217282731086016,
0.04959558695554733,
-0.006772215478122234,
0.03843938559293747,
-0.13259191811084747,
-0.03944573923945427
] |
null | null | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="Sonwe1e/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
| {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": "FrozenLake-v1-4x4-no_slippery"}, "metrics": [{"type": "mean_reward", "value": "1.00 +/- 0.00", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | Sonwe1e/q-FrozenLake-v1-4x4-noSlippery | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | 2024-02-11T05:58:27+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
| [
"# Q-Learning Agent playing1 FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n\n ## Usage"
] | [
"TAGS\n#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n",
"# Q-Learning Agent playing1 FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n\n ## Usage"
] | [
40,
39
] | [
"passage: TAGS\n#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n# Q-Learning Agent playing1 FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n\n ## Usage"
] | [
0.04578453302383423,
-0.08074592798948288,
-0.00430759321898222,
0.10720831900835037,
0.05034215748310089,
-0.040469273924827576,
0.11997015029191971,
0.018999949097633362,
0.20601962506771088,
-0.010012076236307621,
0.1455274522304535,
0.007022971753031015,
-0.006192410364747047,
0.1867983490228653,
0.04572829231619835,
-0.26324528455734253,
0.01831899583339691,
-0.09495259821414948,
-0.07281816750764847,
0.11870454251766205,
0.05470194295048714,
-0.01901467889547348,
-0.0007633853238075972,
0.056141503155231476,
-0.0673527717590332,
0.0007737681735306978,
0.031996939331293106,
-0.012976245954632759,
0.19804789125919342,
-0.02254498563706875,
0.06641989201307297,
0.054705578833818436,
0.0758768692612648,
-0.1998077929019928,
0.0358855277299881,
-0.04215473681688309,
-0.09439758956432343,
-0.03934839740395546,
-0.018780618906021118,
0.05878105387091637,
0.053356342017650604,
0.03858819976449013,
0.058354366570711136,
0.09384993463754654,
-0.0773480236530304,
0.04328357055783272,
0.04280758649110794,
0.024811049923300743,
0.04589218273758888,
-0.0237203948199749,
-0.027002155780792236,
0.08246652781963348,
-0.22182892262935638,
0.10318073630332947,
-0.010159241035580635,
-0.5270710587501526,
-0.00633762264624238,
0.24088262021541595,
0.11517096310853958,
0.05707438662648201,
-0.06903956830501556,
0.10566288232803345,
0.03913382440805435,
-0.007209456991404295,
0.03210983797907829,
0.02150118350982666,
0.12817370891571045,
0.06009242683649063,
-0.09581366181373596,
0.040699947625398636,
0.13722525537014008,
0.012822695076465607,
0.020306183025240898,
-0.08888901025056839,
0.0410032719373703,
-0.03461858257651329,
-0.007679527159780264,
-0.09758518636226654,
0.05478060990571976,
0.012466507963836193,
-0.0934976264834404,
-0.09247440844774246,
-0.04236573353409767,
-0.06708304584026337,
0.11252415925264359,
0.046419668942689896,
-0.0874939113855362,
0.03884070739150047,
-0.06760413944721222,
0.05918780341744423,
-0.16863860189914703,
0.02074250765144825,
-0.06627868115901947,
-0.09376336634159088,
-0.11799788475036621,
-0.01683047041296959,
-0.07946427166461945,
0.009092256426811218,
0.056664444506168365,
0.1447116881608963,
0.22076484560966492,
0.06690320372581482,
0.09728849679231644,
0.07456006109714508,
0.06531001627445221,
0.1538129299879074,
0.10918238013982773,
0.019075315445661545,
-0.015266558155417442,
0.0948706716299057,
-0.06445580720901489,
-0.1351388692855835,
-0.15579092502593994,
0.005488025024533272,
0.0983937531709671,
0.08871900290250778,
-0.044080477207899094,
-0.006702381651848555,
-0.024641724303364754,
0.08566431701183319,
-0.11314457654953003,
-0.024612564593553543,
-0.002267979085445404,
0.06882024556398392,
-0.024801667779684067,
0.020378148183226585,
-0.06242705136537552,
0.12715265154838562,
0.04222423583269119,
-0.059924717992544174,
-0.055308472365140915,
-0.03053177334368229,
-0.014276440255343914,
-0.027539284899830818,
0.02446848154067993,
-0.07659092545509338,
0.04767750948667526,
-0.16766095161437988,
-0.042871296405792236,
-0.04784649610519409,
0.025697942823171616,
-0.03907240927219391,
-0.13557587563991547,
-0.17699143290519714,
-0.048906855285167694,
-0.022438718006014824,
0.03549358621239662,
-0.038111843168735504,
0.006551501806825399,
-0.006318534724414349,
-0.1583600640296936,
0.09783563017845154,
0.09784027189016342,
-0.03643378987908363,
-0.02749447710812092,
0.056263517588377,
-0.07194498926401138,
0.1561182290315628,
-0.21054518222808838,
-0.054014235734939575,
-0.044764336198568344,
-0.06595750898122787,
0.19673264026641846,
0.012690845876932144,
-0.01202624011784792,
0.19873127341270447,
-0.29073721170425415,
-0.06078760325908661,
0.12533614039421082,
-0.07834373414516449,
-0.0936407670378685,
0.06941844522953033,
-0.04206686094403267,
0.023345354944467545,
0.046047765761613846,
0.36345911026000977,
-0.02069227211177349,
-0.16197136044502258,
-0.021782705560326576,
0.13971707224845886,
-0.1184760183095932,
0.059895481914281845,
0.04240793362259865,
0.12543781101703644,
-0.04250509291887283,
-0.018672896549105644,
-0.09023164212703705,
0.05999075248837471,
-0.05241934582591057,
-0.09016361832618713,
-0.03393383324146271,
-0.07645075023174286,
0.13294468820095062,
-0.0629684180021286,
0.05601520463824272,
-0.03255095332860947,
-0.07133250683546066,
-0.050324998795986176,
-0.016492370516061783,
0.04460815340280533,
0.05951254442334175,
-0.12794871628284454,
0.11029167473316193,
0.13025271892547607,
-0.0006193425506353378,
-0.07498852163553238,
-0.17872096598148346,
0.003240168560296297,
0.009576505981385708,
0.039837226271629333,
0.17141658067703247,
0.12209978699684143,
0.033295199275016785,
0.008770671673119068,
-0.06389404833316803,
-0.18276847898960114,
0.058129217475652695,
-0.056212130934000015,
-0.14230976998806,
-0.052409034222364426,
-0.0728459507226944,
0.017381802201271057,
-0.0859743058681488,
-0.017379917204380035,
0.021926190704107285,
0.006908397190272808,
0.02990424446761608,
-0.026645656675100327,
-0.049561817198991776,
0.021254703402519226,
0.06490101665258408,
-0.0037617047782987356,
0.12023693323135376,
0.008277264423668385,
-0.18308481574058533,
0.07930773496627808,
0.08478537946939468,
0.09196605533361435,
0.013250201940536499,
0.02685922384262085,
-0.021522263064980507,
-0.08061408251523972,
-0.054420311003923416,
0.02957955375313759,
0.11417073011398315,
0.1317172348499298,
0.2361993044614792,
0.08753683418035507,
0.04697408527135849,
-0.02164587564766407,
-0.016415923833847046,
0.002810494042932987,
-0.06318057328462601,
-0.029935607686638832,
0.10614971816539764,
0.05865858122706413,
-0.067733034491539,
-0.04576427489519119,
0.09590928256511688,
0.02732124738395214,
0.21205885708332062,
-0.03342745825648308,
0.01286078616976738,
-0.10957037657499313,
-0.06550975888967514,
-0.031982194632291794,
0.09201868623495102,
0.09498392790555954,
0.009755023755133152,
-0.022056059911847115,
-0.04259001836180687,
0.0012916827108711004,
-0.1334889680147171,
-0.10375088453292847,
0.026475343853235245,
0.013400445692241192,
-0.11206940561532974,
0.11674030870199203,
-0.11352457851171494,
0.039504457265138626,
0.06024791672825813,
-0.13837239146232605,
0.04428480193018913,
-0.029713207855820656,
-0.07886212319135666,
0.16866780817508698,
-0.11075661331415176,
-0.094340018928051,
-0.08831550180912018,
0.004082420375198126,
0.0075836325995624065,
-0.03922267258167267,
-0.009283260442316532,
-0.19952571392059326,
-0.005375816952437162,
-0.03544965013861656,
0.013616434298455715,
-0.06988783925771713,
-0.11287739872932434,
-0.010957922786474228,
0.07084179669618607,
-0.043388739228248596,
-0.07803605496883392,
0.007967432029545307,
-0.08923084288835526,
-0.10623309016227722,
0.028189711272716522,
0.019765101373195648,
-0.022883659228682518,
0.16152891516685486,
0.01816628873348236,
0.05626589432358742,
-0.03298520669341087,
0.30665266513824463,
-0.038163769990205765,
0.08371731638908386,
-0.02993497997522354,
-0.07433546334505081,
0.06130730360746384,
-0.022327827289700508,
0.06086638569831848,
-0.020221687853336334,
-0.02362890914082527,
0.0077952733263373375,
-0.08579335361719131,
-0.18365982174873352,
-0.05417544022202492,
0.03724347800016403,
0.195254847407341,
0.031118987128138542,
0.01910330168902874,
-0.0488768145442009,
-0.010547760874032974,
0.1665220558643341,
-0.10005921125411987,
0.04030545800924301,
-0.05366240441799164,
0.11506262421607971,
-0.08640182018280029,
0.06195629760622978,
0.020486772060394287,
0.04266135022044182,
-0.04877188801765442,
0.09486009180545807,
0.0826394334435463,
0.1121082529425621,
-0.02206910029053688,
0.046257395297288895,
0.019012698903679848,
0.07383184134960175,
0.11073657125234604,
0.0368414968252182,
-0.0729052945971489,
0.001982470043003559,
-0.006313489284366369,
-0.039427030831575394,
0.11933320760726929,
0.17963355779647827,
-0.11991413682699203,
-0.05106910318136215,
0.27167606353759766,
0.0031242913100868464,
0.19481229782104492,
-0.01315275114029646,
0.043591804802417755,
-0.04484925419092178,
0.04572054371237755,
-0.05338600277900696,
-0.04086209088563919,
0.2094656229019165,
0.08045925945043564,
-0.17165091633796692,
-0.08549032360315323,
-0.05912299454212189,
0.07081323862075806,
0.10728751868009567,
0.0013539529172703624,
-0.04156802222132683,
0.0004610282776411623,
0.0014198932331055403,
0.08339415490627289,
-0.14520122110843658,
0.11816094070672989,
-0.03172019124031067,
0.05612684786319733,
0.017555562779307365,
-0.045326150953769684,
0.04264266416430473,
0.07474290579557419,
0.26618310809135437,
0.0904107540845871,
-0.040318213403224945,
-0.0892091691493988,
-0.12260187417268753,
0.010461576282978058,
0.029102616012096405,
-0.03534553572535515,
0.0037547778338193893,
-0.020087555050849915,
0.0318896509706974,
0.008264793083071709,
0.016230624169111252,
-0.08987458795309067,
-0.03175399824976921,
-0.027736429125070572,
-0.023839212954044342,
0.10733365267515182,
-0.09495144337415695,
-0.1444292515516281,
-0.15713949501514435,
0.04191131144762039,
-0.0766405463218689,
-0.056593164801597595,
-0.054507751017808914,
-0.05239389091730118,
-0.0311186034232378,
-0.03773957118391991,
0.09099467098712921,
-0.0021037792321294546,
0.14807306230068207,
-0.1920108050107956,
-0.04220759496092796,
0.051812779158353806,
-0.07607918977737427,
-0.08729588985443115,
0.03410962224006653,
0.12136995792388916,
0.05116051807999611,
0.11504370719194412,
0.013609255664050579,
0.09567681699991226,
0.0045484392903745174,
-0.06713183224201202,
0.15302421152591705,
-0.14069625735282898,
-0.27875974774360657,
-0.03836318850517273,
0.016946332529187202,
0.1615200787782669,
-0.05613167956471443,
0.031766023486852646,
0.3335736393928528,
0.27782970666885376,
-0.1428707242012024,
0.25916144251823425,
0.019178593531250954,
0.004398873541504145,
-0.19130495190620422,
-0.10125631093978882,
0.025324683636426926,
0.04740457236766815,
0.12032642960548401,
-0.14564448595046997,
-0.010732659138739109,
-0.04543145373463631,
-0.025908485054969788,
0.10386138409376144,
-0.12300799041986465,
-0.07263197749853134,
0.07765276730060577,
0.039809420704841614,
0.1808302253484726,
0.03932500258088112,
0.0014799144119024277,
0.13626977801322937,
0.06612244248390198,
0.019124457612633705,
0.05216038227081299,
0.08028066903352737,
-0.018944554030895233,
0.14207926392555237,
0.05448179319500923,
-0.02551644667983055,
0.052681710571050644,
-0.0054580713622272015,
-0.03219012916088104,
0.015605825930833817,
-0.183198019862175,
-0.10147556662559509,
-0.0561356320977211,
-0.10798973590135574,
-0.04978342354297638,
0.056853994727134705,
-0.12395523488521576,
-0.007896827533841133,
-0.03841273859143257,
0.03718273714184761,
-0.07831971347332001,
-0.09360362589359283,
-0.036494381725788116,
0.1351792961359024,
0.07210618257522583,
0.04471297934651375,
0.035655103623867035,
-0.07390819489955902,
0.07097936421632767,
0.21671734750270844,
0.08159157633781433,
0.028919655829668045,
-0.19545674324035645,
-0.024042490869760513,
-0.0803457647562027,
0.06306298077106476,
-0.08856996893882751,
-0.016788700595498085,
0.11923003196716309,
0.08616556972265244,
0.05413002520799637,
0.09640096127986908,
-0.045083072036504745,
0.021686913445591927,
0.02684609219431877,
-0.15131035447120667,
-0.18501274287700653,
-0.08534606546163559,
-0.03519878163933754,
0.11561143398284912,
-0.06398691236972809,
0.10897188633680344,
-0.13615410029888153,
0.010051886551082134,
-0.006060056854039431,
0.02693452313542366,
-0.03596206381917,
-0.11251141875982285,
0.15348562598228455,
0.11999429017305374,
-0.06767056882381439,
0.03127254918217659,
-0.09527092427015305,
-0.04423454403877258,
0.12686803936958313,
-0.013623855076730251,
-0.0371493324637413,
-0.054547641426324844,
-0.03628576174378395,
0.15247689187526703,
-0.03436964750289917,
0.008244883269071579,
-0.041229065507650375,
-0.18217355012893677,
0.0798322781920433,
0.09045056998729706,
0.019827889278531075,
-0.031874191015958786,
-0.09797266125679016,
-0.010231015272438526,
-0.0011165260802954435,
0.11730700731277466,
-0.10696814209222794,
-0.10933240503072739,
-0.15144047141075134,
0.06713984161615372,
-0.0007159380475059152,
0.18502596020698547,
-0.06394898891448975,
-0.08904669433832169,
-0.12429379671812057,
0.02344517596065998,
-0.0027384376153349876,
-0.042264558374881744,
0.01618490368127823,
0.07992301136255264,
-0.04095321521162987,
0.02075677551329136,
-0.06651144474744797,
0.06372585147619247,
-0.11786920577287674,
0.09625071287155151,
0.01063506118953228,
0.016993753612041473,
-0.0417880080640316,
-0.01618220843374729,
0.039470795542001724,
-0.057925306260585785,
0.07921463251113892,
0.011758086271584034,
0.0010938759660348296,
0.10196787863969803,
-0.0034960443153977394,
0.06409632414579391,
-0.05372481048107147,
-0.023290161043405533,
0.06578411161899567,
-0.05874887853860855,
-0.03370826691389084,
-0.1573946475982666,
-0.0709633082151413,
0.020051732659339905,
-0.04775108024477959,
0.002077929675579071,
0.03673801198601723,
0.062159497290849686,
-0.06937079131603241,
-0.12125655263662338,
-0.043812792748212814,
-0.028638383373618126,
0.021301284432411194,
0.10829301923513412,
-0.07526551932096481,
0.1547859013080597,
-0.052787959575653076,
-0.00020603960729204118,
0.07437096536159515,
0.04048224538564682,
0.01393822580575943,
-0.10422444343566895,
-0.04698587954044342,
-0.11035211384296417,
0.1502903699874878,
-0.007902312092483044,
-0.03533121198415756,
0.03719403222203255,
-0.11946307867765427,
-0.1572723090648651,
0.03418220207095146,
0.10199101269245148,
0.0448341928422451,
0.025807438418269157,
0.027079269289970398,
-0.04042419046163559,
-0.021270349621772766,
-0.07034418731927872,
0.0882953479886055,
-0.12085357308387756,
-0.09669415652751923,
0.09555385261774063,
0.12178351730108261,
-0.0036850625183433294,
-0.07441367954015732,
0.11554073542356491,
-0.021787192672491074,
0.05525410920381546,
-0.02971339225769043,
0.10308072715997696,
0.0796005055308342,
-0.12273547053337097,
0.005693064536899328,
-0.036891788244247437,
-0.0741485133767128,
-0.12975730001926422,
0.019545545801520348,
-0.061916105449199677,
-0.13383042812347412,
0.12179028987884521,
-0.09376577287912369,
0.030037038028240204,
-0.10506992787122726,
0.021338803693652153,
0.01864001713693142,
0.061665527522563934,
-0.10988292098045349,
0.08575301617383957,
0.13424484431743622,
-0.043199893087148666,
-0.07184189558029175,
-0.12455986440181732,
-0.05022053420543671,
-0.04231856390833855,
-0.13957437872886658,
-0.11600435525178909,
0.0100301094353199,
-0.023418782278895378,
-0.05818291753530502,
0.0015462689334526658,
-0.03659068048000336,
0.008594646118581295,
0.021907730028033257,
0.04032021388411522,
-0.02693161368370056,
0.05134565755724907,
-0.057569269090890884,
-0.052510857582092285,
0.11489357799291611,
0.04113486409187317,
-0.03561042994260788,
-0.052359987050294876,
0.12997733056545258,
-0.11959461867809296,
0.07662346214056015,
-0.020313527435064316,
0.017129231244325638,
-0.06435854732990265,
0.17131924629211426,
0.11673715710639954,
-0.1367570012807846,
-0.005008010193705559,
-0.08210669457912445,
0.020409544929862022,
0.023555370047688484,
0.13693512976169586,
-0.03411718085408211,
-0.0012358218664303422,
-0.1580323874950409,
0.018575575202703476,
-0.18557456135749817,
-0.03716109320521355,
0.04671547934412956,
0.09917585551738739,
0.15293832123279572,
-0.0034432117827236652,
-0.1263325810432434,
0.10424192249774933,
-0.2118520885705948,
0.0907607227563858,
0.05121984705328941,
-0.11874113976955414,
-0.06765396893024445,
-0.06795281916856766,
0.1198519766330719,
0.009196433238685131,
0.2040700763463974,
-0.013615905307233334,
-0.09132910519838333,
-0.07060808688402176,
-0.01980910450220108,
-0.030524181202054024,
0.09714830666780472,
0.041414931416511536,
0.04653804749250412,
0.12821412086486816,
0.00368314771912992,
0.07533777505159378,
0.060310911387205124,
0.02759413793683052,
-0.012300663627684116,
0.04076618701219559,
0.08261215686798096,
-0.14588621258735657,
-0.1659701019525528,
0.1326720416545868,
0.025149408727884293,
0.11792458593845367,
0.03658788278698921,
-0.1549617499113083,
0.06687124073505402,
0.2523096203804016,
-0.11147607117891312,
0.02505038119852543,
0.12737524509429932,
-0.0366884209215641,
0.0672016367316246,
0.1144871786236763,
-0.02633814327418804,
-0.05217865854501724,
-0.011363590136170387,
0.10233135521411896,
0.028660254552960396,
-0.04646271467208862,
-0.02340836264193058,
-0.03373933956027031,
-0.019070526584982872,
-0.011738128960132599,
-0.0909019410610199,
-0.1543993502855301,
-0.10471053421497345,
-0.16619662940502167,
0.04399140924215317,
-0.04626438021659851,
0.13418889045715332,
0.09469578415155411,
-0.012723101302981377,
0.04568437114357948,
0.028575526550412178,
0.07275456190109253,
0.07916246354579926,
-0.02939477376639843,
-0.036159269511699677
] |
null | null | null | # Meetkai Functionary AWQ Q6_K
[https://github.com/MeetKai/functionary](https://github.com/MeetKai/functionary)
Functionary is a language model that can interpret and execute functions/plugins.
The model determines when to execute functions, whether in parallel or serially, and can understand their outputs. It only triggers functions as needed. Function definitions are given as JSON Schema Objects, similar to OpenAI GPT function calls.
## Key Features
- Intelligent **parallel tool use**
- Able to analyze functions/tools outputs and provide relevant responses **grounded in the outputs**
- Able to decide **when to not use tools/call functions** and provide normal chat response
- Truly one of the best open-source alternative to GPT-4
## Performance
Our model achieves achieves state-of-the-art performance in Function Calling Accuracy on our in-house dataset. The accuracy metric measures the overall correctness of predicted function calls, including function name prediction and arguments extraction.
| Dataset | Model Name | Function Calling Accuracy (Name & Arguments) |
| :-------------| :-------------------| ---------------------------: |
| In-house data | MeetKai-functionary-small-v2.2 | 0.546|
| In-house data | MeetKai-functionary-medium-v2.2 | **0.664**|
| In-house data | OpenAI-gpt-3.5-turbo-1106 | 0.531 |
| In-house data | OpenAI-gpt-4-1106-preview | **0.737** |
## Prompt Template
We use a specially designed prompt template which we call "v2PromptTemplate" that breaks down each turns into from, recipient and content portions.
We convert function definitions to a similar text to TypeScript definitions. Then we inject these definitions as system prompts. After that, we inject the default system prompt. Then we start the conversation messages.
This formatting is also available via our vLLM server which we process the functions into Typescript definitions encapsulated in a system message and use a pre-defined Transformers chat template. This means that lists of messages can be formatted for you with the apply_chat_template() method within our server:
```python
from openai import OpenAI
client = OpenAI(base_url="http://localhost:8000/v1", api_key="functionary")
client.chat.completions.create(
model="path/to/functionary/model/",
messages=[{"role": "user",
"content": "What is the weather for Istanbul?"}
],
tools=[{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
}
},
"required": ["location"]
}
}
}],
tool_choice="auto"
)
```
will yield:
```
<|from|>system
<|recipient|>all
<|content|>// Supported function definitions that should be called when necessary.
namespace functions {
// Get the current weather
type get_current_weather = (_: {
// The city and state, e.g. San Francisco, CA
location: string,
}) => any;
} // namespace functions
<|from|>system
<|recipient|>all
<|content|>A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. The assistant calls functions with appropriate input when necessary
<|from|>user
<|recipient|>all
<|content|>What is the weather for Istanbul?
```
A more detailed example is provided [here](https://github.com/MeetKai/functionary/blob/main/tests/prompt_test_v2.txt).
## Run the model
We encourage users to run our models using our OpenAI-compatible vLLM server [here](https://github.com/MeetKai/functionary).
# The MeetKai Team
 | {} | null | casualjim/functionary-medium-v2.2-q6_K-gguf | [
"gguf",
"region:us"
] | 2024-02-11T05:58:28+00:00 | [] | [] | TAGS
#gguf #region-us
| Meetkai Functionary AWQ Q6\_K
=============================
URL
!Functionary Logo
Functionary is a language model that can interpret and execute functions/plugins.
The model determines when to execute functions, whether in parallel or serially, and can understand their outputs. It only triggers functions as needed. Function definitions are given as JSON Schema Objects, similar to OpenAI GPT function calls.
Key Features
------------
* Intelligent parallel tool use
* Able to analyze functions/tools outputs and provide relevant responses grounded in the outputs
* Able to decide when to not use tools/call functions and provide normal chat response
* Truly one of the best open-source alternative to GPT-4
Performance
-----------
Our model achieves achieves state-of-the-art performance in Function Calling Accuracy on our in-house dataset. The accuracy metric measures the overall correctness of predicted function calls, including function name prediction and arguments extraction.
!Eval Chart
Prompt Template
---------------
We use a specially designed prompt template which we call "v2PromptTemplate" that breaks down each turns into from, recipient and content portions.
We convert function definitions to a similar text to TypeScript definitions. Then we inject these definitions as system prompts. After that, we inject the default system prompt. Then we start the conversation messages.
This formatting is also available via our vLLM server which we process the functions into Typescript definitions encapsulated in a system message and use a pre-defined Transformers chat template. This means that lists of messages can be formatted for you with the apply\_chat\_template() method within our server:
will yield:
A more detailed example is provided here.
Run the model
-------------
We encourage users to run our models using our OpenAI-compatible vLLM server here.
The MeetKai Team
================
!MeetKai Logo
| [] | [
"TAGS\n#gguf #region-us \n"
] | [
9
] | [
"passage: TAGS\n#gguf #region-us \n"
] | [
0.030724648386240005,
0.026499787345528603,
-0.010017825290560722,
-0.05703527107834816,
0.08247160166501999,
0.07200847566127777,
0.01814177818596363,
0.020192064344882965,
0.2235025018453598,
0.017216520383954048,
0.1496623009443283,
-0.031233953312039375,
0.006174509879201651,
0.05538657680153847,
0.039407629519701004,
-0.19438467919826508,
0.058440499007701874,
-0.02356063388288021,
-0.020945189520716667,
0.01803453452885151,
-0.05310691148042679,
-0.04108472168445587,
0.022135348990559578,
-0.07881014049053192,
-0.15867982804775238,
0.0678698718547821,
0.017852067947387695,
0.0007025183876976371,
0.0820731669664383,
0.05882885307073593,
0.09657382220029831,
-0.024203501641750336,
-0.15220364928245544,
-0.18796531856060028,
0.0366438589990139,
-0.02974788099527359,
-0.10282598435878754,
0.022019000723958015,
0.029453158378601074,
-0.06967076659202576,
0.02238346077501774,
0.1427535116672516,
-0.10206039994955063,
0.051592033356428146,
-0.27165159583091736,
-0.1715938150882721,
-0.06585682183504105,
-0.025845954194664955,
-0.007345964200794697,
0.01241085771471262,
-0.0010092189768329263,
0.047266922891139984,
-0.20188692212104797,
-0.005631127394735813,
0.09329266101121902,
-0.25229454040527344,
0.02776304818689823,
0.21345718204975128,
-0.010520953685045242,
0.09873088449239731,
-0.05590669438242912,
0.14438565075397491,
0.03173782303929329,
-0.019559340551495552,
-0.1924813836812973,
-0.070224329829216,
-0.07177317887544632,
0.162109375,
-0.0823177620768547,
-0.11764442175626755,
0.24176421761512756,
0.009283576160669327,
-0.026472626253962517,
0.15598991513252258,
-0.029037300497293472,
-0.009749599732458591,
0.04555726423859596,
0.01668328419327736,
-0.010545015335083008,
0.1551385223865509,
0.17108163237571716,
-0.08598228543996811,
-0.10847756266593933,
-0.030579885467886925,
-0.2373785674571991,
0.2470305860042572,
-0.01911027915775776,
0.12945520877838135,
-0.20086053013801575,
0.018443629145622253,
-0.3247532844543457,
-0.0012029389617964625,
-0.010316703468561172,
-0.028618358075618744,
-0.006935348734259605,
0.009301352314651012,
-0.050316113978624344,
0.0739501491189003,
0.14580395817756653,
0.1393439620733261,
-0.11465669423341751,
0.060509420931339264,
-0.052172139286994934,
0.14876529574394226,
0.05827285721898079,
0.061183393001556396,
0.04079163819551468,
0.07037676870822906,
-0.008353544399142265,
-0.21633195877075195,
-0.029873060062527657,
-0.07057386636734009,
-0.08445251733064651,
-0.0130265261977911,
-0.13896764814853668,
0.11386743932962418,
-0.022273007780313492,
-0.07913482189178467,
-0.06810981780290604,
0.07626928389072418,
0.017650218680500984,
-0.008536403998732567,
-0.035703565925359726,
-0.012481719255447388,
0.022218508645892143,
-0.014872739091515541,
-0.1519843488931656,
0.02295425534248352,
0.10455024242401123,
0.07257117331027985,
-0.1489023119211197,
-0.011344035156071186,
-0.017298875376582146,
0.06959983706474304,
0.03884255141019821,
-0.10402916371822357,
0.04283881187438965,
-0.10747409611940384,
-0.08414466679096222,
0.022628657519817352,
-0.005062851123511791,
-0.0418001152575016,
0.13524691760540009,
0.03997812792658806,
0.040150050073862076,
-0.016940169036388397,
-0.04259050637483597,
-0.048133596777915955,
-0.07602019608020782,
0.07334327697753906,
0.05418020859360695,
0.027240034192800522,
-0.1915341019630432,
0.01154522504657507,
-0.048245880752801895,
0.09175369143486023,
-0.11856856942176819,
0.014575321227312088,
-0.08105122298002243,
0.1604209989309311,
0.0349995456635952,
0.09055875241756439,
-0.19562625885009766,
0.02605881541967392,
-0.06191767752170563,
0.1854621320962906,
-0.04451294615864754,
-0.11786319315433502,
0.2698904871940613,
-0.09105797111988068,
-0.040079716593027115,
0.056803084909915924,
0.06560484319925308,
-0.06272535026073456,
0.068723164498806,
0.4434472322463989,
-0.06556011736392975,
-0.07118581980466843,
0.05080527812242508,
0.17805561423301697,
-0.1262815296649933,
-0.09372174739837646,
0.09990617632865906,
-0.1480535864830017,
-0.211008220911026,
0.030864350497722626,
0.028955968096852303,
0.1494358479976654,
-0.06205282360315323,
-0.012456154450774193,
0.058214303106069565,
-0.013022401370108128,
0.046677324920892715,
0.03563477098941803,
0.11109840869903564,
-0.06493768095970154,
0.06851828098297119,
-0.16232267022132874,
0.016065504401922226,
0.1209988072514534,
-0.015012580901384354,
-0.04126624017953873,
0.14286154508590698,
-0.03809087723493576,
0.07199656218290329,
-0.07730832695960999,
-0.1804673671722412,
0.027612121775746346,
0.05621999502182007,
0.028122514486312866,
0.09176547825336456,
0.09526687115430832,
-0.039257392287254333,
0.0013902259524911642,
0.0329861082136631,
0.061223939061164856,
-0.007701692637056112,
0.015235940925776958,
-0.015374142676591873,
0.12888981401920319,
-0.07010363042354584,
-0.04155188798904419,
-0.09715848416090012,
-0.00889967754483223,
0.2288777232170105,
-0.01933911070227623,
0.02257734164595604,
-0.06854789704084396,
0.033186767250299454,
-0.0012386917369440198,
0.09506335854530334,
-0.017756229266524315,
0.06063338369131088,
-0.022011179476976395,
-0.06201287358999252,
0.11652727425098419,
-0.043086208403110504,
0.24556174874305725,
0.10792262107133865,
-0.07513239979743958,
-0.01741042546927929,
-0.0871582105755806,
-0.007020947523415089,
0.022898653522133827,
0.08814648538827896,
-0.04863424599170685,
0.06471672654151917,
-0.037898752838373184,
-0.0013588295551016927,
0.018808960914611816,
-0.008487841114401817,
-0.030526969581842422,
-0.04284367710351944,
-0.08270563185214996,
0.09057542681694031,
0.0691855251789093,
-0.13670015335083008,
0.17748047411441803,
0.2472171038389206,
0.1500423550605774,
0.2487964630126953,
-0.06485911458730698,
-0.014139159582555294,
-0.02016172744333744,
0.03673918917775154,
-0.020436765626072884,
0.13109654188156128,
-0.18929845094680786,
-0.032152432948350906,
0.02558354288339615,
0.029807843267917633,
0.10872193425893784,
-0.1365325003862381,
-0.1145850270986557,
-0.0379912331700325,
-0.047677598893642426,
-0.08257206529378891,
0.07034620642662048,
-0.12104500830173492,
0.03338077291846275,
0.07256745547056198,
0.0073080710135400295,
0.12201625853776932,
0.015417544171214104,
-0.055278971791267395,
0.0998256728053093,
-0.14543165266513824,
-0.2384990155696869,
-0.04642500355839729,
-0.10990478098392487,
0.001206184271723032,
0.05318264663219452,
0.016633260995149612,
-0.21265560388565063,
-0.01741623878479004,
0.11141498386859894,
0.06650645285844803,
-0.18111048638820648,
0.024138791486620903,
0.029385030269622803,
-0.004455238115042448,
-0.10212790220975876,
-0.012687300331890583,
-0.05387670546770096,
-0.11039627343416214,
-0.0691843032836914,
0.08163908869028091,
-0.06936442852020264,
0.11164893209934235,
0.1582336574792862,
0.11141853034496307,
0.11249161511659622,
-0.011774544604122639,
0.1976311057806015,
-0.14119699597358704,
-0.14489109814167023,
0.06405922025442123,
-0.014498869888484478,
0.03640124574303627,
0.08232609927654266,
0.04930112138390541,
-0.14269955456256866,
-0.04848511889576912,
-0.007545206230133772,
-0.1497725397348404,
-0.1323675513267517,
-0.05164776369929314,
-0.10658133774995804,
0.12379065901041031,
-0.06248227879405022,
0.10150982439517975,
0.11162466555833817,
0.017522823065519333,
0.11151766777038574,
-0.06246228888630867,
-0.054680291563272476,
-0.04807431995868683,
0.06297076493501663,
-0.05410824716091156,
-0.04205694422125816,
-0.06721562892198563,
-0.008002115413546562,
0.1349310278892517,
0.10885956883430481,
0.07581131905317307,
0.2265089601278305,
0.02780294418334961,
0.05355561524629593,
0.040789585560560226,
0.16015571355819702,
0.015284501947462559,
-0.0046128155663609505,
-0.08788388222455978,
-0.014365277253091335,
-0.0019687749445438385,
-0.031080376356840134,
-0.006052241660654545,
0.1340780407190323,
-0.2559821307659149,
0.03235609456896782,
-0.2989844083786011,
0.11946471780538559,
-0.1565471589565277,
0.07426489144563675,
0.05220162868499756,
0.030080994591116905,
0.08841689676046371,
0.035069406032562256,
-0.02871096506714821,
0.09149409085512161,
0.11694692075252533,
-0.12628670036792755,
0.01540512777864933,
0.04918349161744118,
0.052707213908433914,
-0.0142430504783988,
0.0931062400341034,
-0.11024625599384308,
-0.0737583339214325,
-0.0024255106691271067,
0.07025767862796783,
-0.2099330574274063,
0.23986183106899261,
0.03523903712630272,
-0.10871971398591995,
-0.021638909354805946,
-0.0547538623213768,
0.03316742554306984,
0.08983159810304642,
0.1342458724975586,
0.11251148581504822,
-0.11371640861034393,
-0.12470904737710953,
0.029020745307207108,
0.03679748624563217,
0.1757190227508545,
-0.09047917276620865,
-0.14164063334465027,
0.001811441034078598,
0.05263577029109001,
-0.053646381944417953,
0.07645093649625778,
-0.05327983945608139,
-0.0941789522767067,
0.03495060279965401,
0.04520740360021591,
0.00641082925722003,
-0.019971303641796112,
0.08110581338405609,
-0.02520396187901497,
0.085345059633255,
-0.04878882318735123,
0.00847524031996727,
-0.10202991217374802,
-0.03634759038686752,
0.04376819357275963,
-0.0722225159406662,
0.01614394783973694,
-0.09818518906831741,
-0.15651735663414001,
-0.08556577563285828,
-0.15303048491477966,
0.12497064471244812,
-0.052672382444143295,
0.10244213044643402,
-0.047614291310310364,
0.147609144449234,
-0.013274060562252998,
0.030878636986017227,
-0.05167607590556145,
0.028036773204803467,
0.011671020649373531,
-0.14858771860599518,
0.20959575474262238,
-0.1476162225008011,
-0.023819662630558014,
0.16589532792568207,
0.05426561459898949,
0.1161220371723175,
0.04555299133062363,
-0.0879630371928215,
0.23518426716327667,
0.2702784240245819,
-0.0007818902959115803,
0.17838320136070251,
0.2352202981710434,
-0.026693791151046753,
-0.2436053603887558,
-0.07260585576295853,
-0.2063993662595749,
-0.039628319442272186,
0.0004186074365861714,
-0.282958060503006,
0.06042884290218353,
0.17210599780082703,
-0.07570867985486984,
0.4319494664669037,
-0.22352926433086395,
0.03153151646256447,
0.13982820510864258,
-0.04242865741252899,
0.6181237101554871,
-0.1820172369480133,
-0.16550765931606293,
0.052592549473047256,
-0.1248052790760994,
0.11609237641096115,
-0.005267696920782328,
0.10048385709524155,
-0.00011838242062367499,
-0.02595684304833412,
0.03428659215569496,
-0.0409976989030838,
0.23620888590812683,
0.018790103495121002,
0.045043930411338806,
-0.09004033356904984,
-0.1538960188627243,
0.10746775567531586,
0.02556895837187767,
-0.10341835021972656,
0.03920651972293854,
-0.06092366203665733,
-0.10915451496839523,
0.011575369164347649,
-0.08317004889249802,
0.03433287888765335,
0.09550272673368454,
-0.050003789365291595,
-0.0652989074587822,
0.024777809157967567,
-0.16975140571594238,
0.028226720169186592,
0.1660151481628418,
-0.08661750704050064,
0.17001861333847046,
-0.04084239527583122,
-0.0947834923863411,
-0.15362800657749176,
-0.020637191832065582,
-0.07918675988912582,
-0.01597081869840622,
0.10419487953186035,
-0.11003783345222473,
0.006433290895074606,
0.09035904705524445,
0.002910176757723093,
0.07882846146821976,
0.09883374720811844,
-0.08716033399105072,
0.05550702288746834,
0.1730797290802002,
-0.21496161818504333,
-0.1694899946451187,
-0.04902869462966919,
-0.1887752115726471,
0.2065081000328064,
0.03903897479176521,
0.04895683750510216,
0.16432031989097595,
0.015995748341083527,
-0.010867753997445107,
-0.020683420822024345,
-0.11664224416017532,
0.00450828718021512,
0.04868127405643463,
-0.005741522181779146,
-0.11094820499420166,
0.13042977452278137,
0.05625306814908981,
-0.010265284217894077,
-0.04014173522591591,
0.1808832287788391,
-0.06324239075183868,
-0.06105973571538925,
-0.29144585132598877,
0.07338178157806396,
-0.10203809291124344,
-0.033191971480846405,
0.08307401835918427,
-0.024927617982029915,
-0.0012370682088658214,
0.14441034197807312,
0.009444275870919228,
0.1295502781867981,
0.031338974833488464,
0.03218937665224075,
0.14084547758102417,
-0.13805074989795685,
-0.14429166913032532,
-0.029582731425762177,
-0.08434601873159409,
-0.12847381830215454,
-0.016780147328972816,
0.1751313954591751,
-0.08363176882266998,
-0.12467111647129059,
-0.2756369411945343,
0.049299292266368866,
-0.0641724020242691,
-0.1138453483581543,
-0.03101496584713459,
-0.06544762849807739,
0.052310146391391754,
-0.040101904422044754,
0.014005003497004509,
-0.023109296336770058,
-0.14451682567596436,
0.0458921417593956,
0.06695213168859482,
0.03172319754958153,
-0.02931683138012886,
0.0015236766776069999,
0.15014788508415222,
0.026510147377848625,
0.16621503233909607,
0.22043149173259735,
0.061838917434215546,
0.20056213438510895,
-0.2713247239589691,
-0.10004157572984695,
0.10868333280086517,
-0.07527677714824677,
0.021882841363549232,
0.13841275870800018,
-0.01911449432373047,
-0.0495067797601223,
-0.03201347589492798,
0.08917038887739182,
-0.017281996086239815,
-0.08984966576099396,
-0.04857974499464035,
-0.003589637577533722,
-0.18503929674625397,
-0.0007536212215200067,
-0.15319249033927917,
0.1420021951198578,
0.04460230842232704,
-0.062356118112802505,
0.07465137541294098,
0.05997058004140854,
0.03977793827652931,
0.006764960940927267,
0.018739836290478706,
-0.14650356769561768,
0.01704270951449871,
-0.025170978158712387,
-0.006106532644480467,
0.03402095288038254,
0.34655115008354187,
-0.0466112419962883,
-0.07675225287675858,
-0.019784720614552498,
0.1001124382019043,
0.13863220810890198,
-0.009452453814446926,
0.13600659370422363,
0.13898764550685883,
-0.07470680773258209,
-0.12456237524747849,
0.10025309771299362,
-0.04034053534269333,
-0.15969179570674896,
0.12802298367023468,
-0.0435095950961113,
-0.016280202195048332,
0.04011611267924309,
-0.03383811563253403,
-0.08241409808397293,
0.04869242012500763,
-0.08193223923444748,
-0.03468599542975426,
-0.03921830281615257,
-0.019609715789556503,
-0.02835456281900406,
0.179523304104805,
-0.03646359592676163,
0.07318142801523209,
-0.02748848870396614,
0.010194642469286919,
-0.10395175963640213,
-0.1028568297624588,
0.05173351243138313,
-0.12340104579925537,
0.07964924722909927,
-0.03694985434412956,
0.030445387586951256,
0.22815105319023132,
0.02754553034901619,
0.015633730217814445,
0.13255921006202698,
-0.00819331593811512,
-0.0877854973077774,
0.03996758162975311,
-0.044342756271362305,
0.021794743835926056,
-0.030855976045131683,
-0.07628626376390457,
-0.0880078375339508,
-0.10075201094150543,
-0.049825526773929596,
0.03320961445569992,
-0.030442843213677406,
-0.05212388187646866,
-0.14976045489311218,
-0.02720625326037407,
-0.07237301766872406,
0.11920249462127686,
-0.09342960268259048,
0.08832328021526337,
-0.012045936658978462,
0.0026839354541152716,
0.037163145840168,
0.1505078673362732,
0.010094218887388706,
0.10494716465473175,
0.006677085533738136,
0.09218452870845795,
-0.06759306788444519,
0.14643312990665436,
-0.12665413320064545,
-0.02135086990892887,
-0.03415476530790329,
0.2331210970878601,
0.20847657322883606,
-0.11358945816755295,
0.009311644360423088,
0.03202449902892113,
0.04839635267853737,
0.185939759016037,
0.12599588930606842,
0.01761433109641075,
0.33329761028289795,
-0.059357043355703354,
-0.02227349951863289,
0.05721667781472206,
-0.00022221643303055316,
-0.06214975565671921,
0.0716261938214302,
0.08921460807323456,
0.013963594101369381,
-0.1257423460483551,
0.11072274297475815,
-0.21343208849430084,
0.15216094255447388,
0.07192383706569672,
-0.18375952541828156,
-0.009178245440125465,
-0.05186039209365845,
0.008210902102291584,
-0.027973614633083344,
0.13407447934150696,
-0.07003656774759293,
-0.1739543378353119,
-0.19977876543998718,
0.060681428760290146,
-0.35512542724609375,
-0.20812080800533295,
0.06384200602769852,
0.1383514702320099,
0.10808566957712173,
-0.06061858683824539,
-0.013316533528268337,
0.006446295417845249,
0.01029437780380249,
-0.019556531682610512,
0.028526417911052704,
-0.008326482027769089,
-0.05453765019774437,
-0.25444141030311584,
-0.006056090816855431,
0.0625600665807724,
-0.15240277349948883,
0.05618175491690636,
-0.017780732363462448,
-0.008800189942121506,
0.13029517233371735,
-0.021711476147174835,
0.03442413732409477,
0.00029493181500583887,
-0.16273388266563416,
0.031801287084817886,
0.035038504749536514,
0.03614772483706474,
-0.010639974847435951,
-0.04227915778756142,
-0.002239778870716691,
0.07848605513572693,
-0.054354216903448105,
-0.1438787877559662,
0.11021588742733002,
-0.026462025940418243,
0.21526864171028137,
-0.06517954170703888,
-0.033111389726400375,
0.023098714649677277,
-0.07031320035457611,
0.2018292248249054,
-0.03690796345472336,
0.05650625377893448,
0.1586160659790039,
0.018734993413090706,
0.019857894629240036,
-0.30062609910964966,
0.08813683688640594,
-0.024517416954040527,
0.006894893944263458,
-0.05270370468497276
] |
null | null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.7.2.dev0 | {"library_name": "peft", "base_model": "bofenghuang/vigostral-7b-chat"} | null | AscheZ/ALIE_1.0 | [
"peft",
"safetensors",
"mistral",
"arxiv:1910.09700",
"base_model:bofenghuang/vigostral-7b-chat",
"region:us"
] | 2024-02-11T05:59:37+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #safetensors #mistral #arxiv-1910.09700 #base_model-bofenghuang/vigostral-7b-chat #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
### Framework versions
- PEFT 0.7.2.dev0 | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact",
"### Framework versions\n\n- PEFT 0.7.2.dev0"
] | [
"TAGS\n#peft #safetensors #mistral #arxiv-1910.09700 #base_model-bofenghuang/vigostral-7b-chat #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact",
"### Framework versions\n\n- PEFT 0.7.2.dev0"
] | [
44,
6,
3,
54,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4,
14
] | [
"passage: TAGS\n#peft #safetensors #mistral #arxiv-1910.09700 #base_model-bofenghuang/vigostral-7b-chat #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\n\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact### Framework versions\n\n- PEFT 0.7.2.dev0"
] | [
-0.1113068088889122,
0.20846091210842133,
-0.0033847871236503124,
0.02556566707789898,
0.07632558047771454,
0.009681041352450848,
0.05920478701591492,
0.13210907578468323,
0.030611630529165268,
0.12680651247501373,
0.06206098198890686,
0.11546380072832108,
0.11617325246334076,
0.2201194018125534,
0.004130533896386623,
-0.1758042573928833,
0.019205130636692047,
-0.0666508898139,
0.0220511332154274,
0.11910156160593033,
0.14156673848628998,
-0.09485448896884918,
0.07504332065582275,
-0.024886546656489372,
-0.009619387798011303,
-0.031070420518517494,
-0.07078886032104492,
-0.014347967691719532,
0.04989273101091385,
0.03775264322757721,
0.054329924285411835,
-0.009756864048540592,
0.07990261912345886,
-0.26733317971229553,
0.018554238602519035,
0.04573015123605728,
-0.008331778459250927,
0.08276966959238052,
0.10162457823753357,
-0.043829258531332016,
0.12949888408184052,
-0.02509811520576477,
0.12911830842494965,
0.08469236642122269,
-0.10597168654203415,
-0.21355755627155304,
-0.06650170683860779,
0.08297671377658844,
0.18117420375347137,
0.07638099044561386,
-0.043867770582437515,
0.11838024854660034,
-0.05931193009018898,
0.03046630695462227,
0.0751551166176796,
-0.10865112394094467,
-0.07047904282808304,
0.07049446552991867,
0.13580761849880219,
0.08232384920120239,
-0.12497443705797195,
-0.0352296382188797,
0.03392969071865082,
0.047760844230651855,
0.055071186274290085,
0.00656661344692111,
0.15019282698631287,
0.028126079589128494,
-0.14674171805381775,
-0.04839356243610382,
0.11599808931350708,
0.008228842169046402,
-0.03950187563896179,
-0.21559275686740875,
-0.002406939398497343,
-0.08627580851316452,
-0.04381948709487915,
-0.04708023741841316,
0.03322609141469002,
0.016729718074202538,
0.12594883143901825,
-0.05017979443073273,
-0.08275000005960464,
-0.011878998018801212,
0.111439049243927,
0.05698612332344055,
0.01430174894630909,
-0.023480720818042755,
-0.00047392945270985365,
0.11425350606441498,
0.05726858228445053,
-0.1330702304840088,
-0.06351475417613983,
-0.06547507643699646,
-0.03517230227589607,
-0.02670109272003174,
0.044830478727817535,
0.021381642669439316,
0.052546270191669464,
0.2747715711593628,
-0.030571212992072105,
0.06471940875053406,
0.0299663245677948,
0.019576434046030045,
0.028571978211402893,
0.1098456084728241,
-0.02887049689888954,
-0.1799648404121399,
-0.013256117701530457,
0.10047955811023712,
-0.000018542215912020765,
-0.03187868744134903,
-0.05634298920631409,
0.028089990839362144,
0.03689508140087128,
0.1219383105635643,
0.11440775543451309,
-0.03147580102086067,
-0.0684630423784256,
-0.05634385347366333,
0.20915810763835907,
-0.14943085610866547,
0.05247386544942856,
0.028727997094392776,
-0.0030377814546227455,
-0.06487040221691132,
0.007098749279975891,
0.013599350117146969,
-0.03607752546668053,
0.07982782274484634,
-0.06660518050193787,
-0.04337523877620697,
-0.1155790239572525,
-0.03995294123888016,
0.039359200745821,
-0.013539495877921581,
-0.044766489416360855,
-0.03806021437048912,
-0.07273221015930176,
-0.11054927855730057,
0.10172957181930542,
-0.05991705507040024,
-0.055810701102018356,
-0.030405381694436073,
-0.07970459759235382,
0.019714219495654106,
0.035448115319013596,
0.07622888684272766,
-0.024781344458460808,
0.0450889952480793,
-0.016568690538406372,
0.06873467564582825,
0.07611144334077835,
0.03528156131505966,
-0.07605748623609543,
0.06262480467557907,
-0.19129344820976257,
0.08125454932451248,
-0.07502612471580505,
0.04223732277750969,
-0.16570879518985748,
-0.0025801353622227907,
-0.0021800606045871973,
0.029172595590353012,
0.048291634768247604,
0.15752190351486206,
-0.2090984731912613,
-0.03588936850428581,
0.1790682077407837,
-0.10358038544654846,
-0.12399762123823166,
0.03801432251930237,
-0.037193961441516876,
0.1733841598033905,
0.03637075051665306,
0.030074074864387512,
0.09488946199417114,
-0.1516043096780777,
-0.01880129799246788,
-0.02668548747897148,
0.01764642260968685,
0.0691947266459465,
0.07605397701263428,
-0.09118816256523132,
0.006440979894250631,
0.008395316079258919,
-0.05429854243993759,
-0.0158535148948431,
-0.04104292392730713,
-0.09983991086483002,
0.009303543716669083,
-0.08111310750246048,
0.004444662947207689,
0.0037813379894942045,
-0.09310007840394974,
-0.00909181497991085,
-0.14511197805404663,
-0.04196173697710037,
0.07813785970211029,
0.0071570249274373055,
-0.010916623286902905,
-0.08771165460348129,
0.0526902861893177,
-0.03835873678326607,
-0.013121042400598526,
-0.1502203345298767,
-0.0073509481735527515,
0.02544943429529667,
-0.13450053334236145,
0.011444062925875187,
-0.12644189596176147,
0.07054959237575531,
0.008187737315893173,
-0.04995690658688545,
-0.04204532504081726,
0.003194289281964302,
-0.011627236381173134,
-0.07283635437488556,
-0.2320340871810913,
-0.025615239515900612,
-0.05970222130417824,
0.14247451722621918,
-0.22691746056079865,
0.042868152260780334,
0.005636720918118954,
0.1190498098731041,
0.010380014777183533,
-0.06175005063414574,
0.024437395855784416,
-0.05601521208882332,
-0.024051373824477196,
-0.0710792988538742,
-0.0037237710785120726,
0.0021271875593811274,
-0.02546881139278412,
0.020307203754782677,
-0.12672726809978485,
-0.06957486271858215,
0.09148845076560974,
0.07527781277894974,
-0.1439594030380249,
0.006362781394273043,
-0.040871761739254,
-0.057390667498111725,
-0.0628250315785408,
-0.06922036409378052,
0.08486837893724442,
0.052001554518938065,
0.048191532492637634,
-0.08615989238023758,
-0.07050482928752899,
0.004477163311094046,
-0.01389825064688921,
-0.0232094619423151,
0.12990215420722961,
0.08361843228340149,
-0.09962493181228638,
0.09383689612150192,
0.06716738641262054,
0.03611987456679344,
0.09245602786540985,
-0.01663353107869625,
-0.1025768294930458,
-0.028474848717451096,
0.05973299220204353,
0.0185687355697155,
0.15717168152332306,
-0.07699138671159744,
0.04405184090137482,
0.04454254359006882,
-0.05077993497252464,
0.04627188295125961,
-0.08968258649110794,
0.010506730526685715,
0.001296323724091053,
-0.017540905624628067,
0.038522426038980484,
-0.015984738245606422,
0.001577648799866438,
0.09156280755996704,
0.06683047115802765,
0.018591947853565216,
0.005720226559787989,
-0.036915138363838196,
-0.14050033688545227,
0.1760943979024887,
-0.09476958215236664,
-0.232263445854187,
-0.14840547740459442,
0.045138295739889145,
0.05908622965216637,
-0.011512991972267628,
0.034184299409389496,
-0.0547897107899189,
-0.09005285799503326,
-0.08674828708171844,
0.013576654717326164,
0.034280870109796524,
-0.056175146251916885,
-0.05893414467573166,
0.03267529979348183,
0.026932524517178535,
-0.12627893686294556,
0.026869863271713257,
0.05356169119477272,
-0.004252058919519186,
-0.008517253212630749,
0.03376626968383789,
0.08864327520132065,
0.2025614231824875,
0.004710331559181213,
0.0032698537688702345,
0.05448389798402786,
0.2892758846282959,
-0.15707309544086456,
0.12121497839689255,
0.13061855733394623,
-0.05622953176498413,
0.07864578813314438,
0.18852120637893677,
0.02823881432414055,
-0.09267820417881012,
0.018985267728567123,
0.031942326575517654,
-0.02825513295829296,
-0.27096933126449585,
-0.04847743734717369,
-0.026881415396928787,
-0.07108589261770248,
0.08702630549669266,
0.09051655232906342,
0.09634210914373398,
0.026446672156453133,
-0.06965948641300201,
-0.08688690513372421,
0.039523448795080185,
0.11627369374036789,
-0.04098623991012573,
0.006951062008738518,
0.08197027444839478,
-0.04698922485113144,
0.00920968595892191,
0.08835180103778839,
-0.01397579163312912,
0.1353723406791687,
0.06131453067064285,
0.11953886598348618,
0.07818067073822021,
0.0672077164053917,
-0.0036090752109885216,
0.03329756483435631,
-0.009634100832045078,
0.024615658447146416,
0.01503939088433981,
-0.08912006765604019,
0.020140940323472023,
0.10933612287044525,
0.017510809004306793,
0.019761724397540092,
0.016316363587975502,
-0.07360357791185379,
0.040784236043691635,
0.19433088600635529,
0.027087338268756866,
-0.19686013460159302,
-0.08304183930158615,
0.05701852962374687,
-0.07423865795135498,
-0.1505446434020996,
-0.01473226584494114,
0.014773406088352203,
-0.15708228945732117,
0.015482885763049126,
-0.03914780542254448,
0.1159391775727272,
-0.060447704046964645,
-0.040947217494249344,
0.09410730749368668,
0.04726604372262955,
-0.03392202407121658,
0.041830308735370636,
-0.18981096148490906,
0.1079765185713768,
0.028966674581170082,
0.06970620155334473,
-0.08571235835552216,
0.0878429114818573,
-0.005482716951519251,
-0.01175630185753107,
0.15965962409973145,
-0.002279815962538123,
-0.0707555040717125,
-0.0767759457230568,
-0.0775434672832489,
-0.013610458932816982,
0.0850655809044838,
-0.1387859582901001,
0.07445719838142395,
-0.025633810088038445,
-0.03615349903702736,
-0.007475290447473526,
-0.09806906431913376,
-0.11167753487825394,
-0.16374829411506653,
0.06029391288757324,
-0.08911971747875214,
0.0211025383323431,
-0.0776343122124672,
-0.050558269023895264,
0.03710923343896866,
0.1724252700805664,
-0.20334815979003906,
-0.10788179188966751,
-0.14334508776664734,
-0.09710246324539185,
0.15641692280769348,
-0.05133803188800812,
0.0877680778503418,
-0.012700526043772697,
0.16090591251850128,
-0.01120086945593357,
-0.019980022683739662,
0.08138992637395859,
-0.09494578093290329,
-0.18403175473213196,
-0.050574544817209244,
0.1876600980758667,
0.13370628654956818,
0.028725001960992813,
-0.012899561785161495,
0.028191760182380676,
-0.05968797206878662,
-0.10927528887987137,
0.029345013201236725,
0.13619127869606018,
0.0614008791744709,
-0.017110854387283325,
-0.03854672238230705,
-0.10493063181638718,
-0.06821805983781815,
-0.04096410423517227,
-0.011954248882830143,
0.20460230112075806,
-0.07002981752157211,
0.16224795579910278,
0.12411075085401535,
-0.06436268985271454,
-0.20274561643600464,
0.03658701106905937,
0.03861753270030022,
0.014806008897721767,
0.020050467923283577,
-0.19844995439052582,
0.07791168987751007,
-0.02760600671172142,
-0.07411566376686096,
0.17775557935237885,
-0.20827358961105347,
-0.12834432721138,
0.0955088660120964,
0.016484636813402176,
-0.20408719778060913,
-0.15309886634349823,
-0.11004865169525146,
-0.009177458472549915,
-0.11923263967037201,
0.05461033061146736,
0.019115403294563293,
0.011839713901281357,
0.01272937934845686,
0.016436606645584106,
0.040440138429403305,
-0.04401126131415367,
0.19851142168045044,
-0.03785134479403496,
-0.005387643352150917,
-0.05278632417321205,
-0.09360764920711517,
0.008384202606976032,
-0.05674626678228378,
0.11423671245574951,
-0.01755552552640438,
0.03104964643716812,
-0.15862461924552917,
-0.041221462190151215,
-0.06670904904603958,
0.03159293904900551,
-0.09776398539543152,
-0.07889054715633392,
-0.045818667858839035,
0.08468793332576752,
0.08972401171922684,
-0.011207309551537037,
0.022641345858573914,
-0.09359759092330933,
0.10224635899066925,
0.19991318881511688,
0.1772029846906662,
0.060064949095249176,
-0.04980091378092766,
0.028498293831944466,
-0.03591479733586311,
0.04491984099149704,
-0.21616913378238678,
0.03656062111258507,
0.06621231138706207,
0.028021806851029396,
0.07790479063987732,
-0.005009897984564304,
-0.16385884582996368,
-0.08592341095209122,
0.08462721109390259,
-0.05625629052519798,
-0.17152391374111176,
-0.030100760981440544,
0.04328012466430664,
-0.20333927869796753,
-0.04938770458102226,
0.04380958899855614,
-0.01528642512857914,
-0.04509608447551727,
0.02541101910173893,
0.08132805675268173,
-0.019340956583619118,
0.0941455140709877,
0.08782676607370377,
0.08622725307941437,
-0.09429708123207092,
0.0526735857129097,
0.0832994282245636,
-0.020914850756525993,
0.024583600461483,
0.1517903059720993,
-0.038397740572690964,
-0.04389023780822754,
0.07754454016685486,
0.12058768421411514,
-0.005486288573592901,
-0.04012029618024826,
0.012233184650540352,
-0.04940563440322876,
0.07238458096981049,
0.13319699466228485,
0.015857623890042305,
-0.011615880765020847,
0.07414963841438293,
0.03236033022403717,
-0.08778905868530273,
0.11958270519971848,
0.047152455896139145,
0.021280847489833832,
-0.023842941969633102,
-0.0225316621363163,
-0.015661410987377167,
-0.004969357047230005,
-0.013241920620203018,
-0.0032035973854362965,
-0.09984530508518219,
-0.0010114498436450958,
-0.10800117254257202,
0.021990882232785225,
-0.07562889903783798,
0.0010035461746156216,
0.015238377265632153,
-0.051493193954229355,
-0.0013210936449468136,
-0.007139339577406645,
-0.07860368490219116,
-0.05534471571445465,
-0.030919335782527924,
0.08215730637311935,
-0.14252926409244537,
0.031967904418706894,
0.07456260174512863,
-0.10401064157485962,
0.06535359472036362,
-0.007362846750766039,
0.017035430297255516,
0.007796287536621094,
-0.1499207466840744,
0.054172053933143616,
-0.030591165646910667,
-0.01113983429968357,
0.006814941298216581,
-0.17350392043590546,
-0.0060358974151313305,
-0.048093002289533615,
-0.07122251391410828,
0.011341702193021774,
-0.015561005100607872,
-0.12470632046461105,
0.10886333882808685,
0.001291486551053822,
-0.06747233122587204,
-0.013535694219172001,
0.055881939828395844,
0.07689787447452545,
-0.012378119863569736,
0.09439682215452194,
-0.026633787900209427,
0.08646479994058609,
-0.18423260748386383,
-0.004742135293781757,
-0.017920132726430893,
0.04047142714262009,
-0.01658201776444912,
-0.040070243179798126,
0.05503256991505623,
-0.014285484328866005,
0.14932376146316528,
-0.002144495490938425,
0.07336688786745071,
0.0507563054561615,
0.005156885366886854,
0.03249361366033554,
0.07354842871427536,
0.060914672911167145,
-0.011758792214095592,
-0.006239642389118671,
0.02923968993127346,
0.0012160713085904717,
-0.04469149187207222,
-0.12855826318264008,
0.06582977622747421,
0.18332187831401825,
0.08195124566555023,
0.026846647262573242,
0.009954225271940231,
-0.13598661124706268,
-0.07692180573940277,
0.10412761569023132,
-0.01657918281853199,
-0.030237341299653053,
-0.0687570795416832,
0.2196500301361084,
0.14686237275600433,
-0.19603866338729858,
0.08017671853303909,
-0.043478380888700485,
-0.03411412984132767,
-0.13542570173740387,
-0.16348488628864288,
-0.05809123441576958,
-0.03238219395279884,
-0.03352809697389603,
-0.06495877355337143,
0.05740514025092125,
0.020711392164230347,
-0.003130959812551737,
-0.015562841668725014,
0.0960272029042244,
0.027940627187490463,
-0.04082115739583969,
0.05368313565850258,
0.06235787272453308,
0.04715953767299652,
-0.09478801488876343,
0.014842755161225796,
0.0022749293129891157,
0.013434004038572311,
0.062212299555540085,
0.02932845801115036,
-0.06543692201375961,
0.029558798298239708,
-0.014392809011042118,
-0.11916821449995041,
0.05055671185255051,
-0.009380949661135674,
-0.02376657910645008,
0.15396390855312347,
0.03620464727282524,
0.005271433852612972,
-0.008870099671185017,
0.23899109661579132,
-0.0673244446516037,
-0.0799090787768364,
-0.12998922169208527,
0.07528762519359589,
-0.05811815708875656,
0.028611930087208748,
0.010818859562277794,
-0.12086629867553711,
0.008156436495482922,
0.17427128553390503,
0.1222783550620079,
-0.011198299005627632,
0.01263305451720953,
0.04850640520453453,
0.01083479356020689,
-0.02078772708773613,
0.010788592509925365,
0.053437069058418274,
0.21461398899555206,
-0.07765914499759674,
0.07211559265851974,
-0.01408041175454855,
-0.06737227737903595,
-0.027339480817317963,
0.11149704456329346,
-0.011382766999304295,
-0.010729867033660412,
-0.05849120765924454,
0.1419209986925125,
-0.07472474128007889,
-0.22081208229064941,
0.05200552940368652,
-0.09507910907268524,
-0.13880318403244019,
-0.04853373020887375,
0.017756594344973564,
-0.022246697917580605,
0.015381770208477974,
0.06544113904237747,
-0.05287898704409599,
0.16991852223873138,
0.027513675391674042,
-0.04513239488005638,
-0.10575255006551743,
0.05622285231947899,
-0.1505405455827713,
0.2791304290294647,
0.01756131462752819,
0.03385831415653229,
0.10981841385364532,
-0.017736246809363365,
-0.13600516319274902,
0.006955255754292011,
0.11029709875583649,
-0.05961615592241287,
0.060553353279829025,
0.16114792227745056,
-0.00382023211568594,
0.1233963742852211,
0.06398700177669525,
-0.0581803172826767,
0.035257235169410706,
-0.06381455808877945,
-0.053193822503089905,
-0.11712803691625595,
0.08068034797906876,
-0.09461541473865509,
0.15097883343696594,
0.12544164061546326,
-0.07308004796504974,
-0.007798030506819487,
-0.017912738025188446,
0.07724756747484207,
0.017895013093948364,
0.12622863054275513,
0.004513572435826063,
-0.18385133147239685,
0.04243536666035652,
0.007883922196924686,
0.1076926440000534,
-0.21329927444458008,
-0.05275868624448776,
0.04037262126803398,
-0.015300963073968887,
-0.09143465012311935,
0.12125254422426224,
0.04055134952068329,
0.01509285718202591,
-0.03281036764383316,
-0.07095649838447571,
0.016810601577162743,
0.1511724293231964,
-0.09965584427118301,
-0.013037214055657387
] |
null | null | ml-agents |
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
- A *longer tutorial* to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
### Resume the training
```bash
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser**
1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: nickmiller795/ppo-SnowballTarget
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
| {"library_name": "ml-agents", "tags": ["SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget"]} | reinforcement-learning | nickmiller795/ppo-SnowballTarget | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | 2024-02-11T06:01:19+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us
|
# ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your
browser: URL
- A *longer tutorial* to understand how works ML-Agents:
URL
### Resume the training
### Watch your Agent play
You can watch your agent playing directly in your browser
1. If the environment is part of ML-Agents official environments, go to URL
2. Step 1: Find your model_id: nickmiller795/ppo-SnowballTarget
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play
| [
"# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: nickmiller795/ppo-SnowballTarget\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
"TAGS\n#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us \n",
"# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: nickmiller795/ppo-SnowballTarget\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
50,
207
] | [
"passage: TAGS\n#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us \n# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: nickmiller795/ppo-SnowballTarget\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
-0.04293098300695419,
0.08110262453556061,
-0.0036183821503072977,
0.11149488389492035,
0.16607506573200226,
-0.014176827855408192,
0.15026329457759857,
0.10253836214542389,
0.11864141374826431,
0.07369662821292877,
0.09136107563972473,
0.09092707186937332,
0.05327548086643219,
0.13215865194797516,
0.08378269523382187,
-0.22161905467510223,
-0.04878932982683182,
-0.10773885250091553,
0.006475449074059725,
0.08181493729352951,
0.03752388060092926,
-0.036947306245565414,
0.026583677157759666,
0.05235160142183304,
-0.021221758797764778,
-0.00033926308969967067,
-0.061324577778577805,
-0.04221798852086067,
0.0630168691277504,
-0.0336446613073349,
0.00968227256089449,
-0.05133259296417236,
0.0985390692949295,
-0.16534331440925598,
0.025677170604467392,
0.04752436652779579,
-0.009709960781037807,
-0.018786130473017693,
0.14571723341941833,
0.02799532562494278,
0.12514996528625488,
-0.12852513790130615,
0.10244081914424896,
0.07739071547985077,
-0.05664728954434395,
0.002602792577818036,
-0.07161812484264374,
0.06575489044189453,
0.21227538585662842,
0.14507049322128296,
-0.0053827473893761635,
0.07760024815797806,
-0.0305742509663105,
0.05982872098684311,
0.16144846379756927,
-0.28112971782684326,
-0.07223636656999588,
0.1785164624452591,
-0.04136086627840996,
0.0341523252427578,
-0.013150489889085293,
0.05309877544641495,
-0.019842565059661865,
0.024605371057987213,
-0.008243441581726074,
0.03145627677440643,
0.27417102456092834,
0.015383325517177582,
-0.09626634418964386,
-0.08371596783399582,
-0.0100643839687109,
0.03997299075126648,
-0.0460713692009449,
-0.19443361461162567,
0.011039440520107746,
0.11390134692192078,
0.0032654220703989267,
0.03117252141237259,
0.047696780413389206,
0.01796971820294857,
-0.10016226023435593,
-0.15216122567653656,
-0.028271997347474098,
-0.06698829680681229,
0.10804688185453415,
0.11741612106561661,
-0.031911417841911316,
-0.006155134178698063,
0.03768640384078026,
0.07629856467247009,
0.11069274693727493,
-0.0419432558119297,
-0.02999090775847435,
-0.01786334253847599,
-0.14665478467941284,
-0.015420259907841682,
-0.0355401448905468,
-0.015815991908311844,
0.04343461990356445,
0.15394817292690277,
0.15700161457061768,
0.03982281684875488,
0.03111712820827961,
0.021860692650079727,
-0.002937314799055457,
0.10027249157428741,
0.05264025181531906,
-0.029675930738449097,
0.0034860875457525253,
0.017480045557022095,
0.06211474537849426,
-0.092946358025074,
-0.09001677483320236,
0.052641600370407104,
-0.034516945481300354,
0.1283494383096695,
0.16870395839214325,
-0.028768742457032204,
-0.003470078343525529,
-0.03487882763147354,
0.03468027338385582,
-0.14315183460712433,
0.08526839315891266,
0.05650412663817406,
-0.050093743950128555,
-0.09541048854589462,
-0.06845707446336746,
0.04985852912068367,
-0.08497413247823715,
0.047962065786123276,
0.004716457333415747,
0.05762592330574989,
0.0064287749119102955,
-0.032321806997060776,
0.052806925028562546,
-0.1121034324169159,
-0.011875690892338753,
-0.16063708066940308,
-0.12261157482862473,
-0.0817827433347702,
0.03480476140975952,
-0.04738008975982666,
-0.11896882951259613,
-0.0969032496213913,
0.039984844624996185,
-0.06204329431056976,
0.031837668269872665,
-0.03103681467473507,
-0.06271377950906754,
-0.026899196207523346,
-0.11546999961137772,
0.05451974272727966,
0.17396733164787292,
0.00036431278567761183,
-0.03157176077365875,
0.024715004488825798,
-0.14671285450458527,
0.1576095074415207,
-0.1368214339017868,
0.1535203605890274,
-0.08591052144765854,
0.03524094820022583,
0.10005836188793182,
-0.026036839932203293,
0.05204435810446739,
0.185408815741539,
-0.10017189383506775,
-0.07794804126024246,
0.04380029812455177,
-0.087098628282547,
-0.10724848508834839,
0.05365601181983948,
0.017476988956332207,
0.027981802821159363,
0.0604095496237278,
0.21561087667942047,
0.09622363746166229,
-0.22659198939800262,
0.03470874950289726,
-0.0031849059741944075,
-0.1366523802280426,
-0.006601291708648205,
0.11483661830425262,
-0.0748642235994339,
-0.01356950681656599,
-0.03826306015253067,
-0.11362649500370026,
0.10470481216907501,
-0.009390445426106453,
-0.06102438643574715,
0.023582983762025833,
-0.052691224962472916,
-0.04318176209926605,
-0.0013235480291768909,
0.03846544772386551,
-0.052377041429281235,
-0.056987714022397995,
-0.03602755442261696,
0.03236742690205574,
0.004274346400052309,
0.07064889371395111,
-0.027223926037549973,
0.11899524927139282,
-0.011517036706209183,
0.008581875823438168,
-0.10894335806369781,
-0.141402468085289,
-0.009539511986076832,
0.004307532217353582,
0.08113070577383041,
-0.10489330440759659,
0.10007838904857635,
0.07736002653837204,
0.040517862886190414,
-0.072198785841465,
-0.06104157119989395,
0.016889918595552444,
-0.10375413298606873,
-0.10525757074356079,
-0.06981953233480453,
-0.05414311960339546,
0.11259908974170685,
-0.09741717576980591,
0.06611093878746033,
-0.05094677954912186,
0.10046877712011337,
-0.017400182783603668,
-0.08925390988588333,
0.04225938767194748,
-0.016334909945726395,
0.04702003300189972,
-0.09441442787647247,
0.101426862180233,
0.07155279815196991,
-0.12425537407398224,
0.012677870690822601,
0.045982275158166885,
-0.10035920143127441,
0.12528209388256073,
0.0441475585103035,
-0.007116613909602165,
-0.05450184643268585,
-0.06523190438747406,
0.005017602350562811,
-0.07559804618358612,
0.026191208511590958,
0.1992952823638916,
0.1319335699081421,
0.07791893184185028,
-0.030658038333058357,
-0.06389378756284714,
-0.022905470803380013,
-0.04750654473900795,
-0.06416591256856918,
0.12910723686218262,
0.043460432440042496,
-0.007448321674019098,
0.029389990493655205,
0.003651190083473921,
0.09959772974252701,
0.1110197901725769,
-0.0034378275740891695,
-0.11665159463882446,
0.015577557496726513,
0.04479449614882469,
0.06203336641192436,
0.001553337904624641,
0.05733855813741684,
-0.02323920838534832,
-0.01643609069287777,
-0.05424795299768448,
-0.01291906088590622,
-0.10691270977258682,
-0.0634411871433258,
0.06837709248065948,
-0.00491416035220027,
0.008116073906421661,
-0.07408425211906433,
-0.04237746819853783,
0.027640722692012787,
0.1032574474811554,
0.0012008165940642357,
0.03519422188401222,
-0.03757467120885849,
-0.12880560755729675,
0.04047723859548569,
-0.08591630309820175,
-0.22687648236751556,
-0.11658716946840286,
-0.04882024973630905,
-0.0803566575050354,
0.015597757883369923,
0.0711502954363823,
-0.18993675708770752,
-0.00013633529306389391,
-0.09685197472572327,
0.004301865119487047,
-0.014631339348852634,
-0.03144510090351105,
0.14771533012390137,
0.0933278426527977,
-0.021861206740140915,
-0.06743182241916656,
0.00999793317168951,
0.017113784328103065,
-0.05980846658349037,
-0.016578998416662216,
0.07905101776123047,
0.09813586622476578,
0.07153364270925522,
0.05454642325639725,
0.06404920667409897,
-0.021623099222779274,
0.17331372201442719,
-0.05678767338395119,
0.03254253417253494,
0.05876903235912323,
0.001298138522543013,
0.07217861711978912,
0.008551833219826221,
0.03894141688942909,
-0.001301009557209909,
0.013154204934835434,
0.017308350652456284,
-0.07649044692516327,
-0.20452888309955597,
-0.08982434868812561,
0.002825953299179673,
0.1627330631017685,
0.1743711531162262,
0.09901441633701324,
-0.08247015625238419,
0.021517401561141014,
0.009020209312438965,
-0.11575961858034134,
0.1172790676355362,
0.12973976135253906,
-0.051939956843853,
-0.01015292014926672,
0.03687098249793053,
-0.03371066972613335,
0.05588758736848831,
0.057019006460905075,
-0.058316055685281754,
0.08386772871017456,
0.02970097027719021,
-0.0072993566282093525,
-0.03207924962043762,
-0.04852311313152313,
-0.05121231451630592,
0.13144223392009735,
0.07189571857452393,
0.02371111512184143,
0.02342401072382927,
-0.06930407881736755,
-0.07406787574291229,
0.1262785941362381,
0.13783378899097443,
-0.07221069186925888,
-0.05654541030526161,
0.0944133996963501,
0.05233239009976387,
0.2029101401567459,
-0.0007426018128171563,
-0.1102168932557106,
-0.06349412351846695,
-0.010994820855557919,
-0.11281464248895645,
0.0062712267972528934,
0.04293143004179001,
-0.020546387881040573,
-0.1552385836839676,
0.05213113874197006,
0.0008381321677006781,
0.11580255627632141,
0.022408772259950638,
-0.03162573650479317,
0.06230589747428894,
0.013919737190008163,
-0.033314332365989685,
0.04292440414428711,
-0.1354108452796936,
0.02526945434510708,
-0.0013170738238841295,
0.09944294393062592,
-0.06038893014192581,
0.02363923005759716,
0.08079829812049866,
-0.04402583837509155,
0.16595879197120667,
0.04668460041284561,
-0.062160272151231766,
-0.1333976686000824,
-0.16850928962230682,
-0.0596483089029789,
-0.020067470148205757,
-0.11051692813634872,
0.06807330995798111,
0.038333795964717865,
-0.024276066571474075,
-0.0999264270067215,
0.019085025414824486,
-0.05731590464711189,
-0.12687508761882782,
-0.0421823225915432,
-0.06977052241563797,
0.060180339962244034,
-0.06123160570859909,
-0.0718245655298233,
-0.08247419446706772,
0.16736972332000732,
0.10048189014196396,
-0.09915895015001297,
-0.11631577461957932,
0.011730348691344261,
-0.0525737889111042,
-0.02799883857369423,
0.07413433492183685,
0.0158083513379097,
0.11202049255371094,
-0.11036185920238495,
-0.0556885302066803,
-0.03405356779694557,
-0.10027208924293518,
-0.09170642495155334,
0.03590673953294754,
0.17738138139247894,
0.04652291536331177,
0.08487322926521301,
-0.006723017431795597,
0.10849374532699585,
-0.0016975811449810863,
-0.06886336952447891,
0.12039753794670105,
0.08671268075704575,
-0.034256480634212494,
0.04433642327785492,
0.041436053812503815,
0.0815792977809906,
-0.1282549351453781,
-0.015303720720112324,
0.2101384401321411,
0.265282541513443,
-0.07168681919574738,
0.18600216507911682,
0.019806835800409317,
-0.04586850106716156,
-0.14989764988422394,
-0.048951078206300735,
0.0015079572331160307,
-0.05530275031924248,
0.09844209998846054,
-0.19057568907737732,
0.10042048990726471,
0.014027608558535576,
-0.010688810609281063,
0.039907198399305344,
-0.15343229472637177,
-0.08216243237257004,
0.018046384677290916,
0.09945137053728104,
-0.06580448895692825,
-0.10124512016773224,
-0.07743530720472336,
0.01945529691874981,
-0.08266840130090714,
0.027992315590381622,
-0.08663233369588852,
0.04863091558218002,
0.012412452138960361,
0.025538383051753044,
0.06189277023077011,
-0.05759529769420624,
0.12483811378479004,
-0.03859053924679756,
-0.05667869746685028,
-0.0675751268863678,
0.03420768678188324,
-0.0275238249450922,
-0.0898958295583725,
0.05101611092686653,
-0.015065954998135567,
-0.015784168615937233,
-0.18780319392681122,
-0.05532820522785187,
0.018262965604662895,
0.037881262600421906,
-0.04002960026264191,
-0.07664515823125839,
-0.022180186584591866,
0.05982043594121933,
0.08542237430810928,
0.022196516394615173,
0.10958310961723328,
-0.0024989251978695393,
0.008021305315196514,
0.05613870546221733,
0.028622908517718315,
0.02496643364429474,
-0.13089418411254883,
-0.0555720329284668,
-0.06888959556818008,
0.00645736837759614,
-0.058107662945985794,
-0.019647957757115364,
0.05755578726530075,
0.06298380345106125,
-0.0070166196674108505,
0.05161485821008682,
-0.07955112308263779,
-0.028386613354086876,
0.026489414274692535,
-0.0973493754863739,
-0.11945221573114395,
-0.08917903900146484,
-0.08897434920072556,
0.020617865025997162,
-0.09145765006542206,
0.08132556080818176,
-0.0564001128077507,
-0.00385987083427608,
0.01196597982198,
0.03301424905657768,
-0.0026042028330266476,
0.03822094574570656,
0.01963837444782257,
0.036901939660310745,
-0.07074742764234543,
0.12115373462438583,
0.022381417453289032,
-0.05616817623376846,
0.048832911998033524,
0.20067709684371948,
-0.05641032010316849,
-0.06488056480884552,
-0.04793393611907959,
0.08030034601688385,
0.052889563143253326,
-0.020645346492528915,
-0.03524522855877876,
-0.04579942673444748,
0.11964952200651169,
-0.16074597835540771,
0.004852849990129471,
-0.12018563598394394,
0.005232230294495821,
0.05003033205866814,
-0.058048296719789505,
0.06468389928340912,
-0.018788965418934822,
-0.061015497893095016,
-0.13736054301261902,
0.06523564457893372,
0.026674965396523476,
0.07959800213575363,
-0.01118918601423502,
-0.023988021537661552,
-0.13345974683761597,
0.02231304533779621,
0.0020848247222602367,
-0.003157347207888961,
-0.17068098485469818,
0.02067764662206173,
-0.009583143517374992,
0.030716150999069214,
0.02943759225308895,
0.059023987501859665,
-0.03700755536556244,
-0.10252967476844788,
-0.05335414037108421,
0.05859636515378952,
-0.08586785197257996,
-0.019069980829954147,
-0.028764929622411728,
-0.07687748968601227,
0.0526028610765934,
0.07603827863931656,
-0.018906202167272568,
-0.04393286630511284,
-0.0554165318608284,
0.022280961275100708,
-0.030189214274287224,
-0.047291349619627,
0.04254262149333954,
-0.13037626445293427,
0.02511828951537609,
-0.06154292821884155,
-0.11729568243026733,
0.03752729669213295,
0.10004793107509613,
-0.07229699194431305,
0.04545723646879196,
0.052874427288770676,
-0.08497907221317291,
-0.07485417276620865,
-0.012298770248889923,
0.08597429096698761,
0.049043893814086914,
0.10433530062437057,
-0.08556906878948212,
0.19603773951530457,
-0.11159806698560715,
-0.030204840004444122,
0.012260881252586842,
0.0635971799492836,
0.033090364187955856,
-0.08270258456468582,
0.04240942373871803,
-0.008166337385773659,
0.05598238483071327,
0.07900909334421158,
0.006155886221677065,
0.05806773155927658,
0.048436883836984634,
0.13126979768276215,
0.011921141296625137,
0.09363870322704315,
-0.004800855647772551,
0.01417784858494997,
0.12513591349124908,
-0.004870492499321699,
0.0666341558098793,
-0.05116700753569603,
0.06406321376562119,
0.07142774760723114,
0.09222352504730225,
0.0583418607711792,
0.05526761710643768,
-0.09208957850933075,
-0.16352148354053497,
-0.025296887382864952,
0.04017360135912895,
0.039177488535642624,
-0.05188816785812378,
0.17696203291416168,
0.12520954012870789,
-0.19299334287643433,
0.017717575654387474,
0.0052199712954461575,
0.03667343407869339,
-0.07581587880849838,
-0.09639205038547516,
0.006726487539708614,
-0.13649526238441467,
0.09665729105472565,
-0.01846378669142723,
0.0008582132286392152,
-0.041757360100746155,
0.0044966875575482845,
0.02683422528207302,
0.04730931669473648,
-0.0438062809407711,
0.01589139550924301,
0.049545951187610626,
-0.03625258430838585,
0.00027702772058546543,
-0.0011063216952607036,
-0.08375386148691177,
-0.0398528091609478,
-0.06605243682861328,
-0.015057196840643883,
0.023185009136795998,
-0.005074725951999426,
0.0608195886015892,
0.011200062930583954,
-0.06403601169586182,
0.07449106872081757,
-0.0038652364164590836,
0.026474729180336,
0.21005181968212128,
0.09836839884519577,
-0.04736442118883133,
-0.052552737295627594,
0.2198583036661148,
-0.03138706088066101,
-0.054400306195020676,
-0.08083800226449966,
0.09646813571453094,
-0.04978033900260925,
-0.04847082868218422,
-0.03908109664916992,
-0.162167489528656,
-0.057291463017463684,
0.1733340620994568,
0.12686635553836823,
-0.002031325362622738,
0.007034043315798044,
-0.0629495307803154,
0.004733401816338301,
0.02892252244055271,
0.09004095196723938,
0.0627729669213295,
0.04791124165058136,
-0.09189682453870773,
0.0026923432014882565,
-0.07975012809038162,
-0.10181774944067001,
-0.19269342720508575,
0.045470379292964935,
0.03951941803097725,
-0.033510129898786545,
-0.01841278374195099,
0.13188399374485016,
-0.09981346875429153,
-0.08376903086900711,
0.10881196707487106,
-0.0471687950193882,
-0.0741431787610054,
0.005527353845536709,
0.022261345759034157,
-0.0014412282034754753,
0.11122216284275055,
0.08680951595306396,
0.04837903752923012,
0.00982162356376648,
-0.019967664033174515,
-0.09392876923084259,
0.011397906579077244,
0.04116757586598396,
-0.11698214709758759,
0.2436903566122055,
-0.020089607685804367,
0.0005024887504987419,
0.09928429126739502,
0.06485574692487717,
-0.18594755232334137,
0.010434833355247974,
0.052076052874326706,
-0.17496609687805176,
0.016708966344594955,
0.09108944237232208,
-0.041318271309137344,
0.01380259357392788,
0.05851608142256737,
-0.050528496503829956,
0.004985847044736147,
0.17391103506088257,
0.04437648132443428,
-0.044371597468853,
0.08320518583059311,
-0.1393350064754486,
0.10498075187206268,
0.09627438336610794,
-0.058855198323726654,
0.0051476359367370605,
-0.03240077570080757,
0.002684784820303321,
-0.007013476453721523,
-0.0011715686414390802,
-0.018711136654019356,
-0.12209875136613846,
-0.020870428532361984,
-0.06508833169937134,
0.019251057878136635,
-0.22257308661937714,
-0.13360927999019623,
-0.051684170961380005,
-0.07960253208875656,
-0.045623231679201126,
0.09021222591400146,
0.07904458045959473,
-0.05718035623431206,
0.015765035524964333,
-0.12637439370155334,
0.030586756765842438,
0.152012899518013,
-0.07625555247068405,
0.001940558897331357
] |
null | null | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="Sonwe1e/Texi-Baseline", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
| {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Texi-Baseline", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- 2.71", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | Sonwe1e/Texi-Baseline | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | 2024-02-11T06:03:44+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
| [
"# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
] | [
"TAGS\n#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n",
"# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
] | [
32,
33
] | [
"passage: TAGS\n#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
] | [
0.048862796276807785,
-0.16549694538116455,
-0.005485367961227894,
0.02960980497300625,
0.1345081776380539,
-0.01784728653728962,
0.11895976960659027,
0.07759871333837509,
-0.07461097836494446,
-0.055395450443029404,
0.1418241262435913,
0.09088201075792313,
0.055222880095243454,
0.05699880048632622,
0.09511256217956543,
-0.27440664172172546,
0.048217080533504486,
-0.02918700873851776,
0.05621987581253052,
0.11878681182861328,
0.0670095682144165,
-0.040441032499074936,
0.061956584453582764,
0.11818158626556396,
-0.1018151044845581,
-0.007344264071434736,
0.035402704030275345,
-0.09440053254365921,
0.17413531243801117,
0.07204403728246689,
0.12337774783372879,
0.05132639780640602,
0.179361954331398,
-0.12762396037578583,
0.024310702458024025,
-0.0010275895474478602,
-0.10138072073459625,
-0.03909514099359512,
-0.012415820732712746,
-0.08349097520112991,
0.03230205550789833,
0.23522862792015076,
0.07199250161647797,
0.06632792949676514,
-0.17707863450050354,
-0.06584878265857697,
-0.04375573247671127,
0.069611094892025,
0.14951466023921967,
0.03758616745471954,
-0.033800311386585236,
0.1684885323047638,
-0.2564343810081482,
0.05066783353686333,
0.037275806069374084,
-0.42313119769096375,
0.017119819298386574,
0.1507398933172226,
0.15090937912464142,
0.06909667700529099,
-0.10573802888393402,
0.013512322679162025,
0.051325585693120956,
-0.0005318621988408267,
0.024325110018253326,
0.006554204970598221,
0.15601307153701782,
0.08537693321704865,
-0.1487821787595749,
-0.058576688170433044,
0.17441977560520172,
-0.03788546845316887,
-0.02613203600049019,
-0.039745692163705826,
0.0067160045728087425,
-0.06427708268165588,
-0.004067842848598957,
-0.1777995079755783,
0.00734262028709054,
0.06666424125432968,
-0.014348524622619152,
0.014901017770171165,
-0.035522811114788055,
-0.0966939702630043,
-0.023098144680261612,
-0.08592145889997482,
0.01677769608795643,
-0.006319406442344189,
-0.10187895596027374,
0.05002119392156601,
-0.061138734221458435,
0.0014382408699020743,
-0.05123179033398628,
-0.15047866106033325,
-0.049055423587560654,
-0.03481535613536835,
0.1474713832139969,
-0.0044205985032022,
-0.01873963139951229,
-0.03164304047822952,
0.15474793314933777,
0.049551334232091904,
-0.05370146036148071,
0.05625450983643532,
0.07605006545782089,
0.23867930471897125,
0.10401605814695358,
0.10196955502033234,
-0.06798075139522552,
0.10180158913135529,
-0.12330973148345947,
-0.08915644884109497,
-0.17508824169635773,
0.11820860952138901,
0.00015364694991149008,
0.1317785084247589,
-0.12023144960403442,
0.07898581773042679,
-0.067511186003685,
0.013453764840960503,
0.01636839471757412,
0.0820009782910347,
-0.012399360537528992,
0.10676060616970062,
-0.005061192903667688,
-0.06941985338926315,
0.014177112840116024,
0.05935845896601677,
0.03754841163754463,
-0.038601722568273544,
-0.03192409873008728,
-0.05762290954589844,
-0.05065649375319481,
-0.10128600150346756,
-0.06447898596525192,
0.018573462963104248,
-0.007677143905311823,
-0.1833900660276413,
-0.06407523155212402,
0.00897200871258974,
0.015712225809693336,
-0.03988850116729736,
-0.05148044601082802,
-0.15265507996082306,
-0.042461175471544266,
-0.015450406819581985,
-0.03500641882419586,
-0.06214277446269989,
-0.0383245050907135,
0.046435944736003876,
-0.07560601085424423,
0.013364278711378574,
0.023342855274677277,
0.05405820533633232,
-0.025881100445985794,
0.06068144738674164,
-0.08357544988393784,
0.09493788331747055,
-0.1540430635213852,
-0.03271956741809845,
-0.025445878505706787,
-0.041183918714523315,
0.1752462536096573,
0.06099751964211464,
-0.015994304791092873,
0.15260063111782074,
-0.17141541838645935,
-0.058121129870414734,
0.15596486628055573,
0.008629098534584045,
-0.09967197477817535,
-0.003560945624485612,
-0.09397093951702118,
0.1428760588169098,
0.08571921288967133,
0.2478504776954651,
0.12005335837602615,
-0.22748184204101562,
0.055358242243528366,
0.12515293061733246,
-0.14365963637828827,
0.10365243256092072,
0.07344598323106766,
0.005470725707709789,
-0.18886831402778625,
-0.06843198090791702,
-0.06121627986431122,
0.1053021252155304,
-0.08522345870733261,
-0.0776243582367897,
0.09323626756668091,
-0.05086790770292282,
0.24641476571559906,
-0.028281206265091896,
0.06174173951148987,
-0.026681531220674515,
-0.1389324963092804,
-0.01723906397819519,
0.060955192893743515,
0.05258452147245407,
-0.024835573509335518,
-0.25895482301712036,
0.13646544516086578,
0.048650871962308884,
0.025074828416109085,
0.004106190986931324,
-0.05691491439938545,
0.016934165731072426,
0.1511998474597931,
0.020012924447655678,
0.13717477023601532,
0.027723990380764008,
0.0706823319196701,
-0.006239562761038542,
-0.10560829937458038,
-0.04169593006372452,
0.061916545033454895,
-0.08518962562084198,
-0.06641357392072678,
0.011197872459888458,
-0.06935211271047592,
-0.11783787608146667,
-0.12166737765073776,
-0.026334572583436966,
-0.02980303019285202,
-0.07444227486848831,
0.02368103712797165,
0.06536602973937988,
-0.06702698022127151,
-0.0023908785078674555,
0.007125476840883493,
-0.011537045240402222,
0.16434046626091003,
0.011393417604267597,
-0.007796820718795061,
0.1328643560409546,
-0.11533161997795105,
0.12461213022470474,
0.049438029527664185,
-0.024806302040815353,
-0.04662557691335678,
0.0014137453399598598,
-0.057529181241989136,
0.029044216498732567,
-0.04390640929341316,
0.02774495631456375,
0.20111067593097687,
0.02772962674498558,
0.11389166116714478,
-0.0656520202755928,
0.04385066404938698,
-0.007961965166032314,
-0.009693224914371967,
0.018563594669103622,
0.07608018070459366,
0.07813210040330887,
-0.1324140727519989,
0.02262016013264656,
0.22455167770385742,
0.1385764330625534,
0.18313980102539062,
-0.010877152904868126,
0.06325667351484299,
-0.04875868931412697,
0.027505528181791306,
0.024100203067064285,
0.10314226150512695,
-0.10732068121433258,
-0.0322517491877079,
-0.025407759472727776,
0.023599207401275635,
-0.08197105675935745,
-0.1055799350142479,
-0.090115025639534,
0.01222382951527834,
-0.03125503659248352,
-0.15570329129695892,
0.13300658762454987,
-0.10451057553291321,
0.01802753657102585,
0.04692702740430832,
-0.22163605690002441,
0.11530312895774841,
0.014291439205408096,
-0.10303618758916855,
0.11281087249517441,
-0.12051989883184433,
-0.08699832111597061,
-0.05777236074209213,
-0.18658851087093353,
0.05280197039246559,
0.04673841595649719,
0.05166793242096901,
-0.18521739542484283,
0.024835903197526932,
0.05545609071850777,
0.13426995277404785,
-0.09743253141641617,
-0.07142634689807892,
-0.15038461983203888,
0.016068490222096443,
-0.033661190420389175,
-0.16029728949069977,
-0.005609163548797369,
-0.032781440764665604,
-0.18849676847457886,
-0.04539939761161804,
-0.15086813271045685,
-0.034627582877874374,
0.20464378595352173,
0.026907702907919884,
0.09480511397123337,
-0.07926445454359055,
0.3802889585494995,
-0.042039383202791214,
-0.06146497279405594,
-0.01321389526128769,
-0.07072482258081436,
0.02512686513364315,
0.13271741569042206,
0.0036099457647651434,
-0.017886579036712646,
-0.0037857077550143003,
0.0024592927657067776,
-0.06234965845942497,
-0.13400450348854065,
0.0028710351325571537,
0.03905198723077774,
0.1874423623085022,
0.004639793653041124,
0.06659388542175293,
0.03133883699774742,
0.057546284049749374,
0.07748064398765564,
0.030926106497645378,
0.0011591583024710417,
-0.01591806672513485,
0.06604493409395218,
-0.11684755235910416,
0.042466625571250916,
-0.030429253354668617,
-0.10143838077783585,
-0.013183288276195526,
0.07950251549482346,
0.12755028903484344,
0.17849206924438477,
-0.04790908098220825,
0.17489230632781982,
0.13580141961574554,
0.16576050221920013,
0.049315933138132095,
-0.020801831036806107,
-0.08773037046194077,
-0.06118565797805786,
0.004774159751832485,
-0.031952597200870514,
0.04869702458381653,
0.3231290578842163,
0.037619613111019135,
-0.09036035090684891,
0.11149907857179642,
0.009480619803071022,
0.05359881371259689,
0.022797370329499245,
-0.11162138730287552,
0.11170321702957153,
0.07968773692846298,
-0.06341761350631714,
-0.07602835446596146,
0.16758501529693604,
-0.1109386757016182,
-0.26646625995635986,
-0.11410990357398987,
-0.012305386364459991,
0.07903840392827988,
0.005651174578815699,
0.05498376116156578,
-0.11829282343387604,
-0.16034497320652008,
-0.034191906452178955,
0.1335442066192627,
-0.3077351450920105,
0.2065143585205078,
-0.0198091771453619,
0.06707923114299774,
-0.039657969027757645,
-0.07026876509189606,
0.09694647043943405,
0.13174086809158325,
0.29124146699905396,
0.01396956667304039,
0.04841272905468941,
-0.15176129341125488,
-0.0976925864815712,
0.0018439020495861769,
0.015482662245631218,
-0.02563396655023098,
0.028520405292510986,
-0.0540912002325058,
0.008404579944908619,
-0.018086453899741173,
0.2102297693490982,
-0.11316607892513275,
0.004344627261161804,
-0.06968966871500015,
-0.11707738786935806,
0.19409789144992828,
-0.07178345322608948,
-0.04543264955282211,
-0.14959357678890228,
-0.15512511134147644,
-0.004174166824668646,
-0.02413962036371231,
-0.019664527848362923,
-0.17603960633277893,
-0.18804074823856354,
-0.05204557999968529,
-0.005645004566758871,
-0.003464865731075406,
0.05867868289351463,
-0.07517234236001968,
-0.04805335775017738,
0.1009904220700264,
-0.07743175327777863,
-0.056063808500766754,
-0.1103200614452362,
0.1391381323337555,
0.06248528137803078,
0.16743235290050507,
0.05907081440091133,
0.0006117874872870743,
0.11471151560544968,
-0.02913086675107479,
0.11103474348783493,
-0.11291708797216415,
-0.17145049571990967,
-0.08334989100694656,
-0.018775060772895813,
0.09519003331661224,
-0.04789286106824875,
0.0028788831550627947,
0.2550160884857178,
0.14880181849002838,
-0.0897710770368576,
0.27680760622024536,
0.04414956644177437,
-0.09375058114528656,
-0.18432219326496124,
-0.15961645543575287,
0.03759992495179176,
0.060025621205568314,
0.13095876574516296,
-0.057205069810152054,
-0.08483537286520004,
-0.08492398262023926,
-0.07478608191013336,
-0.13140805065631866,
-0.24232175946235657,
-0.030598774552345276,
0.22874866425991058,
0.08656918257474899,
0.08219650387763977,
-0.012482990510761738,
-0.01186054851859808,
0.00526038184762001,
0.02680150233209133,
0.12018456310033798,
-0.13341329991817474,
0.11107480525970459,
0.022198403254151344,
0.044267985969781876,
0.009712530300021172,
0.07929777354001999,
0.03375575691461563,
-0.003218587953597307,
-0.0006439819699153304,
-0.0988350659608841,
-0.2596651017665863,
0.0816885456442833,
-0.01623627357184887,
-0.09960969537496567,
0.014988959766924381,
0.02061903104186058,
-0.2089255303144455,
0.011128270998597145,
-0.019883770495653152,
-0.03150356933474541,
-0.06483490765094757,
-0.10664787143468857,
-0.056551624089479446,
0.04928823933005333,
0.10853826254606247,
0.011660109274089336,
0.05354316532611847,
-0.0404130220413208,
0.07917837053537369,
0.0826287642121315,
0.15132710337638855,
0.06795957684516907,
-0.190711110830307,
-0.10953907668590546,
-0.0414445661008358,
0.12121522426605225,
-0.12505418062210083,
0.036917757242918015,
0.053161121904850006,
-0.016534561291337013,
0.14621229469776154,
0.1070784479379654,
-0.07452095299959183,
0.11915595084428787,
0.08904775977134705,
-0.04094788804650307,
-0.23367151618003845,
-0.07120766490697861,
0.11133213341236115,
0.07195597887039185,
-0.03961895406246185,
0.018120890483260155,
-0.04960581287741661,
-0.013980977237224579,
0.048759616911411285,
-0.0538676381111145,
-0.07230538129806519,
0.004421027842909098,
0.1247575581073761,
0.1029362753033638,
-0.04655474051833153,
0.01296416949480772,
0.037371400743722916,
0.003788623260334134,
0.04730486497282982,
0.0407949760556221,
-0.08269952982664108,
-0.04124005511403084,
0.02782733179628849,
0.37552911043167114,
-0.010165480896830559,
-0.020456433296203613,
0.018555615097284317,
-0.19949445128440857,
0.09135842323303223,
0.13205479085445404,
0.04697350412607193,
0.004247748292982578,
-0.08139242231845856,
0.026877427473664284,
-0.010625290684401989,
0.09936143457889557,
-0.07806670665740967,
-0.05493134260177612,
-0.21631066501140594,
-0.025010565295815468,
0.017490221187472343,
0.24077683687210083,
-0.08458559215068817,
-0.12801732122898102,
-0.20628872513771057,
0.13128381967544556,
-0.11333390325307846,
-0.03695881739258766,
-0.024473199620842934,
0.03926658630371094,
-0.01989821158349514,
0.06291737407445908,
-0.0710630789399147,
0.006373001262545586,
-0.11024709790945053,
0.055267609655857086,
0.04204455390572548,
0.1229788213968277,
0.014207782223820686,
0.02016810141503811,
0.05822525918483734,
-0.01837925612926483,
0.07173580676317215,
-0.06203491613268852,
-0.04550490900874138,
0.14224006235599518,
-0.020255116745829582,
-0.04152837023139,
-0.0483345128595829,
-0.036874305456876755,
0.11981741338968277,
-0.05059147998690605,
-0.007141099311411381,
-0.054929375648498535,
-0.06906463205814362,
0.03462086617946625,
-0.009175732731819153,
-0.008798843249678612,
0.06801853328943253,
0.04024988040328026,
-0.026994358748197556,
0.005263668950647116,
0.03447828069329262,
-0.10330043733119965,
-0.04955084249377251,
0.16955432295799255,
-0.0749620869755745,
0.10274054110050201,
-0.031069839373230934,
0.018015999346971512,
0.005847334861755371,
-0.022399673238396645,
-0.015360680408775806,
-0.1457086056470871,
-0.06137600541114807,
-0.09489979594945908,
0.11565322428941727,
0.08146517723798752,
0.03358805552124977,
0.04274565726518631,
0.019532648846507072,
-0.04414922371506691,
-0.038583990186452866,
0.12961317598819733,
0.08133101463317871,
0.012996876612305641,
0.01137041300535202,
0.01941833831369877,
-0.020302120596170425,
0.0028480992186814547,
-0.01250747125595808,
-0.07239153981208801,
-0.05874783173203468,
0.09400010108947754,
0.1600283533334732,
-0.06127211079001427,
-0.13325586915016174,
-0.020593497902154922,
0.04988488554954529,
0.0014717020094394684,
-0.08777432143688202,
0.04833676666021347,
0.15805292129516602,
-0.05623878911137581,
0.03216489031910896,
-0.09984751045703888,
-0.07263360917568207,
-0.16060975193977356,
-0.10029061883687973,
-0.06092562898993492,
-0.28350353240966797,
0.09752398729324341,
0.006392303854227066,
-0.014731393195688725,
0.059529416263103485,
0.051305368542671204,
-0.052508849650621414,
0.07068239152431488,
-0.18146829307079315,
-0.007054794579744339,
0.03497592359781265,
-0.13212306797504425,
0.02475893869996071,
-0.2378365397453308,
0.10198072344064713,
-0.04623803123831749,
-0.1519704908132553,
-0.04004510119557381,
0.0641569048166275,
-0.09540136158466339,
-0.01822364516556263,
-0.0475153923034668,
-0.01922670193016529,
0.01624443754553795,
-0.009348669089376926,
-0.031147832050919533,
0.13716529309749603,
0.02827494591474533,
-0.03268734738230705,
0.005254602525383234,
0.0223685409873724,
0.03955082967877388,
-0.0969657450914383,
-0.05986930429935455,
0.08311155438423157,
-0.031056145206093788,
0.14728976786136627,
0.000341245875461027,
0.04181376099586487,
-0.06758682429790497,
0.2593761384487152,
0.2023983597755432,
-0.12479214370250702,
0.008118697442114353,
-0.021801479160785675,
0.012670028023421764,
-0.041751839220523834,
0.13110700249671936,
0.013386172242462635,
0.12186761200428009,
-0.17513342201709747,
-0.01036517322063446,
-0.0818324014544487,
-0.04501292482018471,
0.06702108681201935,
0.14714950323104858,
0.15742522478103638,
0.03436789661645889,
-0.07328428328037262,
0.06722653657197952,
-0.30119743943214417,
0.20540550351142883,
-0.1346001923084259,
-0.01498429011553526,
-0.040251150727272034,
-0.058389630168676376,
0.061147745698690414,
0.11309876292943954,
0.10832664370536804,
-0.021150551736354828,
-0.0905047357082367,
-0.04486766457557678,
-0.039378076791763306,
-0.13019338250160217,
-0.02718670479953289,
0.1654091775417328,
0.06799814850091934,
0.31520840525627136,
-0.017577875405550003,
0.07702425122261047,
0.034410297870635986,
0.06451138854026794,
0.004519328009337187,
0.09537279605865479,
0.07960964739322662,
-0.06345855444669724,
-0.07373003661632538,
-0.001637450186535716,
0.05033271387219429,
0.14567798376083374,
-0.03826142102479935,
-0.18691548705101013,
0.15858715772628784,
0.07192251086235046,
-0.13762691617012024,
-0.05777517706155777,
0.08409425616264343,
-0.0739973932504654,
0.0550808347761631,
0.08115427941083908,
0.015876613557338715,
-0.017793258652091026,
-0.004664506763219833,
0.06074233725667,
0.024694660678505898,
-0.02343848906457424,
0.003570882137864828,
-0.08337053656578064,
-0.04151543974876404,
0.07267895340919495,
-0.0844460055232048,
-0.20546193420886993,
-0.0957019031047821,
-0.07551700621843338,
0.030557552352547646,
-0.0649830624461174,
0.12575586140155792,
0.1717868149280548,
0.0593598335981369,
-0.03307248651981354,
-0.10721943527460098,
-0.035562749952077866,
0.07602505385875702,
-0.044773899018764496,
-0.09409699589014053
] |
null | null | ml-agents |
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
- A *longer tutorial* to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
### Resume the training
```bash
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser**
1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: RichardKhanhWin/ppo-Huggy
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
| {"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]} | reinforcement-learning | RichardKhanhWin/ppo-Huggy | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | 2024-02-11T06:09:40+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your
browser: URL
- A *longer tutorial* to understand how works ML-Agents:
URL
### Resume the training
### Watch your Agent play
You can watch your agent playing directly in your browser
1. If the environment is part of ML-Agents official environments, go to URL
2. Step 1: Find your model_id: RichardKhanhWin/ppo-Huggy
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play
| [
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: RichardKhanhWin/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
"TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n",
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: RichardKhanhWin/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
44,
200
] | [
"passage: TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: RichardKhanhWin/ppo-Huggy\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
0.025733420625329018,
0.021333634853363037,
-0.003973815124481916,
0.04316367581486702,
0.1199476420879364,
-0.0038001369684934616,
0.15543334186077118,
0.13525047898292542,
0.12295986711978912,
0.07169493287801743,
0.07810307294130325,
0.058144036680459976,
0.04851309210062027,
0.19000281393527985,
0.07952871173620224,
-0.2340133786201477,
-0.01278888713568449,
-0.08505292236804962,
0.032701022922992706,
0.08148334920406342,
0.05435270443558693,
-0.039607830345630646,
0.08036685734987259,
0.02854309044778347,
-0.03345512971282005,
-0.009100791066884995,
-0.07444580644369125,
-0.02710183896124363,
0.05241271108388901,
0.006186670158058405,
-0.028674187138676643,
-0.025903236120939255,
0.05974176526069641,
-0.2131882756948471,
0.03234260529279709,
0.061048723757267,
-0.002665345324203372,
0.012547854334115982,
0.09393388777971268,
0.03655131533741951,
0.1247326210141182,
-0.07044683396816254,
0.06501256674528122,
0.05785784125328064,
-0.07260672748088837,
-0.01689283922314644,
-0.1219625174999237,
0.05151185393333435,
0.2115183025598526,
0.09084965288639069,
0.003725079819560051,
0.11233946681022644,
-0.09156273305416107,
0.03753633424639702,
0.2165573388338089,
-0.23125049471855164,
-0.06776896864175797,
0.10096478462219238,
0.07715421169996262,
-0.022034263238310814,
-0.04818535968661308,
0.04713129252195358,
-0.02023865282535553,
0.035432446748018265,
0.06958812475204468,
-0.039898309856653214,
0.21822383999824524,
-0.005922187585383654,
-0.06982602924108505,
-0.06759484857320786,
0.0548325777053833,
0.06518988311290741,
-0.06220497936010361,
-0.21708440780639648,
0.03765614703297615,
0.13305427134037018,
-0.015817638486623764,
0.020976174622774124,
0.07146421819925308,
-0.027203399688005447,
-0.06239119544625282,
-0.10645480453968048,
-0.044959310442209244,
-0.057894524186849594,
0.08224042505025864,
0.16141055524349213,
-0.004271843004971743,
-0.028031716123223305,
0.07151693105697632,
0.07787639647722244,
-0.0016769531648606062,
-0.03655870258808136,
-0.030886048451066017,
-0.039058785885572433,
-0.10615776479244232,
0.004619433078914881,
-0.00891048926860094,
0.09265030920505524,
0.056489307433366776,
0.12952929735183716,
0.029819076880812645,
0.02055797353386879,
0.027300411835312843,
0.050632137805223465,
-0.0085820984095335,
0.12240128219127655,
0.021138932555913925,
0.020781980827450752,
0.03581038489937782,
0.05904480442404747,
0.06290821731090546,
-0.053250886499881744,
-0.09682552516460419,
0.08152379840612411,
-0.11962752044200897,
0.09301916509866714,
0.08805613219738007,
0.025417255237698555,
-0.07365488260984421,
-0.030493533238768578,
0.01678086631000042,
-0.13255688548088074,
0.07926411181688309,
0.04631872475147247,
-0.04821383208036423,
-0.1001746729016304,
-0.006643571890890598,
0.010261837393045425,
-0.06733962893486023,
0.030243676155805588,
-0.01960553228855133,
0.04141436517238617,
-0.013237224891781807,
-0.03784706071019173,
0.09044186770915985,
-0.07257428020238876,
-0.02102847956120968,
-0.1512608826160431,
-0.10396066308021545,
-0.05471425876021385,
0.058406583964824677,
-0.049201108515262604,
-0.1291227638721466,
-0.048755619674921036,
0.012853102758526802,
-0.09441851079463959,
-0.004980736877769232,
-0.02610873617231846,
-0.05671069025993347,
-0.009440070949494839,
-0.03060164675116539,
0.07669705897569656,
0.15971097350120544,
0.035625796765089035,
-0.014828809536993504,
0.07834188640117645,
-0.21086061000823975,
0.11194295436143875,
-0.10819174349308014,
0.16761361062526703,
-0.05766453593969345,
0.010496435686945915,
0.031243201345205307,
0.024355098605155945,
0.009244969114661217,
0.163129523396492,
-0.058154184371232986,
-0.11552511155605316,
0.1309106945991516,
-0.03376435115933418,
-0.11679578572511673,
0.058607228100299835,
0.02141554467380047,
0.0699673742055893,
0.037038058042526245,
0.24421235918998718,
0.10027176141738892,
-0.2743879556655884,
0.05793220177292824,
0.040808744728565216,
-0.13188351690769196,
0.03255133330821991,
0.1412094682455063,
-0.06403618305921555,
-0.008497915230691433,
-0.0037824742030352354,
-0.1679428517818451,
0.06788083910942078,
-0.006175389513373375,
-0.029865138232707977,
0.04539313539862633,
-0.038540419191122055,
0.002465842990204692,
-0.02106320485472679,
-0.002041213447228074,
-0.06028230860829353,
-0.10298026353120804,
-0.07706388086080551,
0.09320078045129776,
-0.013429766520857811,
0.07502365112304688,
-0.06738406419754028,
0.1080537810921669,
0.04382508248090744,
0.04657543823122978,
-0.09406808018684387,
-0.10411962121725082,
0.014452665112912655,
0.023644186556339264,
0.10174135118722916,
-0.0757378414273262,
0.051598336547613144,
0.0704590380191803,
-0.0029350549448281527,
-0.07420488446950912,
-0.09031153470277786,
-0.01490004826337099,
-0.06457089632749557,
-0.11970538645982742,
-0.06470918655395508,
-0.06943275034427643,
0.11359471827745438,
-0.09230725467205048,
0.05647958442568779,
-0.1130867749452591,
0.04163309186697006,
-0.012129707261919975,
-0.0265410915017128,
0.051956020295619965,
0.0050249407067894936,
0.02688772603869438,
-0.06508530676364899,
0.10345400124788284,
0.028810467571020126,
-0.09860501438379288,
0.08418172597885132,
-0.047117698937654495,
-0.08107063174247742,
0.0992647185921669,
0.04589195176959038,
-0.016458196565508842,
-0.033768828958272934,
-0.08096985518932343,
0.009243977256119251,
-0.08840612322092056,
-0.004606577567756176,
0.18247981369495392,
0.10079371184110641,
0.11227454990148544,
-0.07390600442886353,
-0.06901340186595917,
-0.029491594061255455,
-0.10496878623962402,
-0.057715050876140594,
0.1521213799715042,
0.01949283294379711,
0.07892012596130371,
0.039873458445072174,
0.0584024079144001,
0.0734701007604599,
0.08980904519557953,
0.015765707939863205,
-0.1096453070640564,
-0.018035080283880234,
0.06211978569626808,
0.04477650672197342,
0.008245682343840599,
0.026924293488264084,
-0.010961285792291164,
0.022913744673132896,
-0.03759966418147087,
-0.014519198797643185,
-0.14002282917499542,
-0.07366006076335907,
0.005816054064780474,
-0.039632074534893036,
0.028336692601442337,
-0.00888504646718502,
-0.04158932715654373,
0.05506547540426254,
0.09867674112319946,
0.027040818706154823,
0.0033571633975952864,
-0.049388136714696884,
-0.10976632684469223,
0.07278352975845337,
-0.07936741411685944,
-0.29946303367614746,
-0.11493951827287674,
-0.1366635411977768,
-0.06702372431755066,
0.028590209782123566,
0.060636233538389206,
-0.1698581725358963,
-0.027315786108374596,
-0.11520496755838394,
-0.04402514547109604,
0.03951173275709152,
-0.07386104762554169,
0.18516749143600464,
0.09399866312742233,
0.01643821783363819,
-0.08131545782089233,
-0.02801579050719738,
0.00976218655705452,
-0.03627026826143265,
0.040604040026664734,
0.027392294257879257,
0.047127775847911835,
0.11490190774202347,
0.07209669798612595,
0.04844709858298302,
-0.035679932683706284,
0.06845249235630035,
-0.06345837563276291,
-0.0161224827170372,
0.12780888378620148,
-0.027852673083543777,
0.08428994566202164,
0.037680406123399734,
0.02232346311211586,
-0.030024753883481026,
0.054690081626176834,
0.008646871894598007,
-0.07138856500387192,
-0.19142119586467743,
-0.08863311260938644,
-0.0285321231931448,
0.23176437616348267,
0.09437788277864456,
0.08588887006044388,
-0.05433256924152374,
-0.03909415379166603,
0.008016981184482574,
-0.04537273570895195,
0.15181981027126312,
0.12130275368690491,
-0.03287617489695549,
-0.07652626931667328,
-0.0005050022155046463,
-0.04392046108841896,
0.023969626054167747,
0.0925997793674469,
-0.007057332433760166,
0.07279685884714127,
0.02927403338253498,
0.021249672397971153,
0.03560377657413483,
-0.05892140045762062,
-0.06004251539707184,
0.06315650790929794,
0.03025716356933117,
-0.0037472646217793226,
-0.039531923830509186,
-0.08370703458786011,
-0.032758500427007675,
0.10385735332965851,
0.1350012570619583,
-0.0660465657711029,
-0.09009196609258652,
0.07926333695650101,
0.09506747126579285,
0.0946369394659996,
0.03034158982336521,
-0.1353427916765213,
-0.04926736652851105,
0.018725940957665443,
-0.12091951817274094,
0.03376682475209236,
-0.001432068762369454,
0.019395040348172188,
-0.19991697371006012,
0.08579358458518982,
0.0210807453840971,
0.12008020281791687,
0.0545169860124588,
0.0058835893869400024,
0.01781885139644146,
0.09324239194393158,
-0.020143942907452583,
0.0634998306632042,
-0.17743298411369324,
0.06621519476175308,
-0.014017538167536259,
0.07117410749197006,
-0.049463674426078796,
0.0014850774314254522,
0.10389924049377441,
-0.03234180063009262,
0.1785365790128708,
0.036820512264966965,
0.045622460544109344,
-0.05301352217793465,
-0.175933375954628,
-0.042832281440496445,
-0.00018529515364207327,
-0.09941008687019348,
0.07271180301904678,
-0.006442503072321415,
-0.043951764702796936,
-0.09535805881023407,
0.1357066035270691,
0.006845187861472368,
-0.058016009628772736,
-0.003927986137568951,
-0.06214369460940361,
0.02341841533780098,
-0.06297235935926437,
-0.033900752663612366,
-0.030832767486572266,
0.21541568636894226,
0.1452043354511261,
-0.01951528713107109,
-0.09118309617042542,
-0.03423473611474037,
-0.032331790775060654,
-0.026551760733127594,
-0.022761454805731773,
-0.010209244675934315,
0.13589181005954742,
-0.08459849655628204,
-0.03481972962617874,
-0.007406492251902819,
-0.10183623433113098,
-0.11976373940706253,
-0.01084864977747202,
0.24573169648647308,
-0.0006768453749828041,
0.10130724310874939,
-0.026112757623195648,
0.02060229703783989,
-0.0008088198956102133,
-0.08235237002372742,
0.1494329422712326,
0.17427627742290497,
0.0018020226852968335,
0.06657672673463821,
-0.09455393999814987,
0.06096496060490608,
-0.11986919492483139,
-0.030011838302016258,
0.1999671310186386,
0.3149183690547943,
-0.02823680266737938,
0.2223295122385025,
0.06271440535783768,
-0.0569915734231472,
-0.2191273421049118,
-0.07519382983446121,
0.03772857412695885,
-0.013991348445415497,
0.13906297087669373,
-0.1476803570985794,
0.04135987162590027,
0.01420822273939848,
-0.010852683335542679,
0.02011905424296856,
-0.13186168670654297,
-0.09894497692584991,
-0.005074641201645136,
0.05917815864086151,
0.030258221551775932,
-0.08996857702732086,
-0.05093969777226448,
-0.032097022980451584,
-0.09281415492296219,
0.058900054544210434,
-0.1452881246805191,
0.0862775444984436,
0.0014054705388844013,
0.04311661049723625,
0.038519710302352905,
-0.025349466130137444,
0.12853482365608215,
-0.06496487557888031,
-0.030072633177042007,
-0.08461706340312958,
-0.022222915664315224,
0.009589345194399357,
-0.12289868295192719,
0.08014187961816788,
-0.06241774559020996,
-0.051378559321165085,
-0.17963546514511108,
-0.04504572972655296,
-0.04587327316403389,
0.05177228897809982,
-0.016037965193390846,
-0.020319323986768723,
-0.00797982607036829,
0.07497451454401016,
0.07510506361722946,
0.043155305087566376,
0.06531863659620285,
-0.02535516396164894,
-0.00952385738492012,
0.0825844407081604,
0.10702455788850784,
0.03336184844374657,
-0.09815867245197296,
-0.033177006989717484,
-0.038139812648296356,
-0.025468410924077034,
-0.10648476332426071,
0.003164823865517974,
0.029089266434311867,
0.016168667003512383,
0.05846354365348816,
0.05742879584431648,
-0.10299216955900192,
-0.014397813938558102,
0.07435411214828491,
-0.09731294214725494,
-0.12179111689329147,
-0.04836166277527809,
-0.10183371603488922,
-0.04942549765110016,
-0.07428575307130814,
0.05186314508318901,
-0.02626553364098072,
-0.007132452912628651,
0.04415914788842201,
0.04057447984814644,
-0.07229724526405334,
0.02637498825788498,
-0.013159094378352165,
0.025211172178387642,
-0.06492298096418381,
0.15587840974330902,
-0.0005407339776866138,
-0.05186428502202034,
0.02840394712984562,
0.20606614649295807,
-0.061839208006858826,
-0.07158110290765762,
-0.05875181779265404,
0.07051827758550644,
0.15285639464855194,
-0.02824757993221283,
-0.03729111701250076,
-0.07494433224201202,
0.08216364681720734,
-0.10244075953960419,
0.00483263935893774,
-0.09887566417455673,
0.025055063888430595,
0.09380828589200974,
-0.10522802174091339,
0.10278458148241043,
0.01161496713757515,
-0.05495833978056908,
-0.11238578706979752,
0.07555874437093735,
0.05404840037226677,
0.17920352518558502,
-0.016385221853852272,
-0.047611307352781296,
-0.14063075184822083,
0.0044517372734844685,
-0.019461115822196007,
-0.01115244347602129,
-0.16897428035736084,
-0.013836982659995556,
-0.02169882506132126,
0.0517091229557991,
-0.008750135079026222,
0.04395054280757904,
-0.05739555507898331,
-0.07321124523878098,
-0.05672686547040939,
0.08325569331645966,
-0.041618186980485916,
-0.04063533619046211,
0.03429703414440155,
-0.08422937244176865,
0.09639684855937958,
0.07396847009658813,
-0.022960523143410683,
-0.04299996420741081,
-0.06344418972730637,
-0.04452342540025711,
0.01721569150686264,
-0.042090363800525665,
0.037702012807130814,
-0.19681471586227417,
0.005932434927672148,
-0.05280895531177521,
-0.08985528349876404,
0.007059979718178511,
0.11171562224626541,
-0.07495526224374771,
0.061733752489089966,
0.021220803260803223,
-0.13638392090797424,
-0.07872787117958069,
0.002184343058615923,
0.01818787306547165,
0.06838353723287582,
0.08268532902002335,
-0.07056889683008194,
0.17471155524253845,
-0.12261321395635605,
-0.0056534819304943085,
0.0032055124174803495,
0.01628914661705494,
0.018795179203152657,
-0.09613291174173355,
0.0347214937210083,
-0.018271928653120995,
0.1288125216960907,
0.08148808777332306,
-0.04496654495596886,
0.03195473924279213,
-0.0023236742708832026,
0.10345277190208435,
0.001881541800685227,
0.02608063444495201,
-0.026783393695950508,
0.0018928974168375134,
0.045966602861881256,
-0.007493424694985151,
0.07228410989046097,
-0.12080506235361099,
0.12088465690612793,
0.08145852386951447,
0.1363486796617508,
0.055156316608190536,
0.07682298868894577,
-0.10318848490715027,
-0.18276451528072357,
-0.038882169872522354,
0.007841268554329872,
0.03549304977059364,
-0.06021507829427719,
0.23064731061458588,
0.10456211119890213,
-0.21866026520729065,
0.06489384919404984,
-0.003956409636884928,
0.01898348517715931,
-0.09005732834339142,
-0.1279795616865158,
-0.003243268234655261,
-0.2164754867553711,
0.0781283751130104,
-0.061458975076675415,
0.018321700394153595,
-0.037601225078105927,
-0.021807393059134483,
0.004372040741145611,
0.06610507518053055,
-0.13963951170444489,
-0.05906547233462334,
0.08668392151594162,
-0.04468763992190361,
0.008589879609644413,
0.006997446995228529,
-0.012338469736278057,
-0.046015653759241104,
-0.08589524030685425,
0.05398142710328102,
0.061095308512449265,
0.0076592001132667065,
0.054002176970243454,
-0.05387915298342705,
-0.07034693658351898,
0.029444418847560883,
-0.006930068600922823,
0.026402568444609642,
0.1312142163515091,
0.0489056371152401,
-0.09863794595003128,
0.0010820279130712152,
0.21052441000938416,
-0.06224815547466278,
-0.01687958464026451,
-0.09357841312885284,
0.16090551018714905,
-0.022342044860124588,
-0.0681503638625145,
-0.04832081124186516,
-0.09392007440328598,
-0.08263323456048965,
0.24044331908226013,
0.14765426516532898,
-0.043523963540792465,
0.017206545919179916,
-0.04400790482759476,
0.02563566155731678,
0.014228126965463161,
0.11290999501943588,
0.0785684809088707,
0.13108476996421814,
-0.07299106568098068,
-0.020758487284183502,
-0.0074460674077272415,
-0.07079503685235977,
-0.16002507507801056,
-0.003503332147374749,
0.02639489434659481,
-0.042359866201877594,
-0.030952822417020798,
0.053445734083652496,
-0.11210884898900986,
-0.13596464693546295,
0.10694791376590729,
-0.09953480213880539,
-0.061888549476861954,
-0.014667556621134281,
0.005458098370581865,
0.03261170536279678,
0.13802073895931244,
0.054925285279750824,
0.027443598955869675,
0.10799311846494675,
-0.027953488752245903,
-0.07797211408615112,
0.02906724624335766,
0.08951563388109207,
-0.08259875327348709,
0.1858965903520584,
-0.04068180173635483,
0.039025310426950455,
0.05562499910593033,
0.01759679988026619,
-0.13877595961093903,
0.06978163868188858,
0.029152128845453262,
-0.16241702437400818,
0.0025082649663090706,
0.07469920068979263,
-0.06575414538383484,
-0.014265237376093864,
0.07258340716362,
-0.026740306988358498,
0.0010214115027338266,
0.1413828432559967,
-0.009952548891305923,
-0.056370217353105545,
0.07717382162809372,
-0.1686512678861618,
0.10287701338529587,
0.1514439880847931,
-0.06132619455456734,
-0.008058090694248676,
-0.04954231530427933,
0.03128664940595627,
0.03633448854088783,
0.04198303446173668,
-0.017247674986720085,
-0.1359398066997528,
0.01675042137503624,
0.0321817547082901,
0.02490190975368023,
-0.3067016303539276,
-0.12029547244310379,
-0.05294705927371979,
-0.03763272613286972,
-0.0366995744407177,
0.10578939318656921,
0.09837687760591507,
-0.002530965255573392,
-0.008193030022084713,
-0.1764528453350067,
0.04040927812457085,
0.16341336071491241,
-0.08844413608312607,
-0.014069078490138054
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Base Persian Iranian
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 fa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7142
- Wer: 58.5965
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 1.1086 | 1.02 | 500 | 1.2735 | 85.9444 |
| 0.8782 | 3.0 | 1000 | 1.0477 | 76.5527 |
| 0.6726 | 4.02 | 1500 | 0.9506 | 71.8807 |
| 0.7501 | 6.0 | 2000 | 0.8943 | 69.3890 |
| 0.6079 | 7.02 | 2500 | 0.8550 | 67.1322 |
| 0.6592 | 9.0 | 3000 | 0.8239 | 66.2762 |
| 0.5703 | 10.02 | 3500 | 0.8007 | 63.9907 |
| 0.5767 | 12.0 | 4000 | 0.7815 | 63.2562 |
| 0.5098 | 13.02 | 4500 | 0.7671 | 62.1094 |
| 0.5373 | 15.01 | 5000 | 0.7555 | 61.5551 |
| 0.4592 | 16.02 | 5500 | 0.7460 | 61.1086 |
| 0.5032 | 18.01 | 6000 | 0.7376 | 60.5652 |
| 0.4262 | 19.02 | 6500 | 0.7329 | 60.0792 |
| 0.4726 | 21.01 | 7000 | 0.7257 | 59.6696 |
| 0.4043 | 22.02 | 7500 | 0.7237 | 59.3570 |
| 0.4758 | 24.01 | 8000 | 0.7187 | 59.1098 |
| 0.412 | 25.02 | 8500 | 0.7173 | 58.8518 |
| 0.5119 | 27.01 | 9000 | 0.7146 | 58.7276 |
| 0.4089 | 28.03 | 9500 | 0.7145 | 58.6347 |
| 0.5186 | 30.01 | 10000 | 0.7142 | 58.5965 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
| {"language": ["fa"], "license": "apache-2.0", "tags": ["whisper-event", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_16_0"], "metrics": ["wer"], "base_model": "openai/whisper-base", "model-index": [{"name": "Whisper Base Persian Iranian", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_16_0 fa", "type": "mozilla-foundation/common_voice_16_0", "config": "fa", "split": "test", "args": "fa"}, "metrics": [{"type": "wer", "value": 58.59649122807018, "name": "Wer"}]}]}]} | automatic-speech-recognition | arun100/whisper-base-fa-1 | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"whisper-event",
"generated_from_trainer",
"fa",
"dataset:mozilla-foundation/common_voice_16_0",
"base_model:openai/whisper-base",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2024-02-11T06:13:38+00:00 | [] | [
"fa"
] | TAGS
#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #fa #dataset-mozilla-foundation/common_voice_16_0 #base_model-openai/whisper-base #license-apache-2.0 #model-index #endpoints_compatible #region-us
| Whisper Base Persian Iranian
============================
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common\_voice\_16\_0 fa dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7142
* Wer: 58.5965
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-07
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 10000
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.37.0.dev0
* Pytorch 2.1.2+cu121
* Datasets 2.16.2.dev0
* Tokenizers 0.15.0
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 500\n* training\\_steps: 10000\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.0.dev0\n* Pytorch 2.1.2+cu121\n* Datasets 2.16.2.dev0\n* Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #fa #dataset-mozilla-foundation/common_voice_16_0 #base_model-openai/whisper-base #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 500\n* training\\_steps: 10000\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.0.dev0\n* Pytorch 2.1.2+cu121\n* Datasets 2.16.2.dev0\n* Tokenizers 0.15.0"
] | [
99,
159,
4,
39
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #fa #dataset-mozilla-foundation/common_voice_16_0 #base_model-openai/whisper-base #license-apache-2.0 #model-index #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 500\n* training\\_steps: 10000\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.37.0.dev0\n* Pytorch 2.1.2+cu121\n* Datasets 2.16.2.dev0\n* Tokenizers 0.15.0"
] | [
-0.12733405828475952,
0.1521843671798706,
-0.0053396644070744514,
0.07308343797922134,
0.09896375983953476,
0.013318170793354511,
0.11105846613645554,
0.14626041054725647,
-0.04340410232543945,
0.1128867119550705,
0.08501697331666946,
0.07935093343257904,
0.07939770072698593,
0.14365552365779877,
-0.02246686816215515,
-0.27230194211006165,
0.010463844984769821,
-0.04687905311584473,
-0.10838796198368073,
0.0961715430021286,
0.08118566870689392,
-0.1072068139910698,
0.033476196229457855,
-0.01089737843722105,
-0.05390990525484085,
-0.019701732322573662,
-0.04041414335370064,
-0.04821346327662468,
0.09621161967515945,
0.02413443848490715,
0.041532132774591446,
0.031137146055698395,
0.10722403973340988,
-0.25125616788864136,
0.005470325704663992,
0.05811069533228874,
0.03529121354222298,
0.05496441200375557,
0.1028561219573021,
-0.009486440569162369,
0.07313472777605057,
-0.09607510268688202,
0.051995206624269485,
0.0473325252532959,
-0.09950684756040573,
-0.26723816990852356,
-0.06890708953142166,
0.02703273296356201,
0.1413879692554474,
0.06206965819001198,
-0.0227490421384573,
0.020477047190070152,
-0.03857048600912094,
0.09370550513267517,
0.20635773241519928,
-0.235573872923851,
-0.06893791258335114,
-0.02451443113386631,
0.029482142999768257,
0.05089515820145607,
-0.09953674674034119,
-0.007518584839999676,
0.009814908728003502,
0.016685910522937775,
0.09949235618114471,
0.005711248144507408,
0.032632067799568176,
-0.008834095671772957,
-0.131906658411026,
-0.04583938047289848,
0.10938657075166702,
0.06493986397981644,
-0.03273354098200798,
-0.10976866632699966,
-0.04001903906464577,
-0.14754505455493927,
-0.057351674884557724,
0.02640286646783352,
0.02991764061152935,
-0.03218815475702286,
-0.04073646664619446,
0.009502682834863663,
-0.03973829746246338,
-0.08523320406675339,
0.05497046560049057,
0.1386934071779251,
0.04003923386335373,
-0.023615039885044098,
0.02778126858174801,
0.08829828351736069,
0.05581530183553696,
-0.1731223613023758,
-0.01240962278097868,
0.030605996027588844,
-0.10080930590629578,
0.00007812843250576407,
-0.007394014857709408,
0.01776079647243023,
0.06277313828468323,
0.14028747379779816,
-0.005171219818294048,
0.08753981441259384,
0.026696322485804558,
0.0005904015270061791,
-0.0855981707572937,
0.151238813996315,
-0.05690455064177513,
-0.1211027130484581,
-0.021420007571578026,
0.13383783400058746,
0.02369084022939205,
-0.013029929250478745,
-0.06171848252415657,
0.02142895944416523,
0.07732690125703812,
0.07037468999624252,
0.00014479718811344355,
0.027872253209352493,
-0.06634450703859329,
-0.015088177286088467,
0.010938338935375214,
-0.12974703311920166,
0.03290426358580589,
0.05211670696735382,
-0.07327046245336533,
-0.04950295016169548,
-0.0020784002263098955,
0.005118913948535919,
-0.03319361433386803,
0.0717022642493248,
-0.04100238159298897,
-0.024582907557487488,
-0.06799846142530441,
-0.09005358070135117,
0.016307193785905838,
-0.03995773196220398,
0.0022175973281264305,
-0.046791501343250275,
-0.13729432225227356,
-0.06243756040930748,
0.05911184847354889,
-0.0707102045416832,
-0.05910637229681015,
-0.07722271978855133,
-0.08611419796943665,
0.041022177785634995,
-0.006550178397446871,
0.13795098662376404,
-0.05434678494930267,
0.08759146928787231,
0.017332255840301514,
0.06075851619243622,
0.10184048861265182,
0.05367987975478172,
-0.029834985733032227,
0.07460396736860275,
-0.15260683000087738,
0.10366138815879822,
-0.11415556073188782,
0.0704500749707222,
-0.14005441963672638,
-0.0873880684375763,
0.023140763863921165,
-0.009763319976627827,
0.10879319906234741,
0.14636971056461334,
-0.17632818222045898,
-0.05865355581045151,
0.1708112508058548,
-0.06704027205705643,
-0.09109272807836533,
0.12535810470581055,
-0.010718605481088161,
-0.05030578002333641,
0.026368673890829086,
0.18259300291538239,
0.12627959251403809,
-0.08674557507038116,
0.023920977488160133,
-0.025537770241498947,
0.12117469310760498,
0.04306286945939064,
0.09095240384340286,
-0.044249340891838074,
0.02756466343998909,
0.007382457610219717,
-0.05346189811825752,
0.04923158138990402,
-0.0797499567270279,
-0.08318907022476196,
-0.013694822788238525,
-0.0871884822845459,
0.005399285349994898,
0.03646900877356529,
-0.0031833299435675144,
-0.0836682841181755,
-0.11772657185792923,
-0.02553558722138405,
0.11278919130563736,
-0.0981096550822258,
0.0021747625432908535,
-0.07947647571563721,
0.07098305225372314,
-0.0020619677379727364,
0.0004759940493386239,
-0.1330198347568512,
-0.018709108233451843,
0.04646233096718788,
-0.06801655888557434,
-0.0032714218832552433,
-0.05845699459314346,
0.07982965558767319,
0.07092469185590744,
-0.02988995984196663,
-0.0722275897860527,
-0.026661138981580734,
-0.00475628487765789,
-0.062012165784835815,
-0.23488068580627441,
-0.07104436308145523,
-0.031153323128819466,
0.1517760455608368,
-0.20096109807491302,
0.015657711774110794,
0.022588757798075676,
0.1188584417104721,
0.02299240231513977,
-0.046044837683439255,
0.028934163972735405,
0.03631296008825302,
-0.006874615792185068,
-0.09041006118059158,
0.02767283096909523,
0.009095810353755951,
-0.10886915773153305,
0.007723105605691671,
-0.14279456436634064,
0.07841654121875763,
0.06966272741556168,
0.0363006666302681,
-0.06466103345155716,
-0.05233410745859146,
-0.0514189712703228,
-0.04971817880868912,
-0.009144922718405724,
-0.006333329249173403,
0.16103485226631165,
0.018223607912659645,
0.0998777225613594,
-0.07631158083677292,
-0.04694622755050659,
0.02817344292998314,
0.007795220706611872,
-0.0033342530950903893,
0.15516532957553864,
0.034504346549510956,
-0.05780993029475212,
0.08303787559270859,
0.0571390800178051,
-0.04285323619842529,
0.12565772235393524,
-0.08034859597682953,
-0.07747519016265869,
-0.0428033322095871,
0.04339504614472389,
0.02988043613731861,
0.11206487566232681,
-0.15042023360729218,
-0.009793438948690891,
0.028241192921996117,
0.004206701647490263,
0.004547625780105591,
-0.16554369032382965,
-0.0039534480310976505,
0.04050283879041672,
-0.09050626307725906,
0.002879044972360134,
-0.014352910220623016,
-0.012453963980078697,
0.08518699556589127,
-0.002449111547321081,
-0.07381041347980499,
-0.028423426672816277,
-0.04714900255203247,
-0.07710247486829758,
0.1760786473751068,
-0.1058596596121788,
-0.11869162321090698,
-0.10803631693124771,
-0.009223815985023975,
-0.013513389974832535,
-0.006780317518860102,
0.027842294424772263,
-0.08062811195850372,
-0.05120516195893288,
-0.0790766254067421,
0.01162207406014204,
-0.0012615836458280683,
0.03251275420188904,
0.044306185096502304,
0.00012109775707358494,
0.07814175635576248,
-0.09480921179056168,
0.009357624687254429,
-0.004710254725068808,
-0.026592109352350235,
0.0000473886429972481,
0.03396964073181152,
0.08926470577716827,
0.1407073438167572,
0.05122104287147522,
0.02957982011139393,
-0.008991340175271034,
0.20404356718063354,
-0.11528422683477402,
0.022673409432172775,
0.13244816660881042,
-0.005466049071401358,
0.05223827809095383,
0.16723862290382385,
0.03777344524860382,
-0.09750823676586151,
0.010431104339659214,
0.026592642068862915,
-0.02045108564198017,
-0.21852001547813416,
-0.03328743204474449,
-0.0563088096678257,
-0.0005810280563309789,
0.09713903069496155,
0.0372648648917675,
-0.03554049879312515,
0.025648754090070724,
-0.017885375767946243,
-0.02808222733438015,
0.04691582918167114,
0.05169658735394478,
0.055655866861343384,
0.03115895763039589,
0.10478852689266205,
-0.006261326372623444,
-0.024169977754354477,
0.02947899140417576,
-0.00530270067974925,
0.2254992127418518,
-0.023459024727344513,
0.19082313776016235,
0.03618261218070984,
0.12516726553440094,
-0.019650768488645554,
0.05024540051817894,
0.0023446977138519287,
0.008016342297196388,
0.015703389421105385,
-0.0563192255795002,
-0.02791108936071396,
0.024174710735678673,
0.0462479405105114,
0.034965142607688904,
-0.09543357789516449,
0.04672713205218315,
0.04107626900076866,
0.329863578081131,
0.07705751806497574,
-0.2791268229484558,
-0.07672015577554703,
0.021120604127645493,
-0.06553925573825836,
-0.04418773949146271,
0.024696435779333115,
0.1421225219964981,
-0.0630989670753479,
0.06993397325277328,
-0.056943628937006,
0.07786586135625839,
-0.07472231239080429,
0.009799142368137836,
0.08540361374616623,
0.10873375087976456,
0.0026641006115823984,
0.05105455964803696,
-0.23188544809818268,
0.26096659898757935,
-0.002855736529454589,
0.07788818329572678,
-0.04842685908079147,
0.04675406217575073,
0.02471446432173252,
-0.01480572298169136,
0.10946080833673477,
-0.006696613039821386,
-0.092461496591568,
-0.15382570028305054,
-0.11173001676797867,
0.016314160078763962,
0.1258886158466339,
-0.06408421695232391,
0.11338836699724197,
-0.03492448106408119,
-0.048331160098314285,
0.028921930119395256,
-0.08689218014478683,
-0.0896029844880104,
-0.09005501121282578,
0.030811911448836327,
-0.0031921942718327045,
0.03704565763473511,
-0.09150467813014984,
-0.07578286528587341,
-0.051340848207473755,
0.13717253506183624,
-0.10863158851861954,
-0.048935454338788986,
-0.1350213885307312,
0.046384647488594055,
0.16942965984344482,
-0.06767957657575607,
0.049957238137722015,
0.012694942764937878,
0.11677151173353195,
0.028491828590631485,
-0.014844491146504879,
0.09916695952415466,
-0.09286347031593323,
-0.21310804784297943,
-0.053989216685295105,
0.17522045969963074,
0.028698408976197243,
0.05519179627299309,
-0.014314278960227966,
0.018512221053242683,
0.0013307415647432208,
-0.08357865363359451,
0.06431709229946136,
0.037870313972234726,
0.0085745332762599,
0.03313598781824112,
-0.02503800392150879,
0.012822370044887066,
-0.0690184012055397,
-0.04090745747089386,
0.0888911560177803,
0.2742317020893097,
-0.08200126141309738,
0.04856138303875923,
0.043427105993032455,
-0.06453828513622284,
-0.16653963923454285,
-0.030552536249160767,
0.11241168528795242,
0.0410582609474659,
-0.003914501518011093,
-0.19081833958625793,
0.03404926508665085,
0.0609554685652256,
-0.02946092188358307,
0.08904479444026947,
-0.33806946873664856,
-0.13455110788345337,
0.08727579563856125,
0.08912264555692673,
-0.024614186957478523,
-0.1672971099615097,
-0.07275412976741791,
-0.011468280106782913,
-0.045751988887786865,
0.02684962749481201,
-0.03407522290945053,
0.11280457675457001,
0.00403340021148324,
0.010829339735209942,
0.03076498582959175,
-0.0522741936147213,
0.15491952002048492,
0.00021911341173108667,
0.0553603395819664,
-0.03108646534383297,
0.03428182378411293,
0.0015614896547049284,
-0.06772307306528091,
0.012748572044074535,
-0.10062619298696518,
0.04384447634220123,
-0.12279647588729858,
-0.025627557188272476,
-0.06777115166187286,
0.014589638449251652,
-0.0492313951253891,
-0.029929840937256813,
-0.00001919938404171262,
0.05273471027612686,
0.09519380331039429,
0.015498229302465916,
0.07375305145978928,
-0.04577815160155296,
0.09513337910175323,
0.15055494010448456,
0.10406894236803055,
0.03493361920118332,
-0.07071913033723831,
0.003467957256361842,
0.0034452467225492,
0.027130378410220146,
-0.12114604562520981,
0.046633198857307434,
0.1401529312133789,
0.03954191878437996,
0.1304841935634613,
0.038825105875730515,
-0.06864327937364578,
-0.011178146116435528,
0.055708177387714386,
-0.08840546011924744,
-0.16716469824314117,
-0.009623687714338303,
0.00536263408139348,
-0.1300458312034607,
-0.0032985799480229616,
0.11347276717424393,
-0.028357574716210365,
0.001403792412020266,
0.006630750373005867,
0.05923176184296608,
-0.01636037789285183,
0.23419597744941711,
0.026851065456867218,
0.09115784615278244,
-0.09704351425170898,
0.08564939349889755,
0.03933582454919815,
-0.0766473039984703,
0.038868118077516556,
0.1097659096121788,
-0.06227549910545349,
-0.022346090525388718,
0.03542173281311989,
0.08858074247837067,
0.06426168233156204,
-0.03196058049798012,
-0.12276197969913483,
-0.1440509706735611,
0.08240367472171783,
0.078199602663517,
0.02241363376379013,
0.01536211185157299,
-0.011943522840738297,
0.02760326862335205,
-0.07906736433506012,
0.13659165799617767,
0.09883677959442139,
0.05259409919381142,
-0.1194312572479248,
0.12043886631727219,
-0.009798465296626091,
0.004181568510830402,
-0.005101656541228294,
0.01958637498319149,
-0.10718740522861481,
0.010975624434649944,
-0.126338928937912,
0.01176338829100132,
-0.05006064847111702,
0.0020804181694984436,
-0.0010945238173007965,
-0.05767624080181122,
-0.04451794549822807,
0.025161808356642723,
-0.09469910711050034,
-0.054807934910058975,
-0.02734394557774067,
0.057535428553819656,
-0.0940280482172966,
-0.045525699853897095,
0.025440478697419167,
-0.1302843987941742,
0.10260900110006332,
0.03166496753692627,
0.020935187116265297,
0.006903321016579866,
-0.08953677117824554,
0.01843830570578575,
0.022259164601564407,
0.012660842388868332,
0.024377139285206795,
-0.1618185192346573,
-0.015391509979963303,
-0.04175438731908798,
-0.015481645241379738,
-0.021582819521427155,
0.030618419870734215,
-0.1181618869304657,
0.010423311032354832,
-0.03324480727314949,
-0.03452441468834877,
-0.04282621666789055,
0.04776761308312416,
0.07683250308036804,
0.0146559476852417,
0.13241249322891235,
-0.0792449340224266,
0.0669848620891571,
-0.22727160155773163,
0.000591350079048425,
-0.007039445452392101,
-0.06540034711360931,
-0.0627095028758049,
-0.01533583551645279,
0.10839516669511795,
-0.0637272298336029,
0.08286195248365402,
-0.030160069465637207,
0.04895658418536186,
0.018609346821904182,
-0.07900317758321762,
0.0421561524271965,
0.06434936076402664,
0.1531422734260559,
0.03111182153224945,
-0.02073979191482067,
0.06457937508821487,
-0.017320720478892326,
0.05916447564959526,
0.10215790569782257,
0.12453004717826843,
0.14985331892967224,
0.07845207303762436,
0.057767514139413834,
0.08625517785549164,
-0.13623358309268951,
-0.14384403824806213,
0.1279309242963791,
-0.051575709134340286,
0.13560181856155396,
-0.031872812658548355,
0.18353930115699768,
0.09428258240222931,
-0.1900610774755478,
0.06292043626308441,
-0.024228716269135475,
-0.09283190220594406,
-0.10489384084939957,
-0.09869834780693054,
-0.08127404004335403,
-0.13690482079982758,
0.0071067227981984615,
-0.10981874912977219,
0.058262329548597336,
0.03697248175740242,
0.03414193168282509,
0.0302121564745903,
0.10742703825235367,
0.0595785528421402,
0.016089020296931267,
0.10789070278406143,
0.023734034970402718,
-0.01679765060544014,
-0.005469354335218668,
-0.10985907912254333,
0.0354301854968071,
-0.011952144093811512,
0.04718079790472984,
-0.03398818522691727,
-0.08418891578912735,
0.0533054955303669,
0.010877656750380993,
-0.0976567417383194,
0.02558954618871212,
-0.025609588250517845,
0.04276872053742409,
0.09073702991008759,
0.04293404147028923,
-0.010920168831944466,
-0.010508532635867596,
0.22479930520057678,
-0.09147337824106216,
-0.06054642051458359,
-0.12179210036993027,
0.17392797768115997,
-0.013057544827461243,
0.004175539594143629,
0.029579341411590576,
-0.06686683744192123,
-0.01316245086491108,
0.14804500341415405,
0.15008825063705444,
-0.05099659785628319,
-0.012938576750457287,
0.009175866842269897,
-0.008047126233577728,
-0.02841012552380562,
0.07540067285299301,
0.11429540812969208,
0.04273567348718643,
-0.04637296497821808,
-0.01045621931552887,
-0.023807628080248833,
-0.06099773943424225,
-0.055921535938978195,
0.09044727683067322,
0.014242544770240784,
0.006793467327952385,
-0.012705142609775066,
0.10253363847732544,
-0.07563672959804535,
-0.15111953020095825,
0.03056025691330433,
-0.17612339556217194,
-0.19258655607700348,
-0.04819953814148903,
0.02957262471318245,
0.05923094227910042,
0.05242244154214859,
0.004774091299623251,
-0.022627387195825577,
0.11137717217206955,
-0.004095715470612049,
-0.03281557559967041,
-0.08817905932664871,
0.05983969569206238,
-0.12473538517951965,
0.20268665254116058,
-0.02692592702805996,
0.008351042866706848,
0.11582565307617188,
0.03313668817281723,
-0.10958892852067947,
0.03908726945519447,
0.09191680699586868,
-0.11697117984294891,
0.05813198909163475,
0.17575307190418243,
-0.04406771808862686,
0.1210823804140091,
0.037605538964271545,
-0.0752277746796608,
-0.0030075472313910723,
-0.032902780920267105,
-0.05597754567861557,
-0.06148745119571686,
-0.0038651323411613703,
-0.04713815450668335,
0.14112354815006256,
0.20600561797618866,
-0.07427428662776947,
-0.0031558454502373934,
-0.03605492785573006,
0.009839197620749474,
0.0240626223385334,
0.1178974136710167,
-0.026281066238880157,
-0.24967321753501892,
0.01685682311654091,
0.006581142079085112,
0.03562658652663231,
-0.182023286819458,
-0.0790441483259201,
0.012923466973006725,
-0.04490351676940918,
-0.07349338382482529,
0.11901722103357315,
0.07522016018629074,
0.03519389405846596,
-0.051076021045446396,
-0.08750156313180923,
-0.026879671961069107,
0.17429809272289276,
-0.1691342294216156,
-0.0565662644803524
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small Persian Iranian
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_16_0 fa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4858
- Wer: 39.7201
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4531 | 1.03 | 500 | 0.6448 | 50.7393 |
| 0.4031 | 3.0 | 1000 | 0.5755 | 46.5001 |
| 0.2745 | 4.04 | 1500 | 0.5389 | 43.7190 |
| 0.336 | 6.0 | 2000 | 0.5166 | 42.4056 |
| 0.2429 | 7.04 | 2500 | 0.5045 | 41.1810 |
| 0.2852 | 9.01 | 3000 | 0.4941 | 40.6444 |
| 0.2217 | 10.04 | 3500 | 0.4888 | 40.1106 |
| 0.2384 | 12.01 | 4000 | 0.4873 | 39.9208 |
| 0.1889 | 13.04 | 4500 | 0.4858 | 39.7201 |
| 0.2202 | 15.01 | 5000 | 0.4888 | 39.7228 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
| {"language": ["fa"], "license": "apache-2.0", "tags": ["whisper-event", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_16_0"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small Persian Iranian", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_16_0 fa", "type": "mozilla-foundation/common_voice_16_0", "config": "fa", "split": "test", "args": "fa"}, "metrics": [{"type": "wer", "value": 39.72011741415796, "name": "Wer"}]}]}]} | automatic-speech-recognition | arun100/whisper-small-fa-2 | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"whisper-event",
"generated_from_trainer",
"fa",
"dataset:mozilla-foundation/common_voice_16_0",
"base_model:openai/whisper-small",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2024-02-11T06:14:51+00:00 | [] | [
"fa"
] | TAGS
#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #fa #dataset-mozilla-foundation/common_voice_16_0 #base_model-openai/whisper-small #license-apache-2.0 #model-index #endpoints_compatible #region-us
| Whisper Small Persian Iranian
=============================
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common\_voice\_16\_0 fa dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4858
* Wer: 39.7201
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 1e-06
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 50
* training\_steps: 5000
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.38.0.dev0
* Pytorch 2.1.2+cu121
* Datasets 2.16.2.dev0
* Tokenizers 0.15.0
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 50\n* training\\_steps: 5000\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.2+cu121\n* Datasets 2.16.2.dev0\n* Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #fa #dataset-mozilla-foundation/common_voice_16_0 #base_model-openai/whisper-small #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 50\n* training\\_steps: 5000\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.2+cu121\n* Datasets 2.16.2.dev0\n* Tokenizers 0.15.0"
] | [
100,
158,
4,
41
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #fa #dataset-mozilla-foundation/common_voice_16_0 #base_model-openai/whisper-small #license-apache-2.0 #model-index #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: 50\n* training\\_steps: 5000\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.2+cu121\n* Datasets 2.16.2.dev0\n* Tokenizers 0.15.0"
] | [
-0.1323707401752472,
0.14140459895133972,
-0.005709775723516941,
0.07291052490472794,
0.09274545311927795,
0.012109658680856228,
0.10960625857114792,
0.14719010889530182,
-0.04512426257133484,
0.11618312448263168,
0.08369141817092896,
0.08368182927370071,
0.07752622663974762,
0.14163033664226532,
-0.023678738623857498,
-0.2739883363246918,
0.0036971678491681814,
-0.04091392457485199,
-0.10726317018270493,
0.09841463714838028,
0.08273231983184814,
-0.10535043478012085,
0.030796410515904427,
-0.0070540108717978,
-0.052047260105609894,
-0.018539492040872574,
-0.04062234237790108,
-0.0425385907292366,
0.09376559406518936,
0.029496584087610245,
0.039595331996679306,
0.03630087152123451,
0.10293278843164444,
-0.24214619398117065,
0.007193409837782383,
0.05691355839371681,
0.03419114276766777,
0.05543692037463188,
0.1107775941491127,
-0.011979139409959316,
0.09016670286655426,
-0.09544122219085693,
0.048946790397167206,
0.04775383323431015,
-0.09654221683740616,
-0.27917182445526123,
-0.06728145480155945,
0.03439101204276085,
0.13918857276439667,
0.06857618689537048,
-0.022746369242668152,
0.02464400790631771,
-0.053132861852645874,
0.09569210559129715,
0.21480700373649597,
-0.231857568025589,
-0.06617341935634613,
-0.023300617933273315,
0.026764096692204475,
0.05023125186562538,
-0.10005169361829758,
-0.013553022406995296,
0.008026206865906715,
0.017728185281157494,
0.09479362517595291,
0.0030125512275844812,
0.03503647446632385,
-0.007054541725665331,
-0.13276159763336182,
-0.04544635862112045,
0.10459049791097641,
0.06081518530845642,
-0.02934863232076168,
-0.11469456553459167,
-0.038708172738552094,
-0.14902061223983765,
-0.06123555824160576,
0.02863224223256111,
0.028680341318249702,
-0.033659838140010834,
-0.03532712161540985,
0.013212968595325947,
-0.04212668538093567,
-0.08252620697021484,
0.0570012629032135,
0.12566258013248444,
0.04478117451071739,
-0.02576771192252636,
0.02401336282491684,
0.08369571715593338,
0.05671673268079758,
-0.1705271452665329,
-0.015324131585657597,
0.03440478444099426,
-0.09853136539459229,
-0.0017056413926184177,
-0.0032806231174618006,
0.01762436330318451,
0.05847181752324104,
0.13426998257637024,
-0.016676323488354683,
0.09285928308963776,
0.02829088270664215,
0.006907111499458551,
-0.08388733118772507,
0.14555272459983826,
-0.0523519441485405,
-0.1126570999622345,
-0.021453384310007095,
0.13741813600063324,
0.021995700895786285,
-0.012145604938268661,
-0.0618276484310627,
0.02215450629591942,
0.07821658253669739,
0.07398848980665207,
0.0011862473329529166,
0.02642730064690113,
-0.05941876396536827,
-0.017037544399499893,
0.013730240054428577,
-0.1294286549091339,
0.03502442687749863,
0.059033267199993134,
-0.07626364380121231,
-0.04372105374932289,
-0.005433519370853901,
-0.0006309216842055321,
-0.041010428220033646,
0.07525445520877838,
-0.038193102926015854,
-0.019737517461180687,
-0.06601350754499435,
-0.08809391409158707,
0.01873227022588253,
-0.04326837882399559,
0.002294313395395875,
-0.04569340869784355,
-0.1392771154642105,
-0.06617799401283264,
0.05591535568237305,
-0.07219909131526947,
-0.061853259801864624,
-0.07487937062978745,
-0.08364995568990707,
0.04189001023769379,
-0.0076851858757436275,
0.1457347273826599,
-0.05577874556183815,
0.09020353108644485,
0.014121596701443195,
0.0575568713247776,
0.11199350655078888,
0.05618581920862198,
-0.033456213772296906,
0.07023296505212784,
-0.15519556403160095,
0.10251221060752869,
-0.1084502637386322,
0.06787324696779251,
-0.14200861752033234,
-0.09194337576627731,
0.016909820958971977,
-0.0031968734692782164,
0.10269192606210709,
0.14180926978588104,
-0.17903637886047363,
-0.06580500304698944,
0.16595926880836487,
-0.06860224157571793,
-0.08657123148441315,
0.12619921565055847,
-0.009652214124798775,
-0.046320315450429916,
0.022722765803337097,
0.18784916400909424,
0.1318667232990265,
-0.08006775379180908,
0.023578807711601257,
-0.022560758516192436,
0.12019608169794083,
0.033245593309402466,
0.09018083661794662,
-0.04443837329745293,
0.0319349579513073,
0.00454275868833065,
-0.05360187590122223,
0.0500606894493103,
-0.07674170285463333,
-0.08021761476993561,
-0.011562880128622055,
-0.08662241697311401,
-0.0004338599101174623,
0.04998098686337471,
0.002843719907104969,
-0.08173626661300659,
-0.12249823659658432,
-0.02587551437318325,
0.1139381006360054,
-0.09805478155612946,
0.0015804030699655414,
-0.07947546988725662,
0.07737906277179718,
0.001899720635265112,
0.0018300892552360892,
-0.1373906135559082,
-0.016701925545930862,
0.04048024117946625,
-0.07101179659366608,
-0.002185668796300888,
-0.04670308902859688,
0.08329704403877258,
0.06970749795436859,
-0.031846705824136734,
-0.07487130910158157,
-0.020363178104162216,
-0.009185152128338814,
-0.06604913622140884,
-0.23657846450805664,
-0.07390214502811432,
-0.02614106610417366,
0.1492505967617035,
-0.2119074910879135,
0.015141063369810581,
0.02340846136212349,
0.11079596728086472,
0.02291080914437771,
-0.04540029913187027,
0.02913626655936241,
0.03626388683915138,
-0.0081223975867033,
-0.08886901289224625,
0.03655870258808136,
0.006362757179886103,
-0.10133186727762222,
0.013482552021741867,
-0.14776818454265594,
0.07974237203598022,
0.06671681255102158,
0.03326130285859108,
-0.07020332664251328,
-0.0506625734269619,
-0.05583595484495163,
-0.0466204434633255,
-0.010222033597528934,
0.004185358993709087,
0.16248281300067902,
0.016696562990546227,
0.10275028645992279,
-0.07848247140645981,
-0.053171128034591675,
0.025819383561611176,
0.006499997340142727,
0.0006094908458180726,
0.1660066395998001,
0.0391024611890316,
-0.055112574249506,
0.08441724628210068,
0.0552855059504509,
-0.043205879628658295,
0.12681840360164642,
-0.08489096909761429,
-0.08348552882671356,
-0.03746737539768219,
0.049131765961647034,
0.03267446905374527,
0.10427798330783844,
-0.14222827553749084,
-0.0061058588325977325,
0.03002564236521721,
0.005146093666553497,
0.008255819790065289,
-0.16808664798736572,
-0.0039484514854848385,
0.044869519770145416,
-0.087071493268013,
0.0002536026295274496,
-0.012890650890767574,
-0.006905588787049055,
0.08731026202440262,
-0.005223650950938463,
-0.07340283691883087,
-0.030241312459111214,
-0.044377025216817856,
-0.08177307993173599,
0.17944324016571045,
-0.09378133714199066,
-0.12399233132600784,
-0.10014127194881439,
-0.008925514295697212,
-0.005379219073802233,
-0.014928895980119705,
0.027639439329504967,
-0.08483083546161652,
-0.04644589498639107,
-0.08341958373785019,
0.014536675997078419,
-0.0054542324505746365,
0.03252632915973663,
0.035450518131256104,
0.00413700332865119,
0.0777415856719017,
-0.09244891256093979,
0.01030327845364809,
-0.01142843533307314,
-0.029848549515008926,
-0.00019897711172234267,
0.03454137220978737,
0.08329953253269196,
0.1483205109834671,
0.05295388773083687,
0.033720921725034714,
-0.011551407165825367,
0.19388176500797272,
-0.11429940164089203,
0.024956420063972473,
0.13922418653964996,
-0.0008937559905461967,
0.05191437155008316,
0.16305316984653473,
0.03817092254757881,
-0.09074243903160095,
0.004192451946437359,
0.03369513154029846,
-0.022417165338993073,
-0.2196163535118103,
-0.034111347049474716,
-0.06024964898824692,
0.002460719086229801,
0.10034769028425217,
0.04087623581290245,
-0.026963289827108383,
0.025465333834290504,
-0.016132807359099388,
-0.03003716468811035,
0.04566359147429466,
0.04590308293700218,
0.05104478821158409,
0.034621696919202805,
0.105658158659935,
-0.0154900923371315,
-0.02228016033768654,
0.02930324710905552,
-0.012989236041903496,
0.22278428077697754,
-0.034124575555324554,
0.18705005943775177,
0.0410032719373703,
0.12408015877008438,
-0.011757191270589828,
0.04510711878538132,
-0.005709218792617321,
-0.0003160492342431098,
0.01806558109819889,
-0.057876937091350555,
-0.023978454992175102,
0.023634525015950203,
0.05416683107614517,
0.033227745443582535,
-0.1036355048418045,
0.04151143878698349,
0.035606417804956436,
0.3275800943374634,
0.08195716887712479,
-0.2815095782279968,
-0.08001016080379486,
0.019470464438199997,
-0.059881146997213364,
-0.03813707455992699,
0.02698083408176899,
0.13801205158233643,
-0.06177234277129173,
0.07029099017381668,
-0.052973050624132156,
0.0792224332690239,
-0.07698812335729599,
0.009163422510027885,
0.08802004903554916,
0.10757894068956375,
0.006151985842734575,
0.0520138256251812,
-0.22478753328323364,
0.2647506594657898,
-0.0028397864662110806,
0.07490134239196777,
-0.05042640492320061,
0.04536178335547447,
0.028335005044937134,
-0.012703707441687584,
0.10900339484214783,
-0.007209198549389839,
-0.11052222549915314,
-0.1611206978559494,
-0.10773174464702606,
0.012775715440511703,
0.12062292546033859,
-0.05974135547876358,
0.11337033659219742,
-0.037536878138780594,
-0.04916451498866081,
0.02809188701212406,
-0.0953381136059761,
-0.08310950547456741,
-0.09497198462486267,
0.03126441314816475,
-0.001990940887480974,
0.022388607263565063,
-0.09387706965208054,
-0.08162936568260193,
-0.04574117064476013,
0.14784453809261322,
-0.09757329523563385,
-0.050295669585466385,
-0.13864322006702423,
0.05171140283346176,
0.16362343728542328,
-0.07370176166296005,
0.04203620180487633,
0.012141882441937923,
0.11601273715496063,
0.029247455298900604,
-0.0190728772431612,
0.09671808779239655,
-0.09399258345365524,
-0.2098502665758133,
-0.048812899738550186,
0.18210889399051666,
0.029533645138144493,
0.06005225330591202,
-0.019192587584257126,
0.018172966316342354,
0.0048444089479744434,
-0.08109281957149506,
0.06766100227832794,
0.03634858876466751,
0.004766885656863451,
0.03132352977991104,
-0.02394140511751175,
0.010635843500494957,
-0.06210145726799965,
-0.03863894194364548,
0.09501990675926208,
0.2748461961746216,
-0.08389881253242493,
0.05318821221590042,
0.0425909161567688,
-0.06136747822165489,
-0.1734478622674942,
-0.024493783712387085,
0.11432754993438721,
0.037436097860336304,
-0.00100131263025105,
-0.19358953833580017,
0.03264304995536804,
0.06201910972595215,
-0.02531600184738636,
0.08766312897205353,
-0.3560672998428345,
-0.1306154578924179,
0.09119927138090134,
0.08740346878767014,
-0.026436515152454376,
-0.1705271303653717,
-0.07402326911687851,
-0.004733581095933914,
-0.03889432176947594,
0.021613027900457382,
-0.02587500587105751,
0.11264815926551819,
0.001789657399058342,
0.006292806472629309,
0.03167685121297836,
-0.052816927433013916,
0.14686769247055054,
-0.007147808559238911,
0.05170828849077225,
-0.03055473417043686,
0.036143310368061066,
-0.004680120851844549,
-0.06860844045877457,
0.011631935834884644,
-0.10301459580659866,
0.040474407374858856,
-0.12784279882907867,
-0.027100935578346252,
-0.07320179045200348,
0.01791829615831375,
-0.047803305089473724,
-0.027755849063396454,
-0.005717563908547163,
0.05364881455898285,
0.09506252408027649,
0.014241340570151806,
0.0726289376616478,
-0.05134289711713791,
0.10073693096637726,
0.1383766233921051,
0.10431745648384094,
0.03278918191790581,
-0.09042565524578094,
-0.0008896390208974481,
0.006376404780894518,
0.023540372028946877,
-0.12895837426185608,
0.043152108788490295,
0.14299233257770538,
0.04271039366722107,
0.12718960642814636,
0.04086935147643089,
-0.06419941782951355,
-0.012059223838150501,
0.05367995798587799,
-0.0806509330868721,
-0.16895437240600586,
-0.012240656651556492,
0.010949064046144485,
-0.131629079580307,
-0.00794893503189087,
0.10896404087543488,
-0.028889281675219536,
0.0020388721022754908,
0.007494013290852308,
0.061378877609968185,
-0.01008183415979147,
0.23577290773391724,
0.02796601690351963,
0.09449505060911179,
-0.09635166078805923,
0.07911963015794754,
0.042697370052337646,
-0.08261603116989136,
0.04042130708694458,
0.12469436228275299,
-0.05770545080304146,
-0.027672164142131805,
0.04303072392940521,
0.08690614253282547,
0.06695259362459183,
-0.03658991679549217,
-0.12329141795635223,
-0.14841122925281525,
0.09079363942146301,
0.0757966935634613,
0.021600522100925446,
0.010184862650930882,
-0.015425154007971287,
0.02492903172969818,
-0.08423269540071487,
0.13553039729595184,
0.09754215180873871,
0.0500747412443161,
-0.11591306328773499,
0.12253784388303757,
-0.004347872454673052,
0.006713365204632282,
-0.002132834866642952,
0.017590370029211044,
-0.1076909676194191,
0.015733903273940086,
-0.12265757471323013,
0.012889090925455093,
-0.05029905214905739,
-0.0003449652576819062,
-0.004276263061910868,
-0.05566636472940445,
-0.044848453253507614,
0.025774240493774414,
-0.09846681356430054,
-0.052001241594552994,
-0.027368564158678055,
0.05835971608757973,
-0.09465350210666656,
-0.042073749005794525,
0.023319927975535393,
-0.127224400639534,
0.09842018783092499,
0.02794509381055832,
0.020401563495397568,
0.0057935938239097595,
-0.09515854716300964,
0.010489421896636486,
0.022787198424339294,
0.01219091285020113,
0.026748400181531906,
-0.16144689917564392,
-0.010302028618752956,
-0.038152482360601425,
-0.016740858554840088,
-0.02165600098669529,
0.026575082913041115,
-0.11805769801139832,
0.022549232468008995,
-0.03623223304748535,
-0.03828864172101021,
-0.04569574445486069,
0.05259428918361664,
0.06955482810735703,
0.013384761288762093,
0.1306026726961136,
-0.08164089918136597,
0.07334350794553757,
-0.22966939210891724,
-0.001817443291656673,
-0.00713332137092948,
-0.0631953552365303,
-0.06152684614062309,
-0.014981194399297237,
0.11073050647974014,
-0.06359494477510452,
0.07361672818660736,
-0.024259846657514572,
0.04435444250702858,
0.02004322223365307,
-0.07707542926073074,
0.05488697066903114,
0.061824146658182144,
0.14790838956832886,
0.029062170535326004,
-0.02324662171304226,
0.07464680075645447,
-0.013011963106691837,
0.05728324502706528,
0.1093333289027214,
0.1442028284072876,
0.1561240702867508,
0.07768185436725616,
0.05834932252764702,
0.07867959141731262,
-0.14557261765003204,
-0.14893148839473724,
0.1311403512954712,
-0.05440123379230499,
0.136556938290596,
-0.035087525844573975,
0.1957055628299713,
0.0997287780046463,
-0.18561768531799316,
0.06763456016778946,
-0.028071699663996696,
-0.09160331636667252,
-0.10919270664453506,
-0.10219312459230423,
-0.08184235543012619,
-0.1307494342327118,
0.002414219779893756,
-0.10171663761138916,
0.059075746685266495,
0.03595883771777153,
0.03594938665628433,
0.031890273094177246,
0.10899639129638672,
0.057286009192466736,
0.01956363394856453,
0.10270806401968002,
0.023112932220101357,
-0.015969812870025635,
-0.012015257030725479,
-0.10323352366685867,
0.037123505026102066,
-0.021785089746117592,
0.046417176723480225,
-0.036805570125579834,
-0.08459237217903137,
0.05703463405370712,
0.008906231261789799,
-0.09797574579715729,
0.023895785212516785,
-0.025511575862765312,
0.04874490946531296,
0.08425258100032806,
0.04384802654385567,
-0.011161173693835735,
-0.014540345408022404,
0.22126446664333344,
-0.0863884910941124,
-0.0638372004032135,
-0.11013644933700562,
0.18571195006370544,
-0.012141562066972256,
-0.0016366703202947974,
0.03084407187998295,
-0.0656806156039238,
-0.01168595626950264,
0.157022163271904,
0.15656237304210663,
-0.04533269628882408,
-0.011670256033539772,
0.010039002634584904,
-0.005955961532890797,
-0.027766544371843338,
0.07937482744455338,
0.12026393413543701,
0.06404883414506912,
-0.04941811040043831,
-0.013584227301180363,
-0.02410419099032879,
-0.05809978395700455,
-0.05953320860862732,
0.09845573455095291,
0.019252920523285866,
0.01167846005409956,
-0.010612490586936474,
0.100115105509758,
-0.0699397474527359,
-0.14828217029571533,
0.03878800943493843,
-0.17820142209529877,
-0.19417104125022888,
-0.04948020726442337,
0.038580749183893204,
0.055225785821676254,
0.05339420586824417,
0.0017220217268913984,
-0.025815537199378014,
0.09879444539546967,
-0.0032723674084991217,
-0.03934811055660248,
-0.08684998750686646,
0.061136938631534576,
-0.12614817917346954,
0.20747806131839752,
-0.030601220205426216,
0.0052964948117733,
0.1201888918876648,
0.03070228360593319,
-0.1133555918931961,
0.03951198235154152,
0.09361167252063751,
-0.11883717775344849,
0.05703127384185791,
0.17935781180858612,
-0.04299207031726837,
0.1215047761797905,
0.04225821793079376,
-0.08224216103553772,
0.0008016140782274306,
-0.045517995953559875,
-0.05615564435720444,
-0.05691881105303764,
-0.005059396382421255,
-0.044237446039915085,
0.13541725277900696,
0.2074686735868454,
-0.06896040588617325,
-0.010729542933404446,
-0.04022211208939552,
0.008810206316411495,
0.02434924617409706,
0.12237570434808731,
-0.021897172555327415,
-0.2461966872215271,
0.02186192199587822,
-0.0016902540810406208,
0.038261089473962784,
-0.18460381031036377,
-0.0804126188158989,
0.011793804354965687,
-0.04683176428079605,
-0.07855937629938126,
0.1188986748456955,
0.07406344264745712,
0.03882540762424469,
-0.050851743668317795,
-0.08672181516885757,
-0.025812797248363495,
0.17303110659122467,
-0.16530801355838776,
-0.05284976586699486
] |
null | null | transformers |
<div align="center">
<img src="./figures/logo.png" alt="image" width=8%>
<h2 align="center"> ChatCell: Facilitating Single-Cell Analysis with Natural Language </h2>
<p align="center">
<a href="https://www.zjukg.org/project/ChatCell">💻 Project Page</a> •
<a href="https://huggingface.co/datasets/zjunlp/ChatCell-Instructions">🤗 Dataset</a> •
<a href="https://huggingface.co/spaces/zjunlp/Chatcell">🍎 Demo</a> •
<a href="https://arxiv.org/abs/2402.08303">📑 Paper</a> •
<a href="#1">🏖️ Overview</a> •
<a href="#2">🧬 Single-cell Analysis Tasks</a> •
<a href="#3">🛠️ Quickstart</a> •
<a href="#4">📝 Cite</a>
</p>
<img src="./figures/intro.jpg" alt="image" width=60%>
<b>ChatCell</b> allows researchers to input instructions in either natural or single-cell language, thereby facilitating the execution of necessary tasks in single-cell analysis. Black and red texts denote human and single-cell language, respectively.
</div>
## 📌 Table of Contents
- [🏖️ Overview](#1)
- [🧬 Single-cell Analysis Tasks](#2)
- [🛠️ Quickstart](#3)
- [📝 Cite](#4)
---
<h2 id="1">🏖️ Overview</h2>
**Background**
- Single-cell biology examines the intricate functions of the cells, ranging from energy production to genetic information transfer, playing a critical role in unraveling the fundamental principles of life and mechanisms influencing health and disease.
- The field has witnessed a surge in single-cell RNA sequencing (scRNA-seq) data, driven by advancements in high-throughput sequencing and reduced costs.
- Traditional single-cell foundation models leverage extensive scRNA-seq datasets, applying NLP techniques to analyze gene expression matrices—structured formats that simplify scRNA-seq data into computationally tractable representations—during pre-training. They are subsequently fine-tuned for distinct single-cell analysis tasks, as shown in Figure (a).
<p align="center">
<img src="./figures/overview.jpg" alt="image" width=100%>
</p>
<div align="center">
Figure 1: (a) Comparison of traditional single-cell engineering and <b>ChatCell</b>. (b) Overview of <b>ChatCell</b>.
</div>
<br>
We present <b>ChatCell</b>, a new paradigm that leverages natural language to make single-cell analysis more accessible and intuitive.
- Initially, we convert scRNA-seq data into a single-cell language that LLMs can readily interpret.
- Subsequently, we employ templates to integrate this single-cell language with task descriptions and target outcomes, creating comprehensive single-cell instructions.
- To improve the LLM's expertise in the single-cell domain, we conduct vocabulary adaptation, enriching the model with a specialized single-cell lexicon.
- Following this, we utilize unified sequence generation to empower the model to adeptly execute a range of single-cell tasks.
<h2 id="2">🧬 Single-cell Analysis Tasks</h2>
We concentrate on the following single-cell tasks:
- <b>Random Cell Sentence Generation.</b>
Random cell sentence generation challenges the model to create cell sentences devoid of predefined biological conditions or constraints. This task aims to evaluate the model's ability to generate valid and contextually appropriate cell sentences, potentially simulating natural variations in cellular behavior.
<p align="center">
<img src="./figures/example1.jpg" alt="image" width=80%>
</p>
- <b>Pseudo-cell Generation.</b>
Pseudo-cell generation focuses on generating gene sequences tailored to specific cell type labels. This task is vital for unraveling gene expression and regulation across different cell types, offering insights for medical research and disease studies, particularly in the context of diseased cell types.
<p align="center">
<img src="./figures/example2.jpg" alt="image" width=80%>
</p>
- <b>Cell Type Annotation.</b>
For cell type annotation, the model is tasked with precisely classifying cells into their respective types based on gene expression patterns encapsulated in cell sentences. This task is fundamental for understanding cellular functions and interactions within tissues and organs, playing a crucial role in developmental biology and regenerative medicine.
<p align="center">
<img src="./figures/example3.jpg" alt="image" width=80%>
</p>
- <b>Drug Sensitivity Prediction.</b>
The drug sensitivity prediction task aims to predict the response of different cells to various drugs. It is pivotal in designing effective, personalized treatment plans and contributes significantly to drug development, especially in optimizing drug efficacy and safety.
<p align="center">
<img src="./figures/example4.jpg" alt="image" width=80%>
</p>
<h2 id="3">🛠️ Quickstart</h2>
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("zjunlp/chatcell-base")
model = AutoModelForSeq2SeqLM.from_pretrained("zjunlp/chatcell-base")
input_text="Detail the 100 starting genes for a Mix, ranked by expression level: "
# Encode the input text and generate a response with specified generation parameters
input_ids = tokenizer(input_text,return_tensors="pt").input_ids
output_ids = model.generate(input_ids, max_length=512, num_return_sequences=1, no_repeat_ngram_size=2, top_k=50, top_p=0.95, do_sample=True)
# Decode and print the generated output text
output_text = tokenizer.decode(output_ids[0],skip_special_tokens=True)
print(output_text)
```
<h2 id="4">📝 Cite</h2>
If you use our repository, please cite the following related paper:
```
@article{fang2024chatcell,
title={ChatCell: Facilitating Single-Cell Analysis with Natural Language},
author={Fang, Yin and Liu, Kangwei and Zhang, Ningyu and Deng, Xinle and Yang, Penghui and Chen, Zhuo and Tang, Xiangru and Gerstein, Mark and Fan, Xiaohui and Chen, Huajun},
journal={arXiv preprint arXiv:2402.08303},
year={2024},
}
``` | {"tags": ["biology", "single-cell", "single-cell analysis", "text-generation-inference"], "pipeline_tag": "text-generation"} | text-generation | zjunlp/chatcell-base | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"biology",
"single-cell",
"single-cell analysis",
"text-generation-inference",
"text-generation",
"arxiv:2402.08303",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T06:15:17+00:00 | [
"2402.08303"
] | [] | TAGS
#transformers #safetensors #t5 #text2text-generation #biology #single-cell #single-cell analysis #text-generation-inference #text-generation #arxiv-2402.08303 #autotrain_compatible #endpoints_compatible #region-us
|
<div align="center">
<img src="./figures/URL" alt="image" width=8%>
<h2 align="center"> ChatCell: Facilitating Single-Cell Analysis with Natural Language </h2>
<p align="center">
<a href="URL Project Page</a> •
<a href="URL Dataset</a> •
<a href="URL Demo</a> •
<a href="URL Paper</a> •
<a href="#1">️ Overview</a> •
<a href="#2"> Single-cell Analysis Tasks</a> •
<a href="#3">️ Quickstart</a> •
<a href="#4"> Cite</a>
</p>
<img src="./figures/URL" alt="image" width=60%>
<b>ChatCell</b> allows researchers to input instructions in either natural or single-cell language, thereby facilitating the execution of necessary tasks in single-cell analysis. Black and red texts denote human and single-cell language, respectively.
</div>
## Table of Contents
- ️ Overview
- Single-cell Analysis Tasks
- ️ Quickstart
- Cite
---
<h2 id="1">️ Overview</h2>
Background
- Single-cell biology examines the intricate functions of the cells, ranging from energy production to genetic information transfer, playing a critical role in unraveling the fundamental principles of life and mechanisms influencing health and disease.
- The field has witnessed a surge in single-cell RNA sequencing (scRNA-seq) data, driven by advancements in high-throughput sequencing and reduced costs.
- Traditional single-cell foundation models leverage extensive scRNA-seq datasets, applying NLP techniques to analyze gene expression matrices—structured formats that simplify scRNA-seq data into computationally tractable representations—during pre-training. They are subsequently fine-tuned for distinct single-cell analysis tasks, as shown in Figure (a).
<p align="center">
<img src="./figures/URL" alt="image" width=100%>
</p>
<div align="center">
Figure 1: (a) Comparison of traditional single-cell engineering and <b>ChatCell</b>. (b) Overview of <b>ChatCell</b>.
</div>
<br>
We present <b>ChatCell</b>, a new paradigm that leverages natural language to make single-cell analysis more accessible and intuitive.
- Initially, we convert scRNA-seq data into a single-cell language that LLMs can readily interpret.
- Subsequently, we employ templates to integrate this single-cell language with task descriptions and target outcomes, creating comprehensive single-cell instructions.
- To improve the LLM's expertise in the single-cell domain, we conduct vocabulary adaptation, enriching the model with a specialized single-cell lexicon.
- Following this, we utilize unified sequence generation to empower the model to adeptly execute a range of single-cell tasks.
<h2 id="2"> Single-cell Analysis Tasks</h2>
We concentrate on the following single-cell tasks:
- <b>Random Cell Sentence Generation.</b>
Random cell sentence generation challenges the model to create cell sentences devoid of predefined biological conditions or constraints. This task aims to evaluate the model's ability to generate valid and contextually appropriate cell sentences, potentially simulating natural variations in cellular behavior.
<p align="center">
<img src="./figures/URL" alt="image" width=80%>
</p>
- <b>Pseudo-cell Generation.</b>
Pseudo-cell generation focuses on generating gene sequences tailored to specific cell type labels. This task is vital for unraveling gene expression and regulation across different cell types, offering insights for medical research and disease studies, particularly in the context of diseased cell types.
<p align="center">
<img src="./figures/URL" alt="image" width=80%>
</p>
- <b>Cell Type Annotation.</b>
For cell type annotation, the model is tasked with precisely classifying cells into their respective types based on gene expression patterns encapsulated in cell sentences. This task is fundamental for understanding cellular functions and interactions within tissues and organs, playing a crucial role in developmental biology and regenerative medicine.
<p align="center">
<img src="./figures/URL" alt="image" width=80%>
</p>
- <b>Drug Sensitivity Prediction.</b>
The drug sensitivity prediction task aims to predict the response of different cells to various drugs. It is pivotal in designing effective, personalized treatment plans and contributes significantly to drug development, especially in optimizing drug efficacy and safety.
<p align="center">
<img src="./figures/URL" alt="image" width=80%>
</p>
<h2 id="3">️ Quickstart</h2>
<h2 id="4"> Cite</h2>
If you use our repository, please cite the following related paper:
| [
"## Table of Contents\n\n- ️ Overview\n- Single-cell Analysis Tasks\n- ️ Quickstart\n- Cite\n\n\n---\n\n<h2 id=\"1\">️ Overview</h2>\n\nBackground\n- Single-cell biology examines the intricate functions of the cells, ranging from energy production to genetic information transfer, playing a critical role in unraveling the fundamental principles of life and mechanisms influencing health and disease. \n- The field has witnessed a surge in single-cell RNA sequencing (scRNA-seq) data, driven by advancements in high-throughput sequencing and reduced costs.\n- Traditional single-cell foundation models leverage extensive scRNA-seq datasets, applying NLP techniques to analyze gene expression matrices—structured formats that simplify scRNA-seq data into computationally tractable representations—during pre-training. They are subsequently fine-tuned for distinct single-cell analysis tasks, as shown in Figure (a).\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=100%>\n</p>\n<div align=\"center\">\nFigure 1: (a) Comparison of traditional single-cell engineering and <b>ChatCell</b>. (b) Overview of <b>ChatCell</b>.\n</div>\n<br>\nWe present <b>ChatCell</b>, a new paradigm that leverages natural language to make single-cell analysis more accessible and intuitive.\n\n- Initially, we convert scRNA-seq data into a single-cell language that LLMs can readily interpret.\n- Subsequently, we employ templates to integrate this single-cell language with task descriptions and target outcomes, creating comprehensive single-cell instructions.\n- To improve the LLM's expertise in the single-cell domain, we conduct vocabulary adaptation, enriching the model with a specialized single-cell lexicon.\n- Following this, we utilize unified sequence generation to empower the model to adeptly execute a range of single-cell tasks.\n\n\n<h2 id=\"2\"> Single-cell Analysis Tasks</h2>\n\nWe concentrate on the following single-cell tasks:\n\n- <b>Random Cell Sentence Generation.</b>\nRandom cell sentence generation challenges the model to create cell sentences devoid of predefined biological conditions or constraints. This task aims to evaluate the model's ability to generate valid and contextually appropriate cell sentences, potentially simulating natural variations in cellular behavior. \n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n\n- <b>Pseudo-cell Generation.</b>\nPseudo-cell generation focuses on generating gene sequences tailored to specific cell type labels. This task is vital for unraveling gene expression and regulation across different cell types, offering insights for medical research and disease studies, particularly in the context of diseased cell types.\n\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n- <b>Cell Type Annotation.</b>\nFor cell type annotation, the model is tasked with precisely classifying cells into their respective types based on gene expression patterns encapsulated in cell sentences. This task is fundamental for understanding cellular functions and interactions within tissues and organs, playing a crucial role in developmental biology and regenerative medicine.\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n- <b>Drug Sensitivity Prediction.</b>\nThe drug sensitivity prediction task aims to predict the response of different cells to various drugs. It is pivotal in designing effective, personalized treatment plans and contributes significantly to drug development, especially in optimizing drug efficacy and safety.\n\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n<h2 id=\"3\">️ Quickstart</h2>\n\n\n\n\n\n<h2 id=\"4\"> Cite</h2>\n\nIf you use our repository, please cite the following related paper:"
] | [
"TAGS\n#transformers #safetensors #t5 #text2text-generation #biology #single-cell #single-cell analysis #text-generation-inference #text-generation #arxiv-2402.08303 #autotrain_compatible #endpoints_compatible #region-us \n",
"## Table of Contents\n\n- ️ Overview\n- Single-cell Analysis Tasks\n- ️ Quickstart\n- Cite\n\n\n---\n\n<h2 id=\"1\">️ Overview</h2>\n\nBackground\n- Single-cell biology examines the intricate functions of the cells, ranging from energy production to genetic information transfer, playing a critical role in unraveling the fundamental principles of life and mechanisms influencing health and disease. \n- The field has witnessed a surge in single-cell RNA sequencing (scRNA-seq) data, driven by advancements in high-throughput sequencing and reduced costs.\n- Traditional single-cell foundation models leverage extensive scRNA-seq datasets, applying NLP techniques to analyze gene expression matrices—structured formats that simplify scRNA-seq data into computationally tractable representations—during pre-training. They are subsequently fine-tuned for distinct single-cell analysis tasks, as shown in Figure (a).\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=100%>\n</p>\n<div align=\"center\">\nFigure 1: (a) Comparison of traditional single-cell engineering and <b>ChatCell</b>. (b) Overview of <b>ChatCell</b>.\n</div>\n<br>\nWe present <b>ChatCell</b>, a new paradigm that leverages natural language to make single-cell analysis more accessible and intuitive.\n\n- Initially, we convert scRNA-seq data into a single-cell language that LLMs can readily interpret.\n- Subsequently, we employ templates to integrate this single-cell language with task descriptions and target outcomes, creating comprehensive single-cell instructions.\n- To improve the LLM's expertise in the single-cell domain, we conduct vocabulary adaptation, enriching the model with a specialized single-cell lexicon.\n- Following this, we utilize unified sequence generation to empower the model to adeptly execute a range of single-cell tasks.\n\n\n<h2 id=\"2\"> Single-cell Analysis Tasks</h2>\n\nWe concentrate on the following single-cell tasks:\n\n- <b>Random Cell Sentence Generation.</b>\nRandom cell sentence generation challenges the model to create cell sentences devoid of predefined biological conditions or constraints. This task aims to evaluate the model's ability to generate valid and contextually appropriate cell sentences, potentially simulating natural variations in cellular behavior. \n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n\n- <b>Pseudo-cell Generation.</b>\nPseudo-cell generation focuses on generating gene sequences tailored to specific cell type labels. This task is vital for unraveling gene expression and regulation across different cell types, offering insights for medical research and disease studies, particularly in the context of diseased cell types.\n\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n- <b>Cell Type Annotation.</b>\nFor cell type annotation, the model is tasked with precisely classifying cells into their respective types based on gene expression patterns encapsulated in cell sentences. This task is fundamental for understanding cellular functions and interactions within tissues and organs, playing a crucial role in developmental biology and regenerative medicine.\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n- <b>Drug Sensitivity Prediction.</b>\nThe drug sensitivity prediction task aims to predict the response of different cells to various drugs. It is pivotal in designing effective, personalized treatment plans and contributes significantly to drug development, especially in optimizing drug efficacy and safety.\n\n\n<p align=\"center\">\n<img src=\"./figures/URL\" alt=\"image\" width=80%>\n</p>\n\n<h2 id=\"3\">️ Quickstart</h2>\n\n\n\n\n\n<h2 id=\"4\"> Cite</h2>\n\nIf you use our repository, please cite the following related paper:"
] | [
77,
996
] | [
"passage: TAGS\n#transformers #safetensors #t5 #text2text-generation #biology #single-cell #single-cell analysis #text-generation-inference #text-generation #arxiv-2402.08303 #autotrain_compatible #endpoints_compatible #region-us \n"
] | [
0.005268423818051815,
-0.0006200210191309452,
-0.006125427782535553,
-0.07780243456363678,
0.08789871633052826,
0.0004210644110571593,
0.21900059282779694,
0.141391783952713,
-0.03193517401814461,
0.03248317912220955,
0.11028508841991425,
0.14322663843631744,
0.017003003507852554,
0.1368696689605713,
-0.08726264536380768,
-0.10550718009471893,
0.03133787959814072,
0.017107831314206123,
-0.03511926159262657,
0.053019870072603226,
0.0964236631989479,
-0.026391612365841866,
0.10612654685974121,
-0.06597983092069626,
-0.12451019138097763,
0.013961976394057274,
0.0881529375910759,
-0.1146271675825119,
0.16308248043060303,
0.03236667439341545,
0.09076447784900665,
0.0771142765879631,
-0.025718821212649345,
-0.1587182581424713,
0.03926762193441391,
0.026582028716802597,
-0.04784517362713814,
0.07634638249874115,
0.08891011774539948,
-0.08684622496366501,
0.07115110009908676,
0.0013765033800154924,
0.010527596808969975,
0.06837461143732071,
-0.09465792775154114,
0.001921778079122305,
-0.02196289785206318,
0.014167233370244503,
0.06771764904260635,
0.06090063601732254,
-0.0039373282343149185,
0.12319769710302353,
0.11778190732002258,
0.12406768649816513,
0.22294332087039948,
-0.3157714605331421,
0.029145073145627975,
0.07688695192337036,
0.15202923119068146,
0.07575657218694687,
0.03719494491815567,
0.09748239815235138,
0.07000177353620529,
-0.01748146489262581,
0.05965324863791466,
-0.09366907179355621,
-0.07571732252836227,
0.0014380236389115453,
-0.08761805295944214,
0.006837454158812761,
0.2551490068435669,
-0.12190920859575272,
0.02305164746940136,
-0.05416655167937279,
-0.11723208427429199,
-0.09070075303316116,
0.0015836561797186732,
-0.09791114926338196,
-0.005170444492250681,
0.0061078984290361404,
0.013495384715497494,
-0.04822009429335594,
-0.06612338870763779,
-0.029511546716094017,
-0.1952785700559616,
0.10992615669965744,
-0.006610157899558544,
-0.038338322192430496,
-0.19048647582530975,
0.04373134300112724,
0.07453839480876923,
-0.09486435353755951,
0.045567579567432404,
-0.028180578723549843,
0.0042369673028588295,
-0.06803564727306366,
-0.03011164255440235,
-0.22530412673950195,
0.1613505631685257,
0.06619317829608917,
0.011606113985180855,
0.03475232049822807,
-0.14944612979888916,
0.03145546466112137,
0.01604551635682583,
-0.12116144597530365,
-0.03179597854614258,
-0.015559794381260872,
0.058861296623945236,
-0.06647175550460815,
-0.004435643088072538,
-0.01513816136866808,
-0.12520359456539154,
0.003309412393718958,
0.10727620869874954,
0.12506820261478424,
0.01880556158721447,
0.08705839514732361,
0.0024150751996785402,
-0.0191179309040308,
-0.001866592443548143,
-0.08386532217264175,
-0.042570918798446655,
0.03365259990096092,
0.11916365474462509,
0.03866630792617798,
-0.021228253841400146,
-0.01795906201004982,
-0.07592204213142395,
-0.06430355459451675,
-0.10863625258207321,
-0.04577565938234329,
0.0034806891344487667,
-0.11451942473649979,
0.03524329140782356,
-0.01131889596581459,
-0.0021672567818313837,
-0.18153591454029083,
-0.027125032618641853,
0.00436768401414156,
-0.0743844211101532,
-0.06121150404214859,
-0.017792440950870514,
-0.011373866349458694,
-0.05990329384803772,
0.03888186439871788,
-0.04438966512680054,
-0.013469330966472626,
-0.013722889125347137,
0.04413408786058426,
0.022379934787750244,
0.10867608338594437,
-0.0780118927359581,
0.019508231431245804,
-0.0950353816151619,
0.02496696636080742,
-0.07834074646234512,
-0.0054513243958354,
-0.043652668595314026,
0.08369965851306915,
-0.06715968251228333,
0.0003570470435079187,
-0.0649198666214943,
-0.006373565644025803,
0.04145204648375511,
0.14504177868366241,
-0.09648627042770386,
-0.05245549604296684,
0.22857248783111572,
-0.09144257009029388,
-0.20880240201950073,
0.017966685816645622,
0.02146388217806816,
0.09038012474775314,
0.06094728410243988,
0.23492537438869476,
0.007559350226074457,
-0.013755112886428833,
-0.013568294234573841,
0.05353913456201553,
-0.06316085904836655,
-0.029362836852669716,
0.06953806430101395,
0.00907971989363432,
-0.10613555461168289,
0.017501233145594597,
0.11107692122459412,
0.0729636624455452,
-0.07906527817249298,
0.0064262328669428825,
-0.05394050106406212,
-0.0118938023224473,
0.015345321968197823,
-0.07335279881954193,
0.06567443162202835,
-0.12845921516418457,
0.03559420257806778,
0.016849055886268616,
0.017767978832125664,
-0.07518792152404785,
0.022044667974114418,
-0.06109175831079483,
0.09911699593067169,
-0.07017689943313599,
0.03651866316795349,
-0.15854884684085846,
-0.1539672166109085,
0.0024472696240991354,
0.07957514375448227,
-0.002860588487237692,
0.024085385724902153,
0.01684013195335865,
0.004317556042224169,
-0.024414395913481712,
0.03743298724293709,
0.16042327880859375,
0.05509728565812111,
-0.10203180462121964,
-0.15269432961940765,
0.08666978776454926,
-0.08912838250398636,
0.020664140582084656,
-0.17157132923603058,
0.0263716708868742,
0.08617551624774933,
0.11132124811410904,
0.036172572523355484,
0.034673988819122314,
0.03314737230539322,
-0.005078759975731373,
-0.1651383340358734,
-0.04119144752621651,
0.09315638989210129,
-0.03211010619997978,
-0.07182734459638596,
0.17450939118862152,
-0.19246581196784973,
0.18543031811714172,
0.0981915295124054,
-0.16789239645004272,
-0.07612196356058121,
-0.013739512301981449,
-0.0021034274250268936,
0.007572011556476355,
-0.022698599845170975,
-0.05457307770848274,
-0.01948206126689911,
-0.0022454026620835066,
0.16892315447330475,
-0.06910067796707153,
-0.04960618168115616,
0.04028356447815895,
-0.0371209979057312,
0.020177504047751427,
0.09325434267520905,
0.0018236534669995308,
-0.26446568965911865,
0.13801831007003784,
0.1397973895072937,
0.1153242215514183,
0.0982324481010437,
0.023332074284553528,
-0.0052018663845956326,
0.028786903247237206,
0.037563517689704895,
0.015943385660648346,
-0.0435924306511879,
-0.05151708796620369,
-0.010184573009610176,
0.07002006471157074,
0.02862531691789627,
0.04070347175002098,
-0.07172930985689163,
-0.00247903261333704,
0.042840927839279175,
-0.03950522840023041,
0.035000212490558624,
0.058450158685445786,
0.030790066346526146,
0.18162988126277924,
-0.06310002505779266,
-0.013382614590227604,
0.024883391335606575,
0.01967153698205948,
-0.18395763635635376,
0.25294041633605957,
-0.08884355425834656,
-0.3196113109588623,
-0.10339079052209854,
-0.14877186715602875,
-0.017121853306889534,
0.08712450414896011,
0.10497229546308517,
-0.0630243718624115,
0.008205253630876541,
-0.05323139205574989,
0.06182912364602089,
0.01634785160422325,
0.056265346705913544,
-0.04529969021677971,
0.08007527887821198,
0.019614363089203835,
-0.07481708377599716,
-0.03372640535235405,
0.012580974958837032,
-0.02300761267542839,
0.11996658891439438,
-0.10568659752607346,
0.07501188665628433,
0.17162613570690155,
-0.016002517193555832,
-0.06089510768651962,
-0.08958965539932251,
0.1092083752155304,
-0.047629714012145996,
0.017127804458141327,
0.19220396876335144,
-0.006664832588285208,
0.033582188189029694,
0.08125552535057068,
-0.019391248002648354,
-0.05970287322998047,
0.07317847013473511,
0.009113162755966187,
-0.04795021563768387,
-0.311544269323349,
-0.07564792782068253,
-0.0023306196089833975,
0.11871195584535599,
0.006980399135500193,
0.060936085879802704,
0.17990244925022125,
0.10110586881637573,
0.03487624228000641,
0.04313031956553459,
0.001991582801565528,
0.11556998640298843,
0.18577371537685394,
-0.01338700857013464,
0.14444664120674133,
-0.023022247478365898,
-0.1160631850361824,
0.104685939848423,
0.09977434575557709,
0.08510887622833252,
0.07882717996835709,
0.12150738388299942,
0.0028379361610859632,
-0.016178447753190994,
0.0911230742931366,
0.17015200853347778,
0.007485667243599892,
-0.046424027532339096,
-0.03528622165322304,
-0.05532794073224068,
0.011857353150844574,
-0.015168771147727966,
-0.1349848061800003,
-0.09323500841856003,
-0.07962848246097565,
0.08293687552213669,
0.07040673494338989,
0.026275988668203354,
0.10883621871471405,
-0.2187739908695221,
0.03115234524011612,
0.0912255272269249,
-0.022053509950637817,
-0.11825255304574966,
0.09096353501081467,
0.11322999000549316,
-0.06760233640670776,
0.07692568004131317,
-0.06865570694208145,
0.08710619807243347,
-0.008071654476225376,
0.07179287075996399,
-0.07879389077425003,
-0.10852441936731339,
-0.0490952767431736,
0.11936976760625839,
-0.28450027108192444,
0.15820036828517914,
-0.016435520723462105,
-0.11203894019126892,
-0.07153550535440445,
-0.021953627467155457,
-0.013591472059488297,
0.20650769770145416,
0.13726955652236938,
0.008603502996265888,
-0.10858079791069031,
-0.030174357816576958,
-0.06336861848831177,
-0.005133831407874823,
0.11485929787158966,
-0.031245192512869835,
0.11390592902898788,
-0.06363455951213837,
0.017784640192985535,
-0.006841627880930901,
-0.07372400909662247,
-0.06094912439584732,
-0.08220325410366058,
0.11937624961137772,
-0.0015624897787347436,
0.10837516188621521,
-0.016213247552514076,
-0.01584891602396965,
-0.00757428165525198,
0.20417959988117218,
-0.1282864809036255,
-0.062072865664958954,
-0.1494975984096527,
-0.04610135406255722,
0.058785662055015564,
-0.07796075195074081,
0.00436968170106411,
-0.020000284537672997,
0.042222559452056885,
-0.004181734286248684,
-0.2509472370147705,
0.165352001786232,
-0.10046076029539108,
-0.11588234454393387,
-0.03802245110273361,
0.15575768053531647,
-0.1519995480775833,
0.049993425607681274,
0.0617358535528183,
-0.020796552300453186,
-0.058392394334077835,
-0.044967494904994965,
0.06837671995162964,
-0.10279607027769089,
0.07389852404594421,
0.019770080223679543,
-0.1745496690273285,
-0.08166751265525818,
-0.03948095813393593,
-0.054107166826725006,
0.2945336699485779,
0.2396153062582016,
0.008068835362792015,
0.139963299036026,
0.04082976281642914,
-0.1576370745897293,
-0.2527044415473938,
-0.06664466112852097,
-0.09527400881052017,
-0.014185846783220768,
0.05349882319569588,
-0.1921672523021698,
0.12248359620571136,
0.04908661171793938,
-0.012489527463912964,
0.08741331845521927,
-0.12543070316314697,
-0.145973801612854,
0.12159451097249985,
0.034224264323711395,
0.2838757634162903,
-0.22645622491836548,
-0.0963897630572319,
-0.1218620240688324,
-0.09936639666557312,
0.16638678312301636,
-0.15849308669567108,
0.09298093616962433,
0.025417571887373924,
0.024825729429721832,
0.026881085708737373,
-0.01809995248913765,
0.051717158406972885,
0.012089237570762634,
0.032063134014606476,
-0.060559820383787155,
-0.09166362136602402,
0.09467872232198715,
0.058365944772958755,
0.028122015297412872,
-0.018537553027272224,
0.09337788075208664,
-0.11685033142566681,
-0.01764640584588051,
-0.004934447351843119,
0.03830524906516075,
0.016399327665567398,
-0.04491593688726425,
-0.07861605286598206,
-0.047747768461704254,
0.06462561339139938,
-0.06133474409580231,
0.2794666886329651,
-0.057876069098711014,
0.15375874936580658,
0.14534975588321686,
0.19094575941562653,
-0.01990344561636448,
0.10917361080646515,
-0.02972203493118286,
-0.0739273726940155,
-0.016864316537976265,
-0.07246237993240356,
0.06732041388750076,
0.08085612207651138,
-0.04646474868059158,
0.0456450879573822,
0.10448190569877625,
0.05076802149415016,
0.0073915389366447926,
0.11263985931873322,
-0.25334179401397705,
-0.021579083055257797,
-0.06090373173356056,
0.00594727136194706,
-0.018967537209391594,
0.15296106040477753,
0.22924990952014923,
0.03808937594294548,
-0.034975264221429825,
-0.02844107896089554,
0.013267907314002514,
-0.023984970524907112,
0.1542685478925705,
0.014823099598288536,
0.06359904259443283,
-0.08517858386039734,
-0.017041226848959923,
0.02597874216735363,
-0.044575124979019165,
0.05636253580451012,
0.10697803646326065,
-0.1483648270368576,
-0.07628452777862549,
0.07854510843753815,
0.19650360941886902,
-0.15894487500190735,
-0.01775980368256569,
-0.11074340343475342,
-0.16771017014980316,
0.039750032126903534,
0.33457526564598083,
0.05393990874290466,
0.06729577481746674,
0.01216654758900404,
-0.07941332459449768,
-0.08529794216156006,
0.0991629958152771,
-0.07304704189300537,
0.11582250893115997,
-0.1044241264462471,
0.15270115435123444,
-0.09608045965433121,
0.06425485759973526,
-0.1301959753036499,
0.04081561416387558,
-0.17355769872665405,
-0.059996169060468674,
-0.13128462433815002,
-0.03434685245156288,
-0.059399086982011795,
-0.08532704412937164,
0.017666231840848923,
-0.002378281904384494,
0.009813865646719933,
-0.027659771963953972,
-0.04176471382379532,
0.016239983960986137,
-0.04333420842885971,
0.064133420586586,
-0.09162416309118271,
0.005487725138664246,
0.015917662531137466,
-0.030480358749628067,
0.13768987357616425,
0.07946489751338959,
-0.023742659017443657,
0.01759735681116581,
-0.10220412164926529,
-0.0628928393125534,
0.09873371571302414,
0.010941991582512856,
-0.018617555499076843,
-0.09726744145154953,
-0.019455431029200554,
0.06678582727909088,
0.001895869616419077,
0.04615924507379532,
0.012787237763404846,
-0.042924802750349045,
-0.02254810370504856,
-0.12659917771816254,
-0.061785537749528885,
0.0019243458518758416,
-0.050294771790504456,
-0.006525067612528801,
-0.036934614181518555,
0.10738750547170639,
-0.07774483412504196,
0.00530365901067853,
-0.11898428946733475,
0.033980872482061386,
0.0011938465759158134,
-0.18992197513580322,
-0.05796726420521736,
-0.06754403561353683,
0.04668955132365227,
0.0075838021002709866,
0.20575450360774994,
0.003039497649297118,
-0.042370088398456573,
0.039748575538396835,
0.0662311539053917,
0.06555569171905518,
0.03981770575046539,
0.28081172704696655,
0.0802650898694992,
-0.07460470497608185,
-0.13494586944580078,
0.0485360212624073,
0.046235259622335434,
0.029557714238762856,
0.13590764999389648,
0.08520226180553436,
-0.13411486148834229,
0.05488928034901619,
-0.024247972294688225,
-0.017794432118535042,
-0.06631845980882645,
-0.10699623078107834,
-0.0047538564540445805,
-0.025230513885617256,
0.002481818664819002,
0.114695243537426,
0.16734540462493896,
-0.0073227244429290295,
0.015934448689222336,
-0.04293256625533104,
-0.05326288193464279,
-0.1689361333847046,
-0.072625532746315,
-0.13864682614803314,
-0.129708394408226,
-0.0928451344370842,
-0.2000843733549118,
0.01582498289644718,
0.05145108327269554,
0.08772397041320801,
-0.010016297921538353,
0.14400726556777954,
-0.027292773127555847,
-0.07456684857606888,
0.016051288694143295,
0.0057939188554883,
0.10160282254219055,
-0.06599051505327225,
-0.031746331602334976,
-0.0015732160536572337,
0.026125837117433548,
0.0005924100405536592,
0.006416932214051485,
0.024766186252236366,
0.033577896654605865,
-0.13449832797050476,
-0.08325579762458801,
-0.03488584980368614,
0.01483186800032854,
-0.07455159723758698,
0.07172423601150513,
0.029284467920660973,
-0.06025530397891998,
0.011652710847556591,
0.22296033799648285,
-0.04099354147911072,
-0.04205095022916794,
-0.0491325818002224,
0.1431376188993454,
0.013043197803199291,
0.14323683083057404,
-0.045950282365083694,
0.005504986271262169,
-0.04108504205942154,
0.31321197748184204,
0.1911860555410385,
-0.07389027625322342,
-0.014921490103006363,
0.020959896966814995,
0.014154504984617233,
0.1336037516593933,
0.09419597685337067,
0.06310434639453888,
0.1728450506925583,
-0.02800457552075386,
-0.0387079231441021,
-0.015062631107866764,
0.024185901507735252,
-0.16864646971225739,
0.05643533915281296,
0.0630074068903923,
-0.038718726485967636,
0.020069018006324768,
0.0619329996407032,
-0.06862027198076248,
0.07890579849481583,
-0.13260267674922943,
-0.09726671874523163,
-0.04446971416473389,
-0.025418763980269432,
0.1095169186592102,
-0.0322517529129982,
0.0003065321652684361,
0.0011225031921640038,
-0.034852419048547745,
0.0632987916469574,
0.041411470621824265,
-0.12998047471046448,
0.06833993643522263,
0.02614804543554783,
-0.16916856169700623,
0.012206343933939934,
-0.02609281986951828,
0.02521849051117897,
0.10159897804260254,
-0.06431502103805542,
-0.0876796543598175,
0.07788443565368652,
-0.004119726829230785,
0.018688099458813667,
0.14220930635929108,
0.08765041083097458,
0.0340752974152565,
0.008542897179722786,
0.055127814412117004,
-0.13897959887981415,
-0.00254090060479939,
0.02777745947241783,
-0.025864170864224434,
0.014657469466328621,
-0.01740412414073944,
-0.0517248697578907,
0.0460195317864418,
0.0857410803437233,
-0.04165021330118179,
0.0535876527428627,
-0.04112762212753296,
-0.003111255820840597,
0.0035762430634349585,
-0.0064169662073254585,
-0.008705935440957546,
-0.20004746317863464,
-0.07915439456701279,
0.10336056351661682,
-0.00002780115210043732,
-0.3110036849975586,
-0.02203570492565632,
-0.09464550018310547,
0.03980084881186485,
-0.21730142831802368,
0.04751552641391754,
0.1823977679014206,
0.007852518931031227,
-0.05885200574994087,
-0.052447542548179626,
0.04310980439186096,
0.12024915963411331,
-0.09387893974781036,
-0.09959100931882858
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# G-SciEdBERT-scoring
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
### Training results
### Framework versions
- Transformers 4.37.2
- TensorFlow 2.10.1
- Datasets 2.14.5
- Tokenizers 0.15.1
| {"tags": ["generated_from_keras_callback"], "model-index": [{"name": "G-SciEdBERT-scoring", "results": []}]} | text-classification | ai4stem-uga/G-SciEdBERT-scoring | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T06:17:31+00:00 | [] | [] | TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us
|
# G-SciEdBERT-scoring
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
### Training results
### Framework versions
- Transformers 4.37.2
- TensorFlow 2.10.1
- Datasets 2.14.5
- Tokenizers 0.15.1
| [
"# G-SciEdBERT-scoring\n\nThis model was trained from scratch on an unknown dataset.\nIt achieves the following results on the evaluation set:",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- optimizer: None\n- training_precision: float32",
"### Training results",
"### Framework versions\n\n- Transformers 4.37.2\n- TensorFlow 2.10.1\n- Datasets 2.14.5\n- Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us \n",
"# G-SciEdBERT-scoring\n\nThis model was trained from scratch on an unknown dataset.\nIt achieves the following results on the evaluation set:",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- optimizer: None\n- training_precision: float32",
"### Training results",
"### Framework versions\n\n- Transformers 4.37.2\n- TensorFlow 2.10.1\n- Datasets 2.14.5\n- Tokenizers 0.15.1"
] | [
46,
37,
6,
12,
8,
3,
33,
4,
31
] | [
"passage: TAGS\n#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us \n# G-SciEdBERT-scoring\n\nThis model was trained from scratch on an unknown dataset.\nIt achieves the following results on the evaluation set:## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- optimizer: None\n- training_precision: float32### Training results### Framework versions\n\n- Transformers 4.37.2\n- TensorFlow 2.10.1\n- Datasets 2.14.5\n- Tokenizers 0.15.1"
] | [
-0.07834771275520325,
0.04819140210747719,
-0.00027181708719581366,
0.08430669456720352,
0.1819837987422943,
0.0199588630348444,
0.10367203503847122,
0.10089447349309921,
-0.1053101196885109,
0.005434804130345583,
0.0874173566699028,
0.10025946795940399,
0.019185420125722885,
0.12216772884130478,
-0.05519550293684006,
-0.24582286179065704,
0.026775535196065903,
0.02429940551519394,
-0.10329534858465195,
0.0888972133398056,
0.1037890687584877,
-0.10045293718576431,
0.09541040658950806,
-0.015040777623653412,
-0.23860803246498108,
0.020853830501437187,
0.04234407842159271,
-0.07926897704601288,
0.11183204501867294,
0.04813489690423012,
0.09049557149410248,
0.04344908148050308,
0.09502386301755905,
-0.088936947286129,
0.01538336742669344,
0.0678074061870575,
0.002839825814589858,
0.08033765107393265,
0.05028921738266945,
-0.00881398469209671,
0.10622987151145935,
-0.05286603420972824,
0.07357119768857956,
0.05044931545853615,
-0.11938086897134781,
-0.12245836853981018,
-0.06035038083791733,
0.011837156489491463,
0.054812535643577576,
0.0825626403093338,
-0.013666287995874882,
0.20481398701667786,
-0.09245608747005463,
0.08494513481855392,
0.12125649303197861,
-0.32052209973335266,
-0.06729955226182938,
0.09182402491569519,
0.034143704921007156,
0.0254135113209486,
-0.10575305670499802,
0.06190810352563858,
0.061932239681482315,
0.02957315742969513,
0.09715564548969269,
-0.02810489386320114,
-0.14747890830039978,
0.03032270446419716,
-0.1135350689291954,
0.037196703255176544,
0.18629199266433716,
0.008525295183062553,
-0.0702868178486824,
-0.0627938061952591,
-0.04892275109887123,
-0.09053482860326767,
-0.00788925215601921,
-0.07884904742240906,
0.037185247987508774,
-0.006268472410738468,
-0.10003071278333664,
-0.07074321806430817,
-0.1078934520483017,
-0.09805131703615189,
-0.08900121599435806,
0.1599503755569458,
0.00017167023906949908,
0.02913987636566162,
-0.07780641317367554,
0.1330394595861435,
-0.06207726523280144,
-0.1066356748342514,
-0.025189803913235664,
-0.02090620994567871,
-0.1034054234623909,
-0.09280399978160858,
-0.07627306133508682,
-0.16797371208667755,
0.003839273704215884,
0.11470147967338562,
0.013411487452685833,
0.07192938774824142,
-0.04363614693284035,
0.00784850399941206,
-0.01711607538163662,
0.17759419977664948,
-0.06177433207631111,
0.009554080665111542,
0.013228586874902248,
-0.02868698164820671,
-0.03799106180667877,
-0.044583700597286224,
-0.11996468901634216,
-0.005748034920543432,
0.06872619688510895,
0.031242189928889275,
-0.08714614808559418,
0.10682207345962524,
-0.028370395302772522,
-0.02661348320543766,
-0.03349350765347481,
-0.08960825204849243,
0.025793936103582382,
-0.022616170346736908,
-0.07924284785985947,
0.010533599182963371,
0.07335358113050461,
-0.00817833375185728,
-0.0291323009878397,
0.05940670892596245,
-0.10948669910430908,
0.001998285297304392,
-0.07385433465242386,
-0.08377698063850403,
0.00011406106204958633,
-0.09934668987989426,
0.01360550057142973,
-0.08392129093408585,
-0.18037725985050201,
-0.008266035467386246,
0.05400163307785988,
-0.07455364614725113,
0.027380002662539482,
-0.06866854429244995,
-0.0613173209130764,
0.04427994415163994,
0.006996356416493654,
0.10548857599496841,
-0.024581313133239746,
0.04482987895607948,
0.037797681987285614,
0.046239085495471954,
-0.060823678970336914,
0.030492380261421204,
-0.1113642081618309,
0.004349891096353531,
-0.15307623147964478,
0.1034305989742279,
-0.06540613621473312,
0.06955670565366745,
-0.09994851052761078,
-0.06651663035154343,
-0.005564597435295582,
0.0036623484920710325,
0.06531380861997604,
0.1731380820274353,
-0.1786777824163437,
-0.03540968894958496,
0.17382033169269562,
-0.10044689476490021,
-0.08886615931987762,
0.0826447531580925,
-0.07798287272453308,
0.1148805245757103,
0.09316322952508926,
0.15548712015151978,
0.03449495509266853,
-0.09069410711526871,
0.04062343388795853,
0.04121909290552139,
-0.016860758885741234,
0.023672696202993393,
0.02568790502846241,
0.0021754391491413116,
-0.09437553584575653,
0.04382031038403511,
-0.046631380915641785,
0.034286245703697205,
-0.10005468130111694,
-0.06480682641267776,
-0.059654463082551956,
-0.09334302693605423,
0.09920700639486313,
0.012501186691224575,
0.12808024883270264,
-0.04081549495458603,
-0.11124558001756668,
0.1167239099740982,
0.0507594533264637,
-0.06139204278588295,
0.0018961980240419507,
-0.11715512722730637,
0.015094460919499397,
-0.07341491430997849,
0.0005152502562850714,
-0.1840362548828125,
-0.10091689974069595,
0.01653655245900154,
0.07574698328971863,
0.07593122124671936,
0.04642961919307709,
0.09327343106269836,
0.05362372100353241,
-0.06245187297463417,
0.019632115960121155,
0.005280466750264168,
0.02497672848403454,
-0.10678951442241669,
-0.17311885952949524,
-0.017808182165026665,
-0.054309237748384476,
0.09892483055591583,
-0.25427308678627014,
0.013907603919506073,
0.08628770709037781,
0.11940260976552963,
0.04396212473511696,
-0.03888910636305809,
-0.008006391115486622,
0.010639404878020287,
-0.030552420765161514,
-0.08897174149751663,
0.036277785897254944,
0.028053943067789078,
-0.16127713024616241,
-0.010348407551646233,
-0.13220226764678955,
0.1306181252002716,
0.10407751053571701,
-0.08067769557237625,
-0.1284753978252411,
0.023618487641215324,
-0.03453318774700165,
-0.03116663545370102,
-0.03398643061518669,
0.014421124942600727,
0.17247548699378967,
-0.023036621510982513,
0.1587807685136795,
-0.0363919660449028,
-0.05596790835261345,
0.03571363538503647,
-0.009860878810286522,
-0.0006970131653361022,
0.06495687365531921,
0.003240371122956276,
-0.19390986859798431,
0.10177654772996902,
0.044241223484277725,
-0.03154846280813217,
0.17645831406116486,
-0.0388479083776474,
-0.06363431364297867,
-0.05597507208585739,
-0.022937195375561714,
0.017667589709162712,
0.11025173217058182,
-0.1798175573348999,
-0.04236673563718796,
0.012599444948136806,
0.04214188829064369,
0.034871507436037064,
-0.15962272882461548,
-0.017394252121448517,
0.03305947408080101,
-0.005923491436988115,
-0.008538913913071156,
0.018145717680454254,
-0.03352578729391098,
0.10527309030294418,
0.03190946206450462,
-0.0004800762690138072,
0.09114686399698257,
0.00038486329140141606,
-0.10184935480356216,
0.22856931388378143,
-0.10102490335702896,
-0.10785756260156631,
-0.10759195685386658,
-0.00879399199038744,
-0.06629710644483566,
0.03765757009387016,
0.018265249207615852,
-0.11015143245458603,
-0.05106028541922569,
-0.05164267495274544,
-0.0003894052351824939,
-0.07917943596839905,
0.040600113570690155,
-0.015047114342451096,
-0.014119845815002918,
0.07795613259077072,
-0.11475294828414917,
-0.013050297275185585,
-0.028516197577118874,
-0.10962724685668945,
0.02015015296638012,
-0.011321760714054108,
0.0864957645535469,
0.15941008925437927,
-0.04868438467383385,
0.051242683082818985,
-0.04621277004480362,
0.21378101408481598,
-0.09398888051509857,
-0.01963023655116558,
0.057242851704359055,
-0.03831817954778671,
0.0011770828859880567,
0.053272753953933716,
0.048138175159692764,
-0.12029817700386047,
0.0488562136888504,
0.025768211111426353,
-0.06615617871284485,
-0.22481220960617065,
-0.04334329813718796,
-0.03794408589601517,
-0.044709932059049606,
0.04393187165260315,
0.05828263983130455,
0.11621752381324768,
0.07667761296033859,
0.06482292711734772,
0.10357069969177246,
-0.016584910452365875,
0.06791868060827255,
0.07397767901420593,
0.04948367550969124,
0.10341623425483704,
-0.05706876888871193,
-0.0520133301615715,
0.061449937522411346,
-0.04505389556288719,
0.22880899906158447,
0.031730640679597855,
0.08515854179859161,
0.03436274826526642,
0.08244603872299194,
0.01076752133667469,
0.09525631368160248,
0.04577472433447838,
-0.05685824900865555,
0.010153403505682945,
-0.06869271397590637,
-0.022314561530947685,
0.028980892151594162,
-0.07913361489772797,
0.004169143736362457,
-0.12874531745910645,
-0.011346007697284222,
0.042991992086172104,
0.21504734456539154,
0.03244679793715477,
-0.30887478590011597,
-0.11443498730659485,
0.0006034995312802494,
-0.02671944908797741,
-0.06372474879026413,
0.007491155993193388,
0.09819076210260391,
-0.10751812160015106,
0.05976737290620804,
-0.07205267995595932,
0.08692991733551025,
-0.00936151947826147,
0.03279867023229599,
0.03212148696184158,
0.05993529036641121,
-0.020087219774723053,
0.0947808027267456,
-0.27572107315063477,
0.24534256756305695,
0.027395235374569893,
0.1240214854478836,
-0.08795418590307236,
-0.0026910940650850534,
0.0311944130808115,
0.1324487030506134,
0.16226060688495636,
-0.016659021377563477,
-0.08198604732751846,
-0.17571012675762177,
-0.01092176791280508,
0.016005799174308777,
0.12107125669717789,
-0.035042982548475266,
0.0893184021115303,
-0.03286164626479149,
-0.0011906442232429981,
0.07575655728578568,
-0.01224125362932682,
-0.1612151712179184,
-0.0978618636727333,
0.03298042714595795,
-0.0021176438312977552,
-0.01621292531490326,
-0.05264372378587723,
-0.08571840077638626,
-0.028595825657248497,
0.2049439251422882,
-0.03505253046751022,
-0.0355243906378746,
-0.1686990112066269,
0.10478466004133224,
0.0672110766172409,
-0.030303509905934334,
0.019245969131588936,
0.017231374979019165,
0.09406089782714844,
0.06861434876918793,
-0.14220906794071198,
0.12393949180841446,
-0.06481672078371048,
-0.14517109096050262,
-0.042028166353702545,
0.07121666520833969,
0.10585599392652512,
0.035931531339883804,
0.024573197588324547,
0.017397241666913033,
0.03731527179479599,
-0.1101747527718544,
0.03730952367186546,
0.01125136949121952,
0.016528241336345673,
0.045663982629776,
-0.04310854151844978,
0.006115517113357782,
-0.010665146633982658,
0.004125416744500399,
0.1330072432756424,
0.15846747159957886,
-0.09382518380880356,
0.08967459201812744,
0.056319709867239,
-0.11965551972389221,
-0.23790611326694489,
0.12385271489620209,
0.026250196620821953,
0.03678605705499649,
0.02696310169994831,
-0.1927907019853592,
0.14919541776180267,
0.03659610077738762,
-0.022421566769480705,
0.03958893567323685,
-0.2419668287038803,
-0.13284452259540558,
0.12074489146471024,
0.09183505177497864,
0.1718173623085022,
-0.13469600677490234,
-0.05000357702374458,
-0.0433042012155056,
-0.07106929272413254,
0.16924799978733063,
-0.17136768996715546,
0.10518946498632431,
0.006135663017630577,
0.05936390534043312,
0.03971398249268532,
-0.034882597625255585,
0.10854318737983704,
0.030567290261387825,
0.11181776970624924,
-0.07668381929397583,
-0.0253947414457798,
0.16905048489570618,
-0.02537839487195015,
0.06364254653453827,
0.01406052801758051,
0.05128129944205284,
-0.08634206652641296,
-0.03678746521472931,
-0.060135964304208755,
0.07738450169563293,
-0.012825073674321175,
-0.07729525119066238,
-0.04801002889871597,
0.03136000037193298,
0.04529492184519768,
-0.03870144486427307,
0.0824466124176979,
-0.0193820558488369,
0.15587764978408813,
0.11493439227342606,
0.1851556897163391,
-0.03160655125975609,
-0.015458581037819386,
0.04195709154009819,
-0.03317796811461449,
0.0822768583893776,
-0.13666409254074097,
0.04744590446352959,
0.12474310398101807,
0.027922168374061584,
0.12395618855953217,
0.1074950322508812,
-0.04422483220696449,
0.01492380816489458,
0.05172469839453697,
-0.15198752284049988,
-0.1256566196680069,
-0.06017529219388962,
-0.08177978545427322,
-0.04185062274336815,
0.09143953025341034,
0.14433276653289795,
-0.08116142451763153,
0.010928435251116753,
-0.0034025839995592833,
-0.03507911413908005,
-0.08983343094587326,
0.18664288520812988,
0.03539562597870827,
0.045591410249471664,
-0.09640272706747055,
0.13036440312862396,
0.04329725727438927,
-0.06938933581113815,
0.07653734087944031,
0.03889862820506096,
-0.11680764704942703,
-0.048432864248752594,
0.04456300660967827,
0.22418920695781708,
-0.08795095980167389,
-0.04033516347408295,
-0.10146167874336243,
-0.09009469300508499,
0.02106115035712719,
0.19780997931957245,
0.07045941054821014,
0.0662643313407898,
-0.08177532255649567,
0.05162221938371658,
-0.13513082265853882,
0.035002484917640686,
0.05035915970802307,
0.05317032337188721,
-0.15964071452617645,
0.1731896698474884,
-0.03340744972229004,
0.0614248551428318,
-0.08850385993719101,
-0.014817232266068459,
-0.14239048957824707,
-0.0018455397803336382,
-0.1286724954843521,
-0.017423486337065697,
-0.006489693187177181,
-0.017770305275917053,
0.02711893804371357,
-0.04805456101894379,
-0.030458960682153702,
0.03563519939780235,
-0.09228262305259705,
0.007977393455803394,
0.04436244070529938,
0.016407538205385208,
-0.08812747895717621,
-0.018350357189774513,
-0.005193636287003756,
-0.06422749161720276,
0.08354029059410095,
0.08925057202577591,
-0.004815557971596718,
0.08231007307767868,
-0.18880489468574524,
-0.0037659937515854836,
0.024300219491124153,
-0.020625412464141846,
0.06026558578014374,
-0.013516463339328766,
0.00031674609635956585,
-0.013253405690193176,
0.07941053062677383,
0.03818570822477341,
0.07571214437484741,
-0.09501311182975769,
-0.07367169857025146,
-0.03181669861078262,
-0.012222060933709145,
-0.07057952135801315,
0.06065870821475983,
0.10335094481706619,
0.03792349994182587,
0.11038172990083694,
-0.1002994030714035,
0.02037963829934597,
-0.1425037980079651,
-0.016452347859740257,
0.011503858491778374,
-0.08124168962240219,
-0.07308913767337799,
-0.0656295120716095,
0.08393868803977966,
-0.06020243838429451,
0.15910668671131134,
0.014213685877621174,
0.11416859179735184,
0.040475111454725266,
-0.010577281937003136,
0.01303539052605629,
0.03915725275874138,
0.23950839042663574,
0.06419099122285843,
-0.02369125932455063,
0.017680123448371887,
0.06022987887263298,
0.043476033955812454,
0.03451194614171982,
0.17603205144405365,
0.030997557565569878,
-0.133978471159935,
0.10951836407184601,
0.015110054984688759,
-0.06405111402273178,
-0.16574877500534058,
0.04101577028632164,
-0.06356164813041687,
0.11532533168792725,
-0.08883555978536606,
0.05212938040494919,
0.06522593647241592,
-0.10677049309015274,
0.05408709868788719,
-0.06379308551549911,
-0.09979057312011719,
-0.14108866453170776,
-0.12451282143592834,
-0.08258537948131561,
-0.12596498429775238,
0.022951968014240265,
-0.09685446321964264,
0.02427826263010502,
0.04049546644091606,
0.034032709896564484,
-0.02353612519800663,
0.2180798351764679,
-0.07346517592668533,
0.021788958460092545,
0.11942224204540253,
-0.027797719463706017,
-0.03647708147764206,
-0.06569813191890717,
-0.0019341956358402967,
0.011029757559299469,
0.0064622266218066216,
0.021543027833104134,
-0.03994981199502945,
0.0028632350731641054,
0.01869741454720497,
0.0019485976081341505,
-0.09009449183940887,
0.014141724444925785,
0.0497153140604496,
0.008121483959257603,
-0.009625330567359924,
0.01408363413065672,
-0.03333909064531326,
-0.039116572588682175,
0.25297999382019043,
-0.11241606622934341,
-0.012881477363407612,
-0.13758738338947296,
0.26679709553718567,
0.030777519568800926,
0.03668743744492531,
0.027178630232810974,
-0.10065130144357681,
0.006728450767695904,
0.23494650423526764,
0.1811404526233673,
-0.04655873030424118,
-0.000792529433965683,
0.01414178404957056,
-0.010250371880829334,
-0.017864318564534187,
0.1474720537662506,
0.00876045972108841,
0.06517303735017776,
-0.07505211979150772,
-0.00504329614341259,
0.015622884035110474,
-0.04869617149233818,
-0.010416308417916298,
0.0899432897567749,
0.040787991136312485,
0.028577178716659546,
-0.04980362951755524,
0.07628554850816727,
-0.09227999299764633,
-0.15553772449493408,
0.06420526653528214,
-0.13837310671806335,
-0.12183422595262527,
-0.043769825249910355,
-0.02080381289124489,
-0.010003446601331234,
0.07947097718715668,
-0.02832343615591526,
0.005311454180628061,
0.10272910445928574,
0.01156593021005392,
-0.09387560933828354,
-0.04815589264035225,
0.08807279914617538,
-0.049393050372600555,
0.204961895942688,
-0.022986015304923058,
0.06528723239898682,
0.09830567985773087,
0.017674390226602554,
-0.09717109054327011,
0.04508619382977486,
-0.0004981725360266864,
-0.06926781684160233,
0.032461341470479965,
0.16463953256607056,
-0.030192112550139427,
0.05534861981868744,
-0.015526609495282173,
-0.1968526691198349,
0.02892271988093853,
-0.04009373113512993,
-0.04941180348396301,
-0.07083983719348907,
-0.026360634714365005,
-0.07093513011932373,
0.14404644072055817,
0.19345970451831818,
-0.024845024570822716,
0.022831661626696587,
-0.07294553518295288,
0.06157947704195976,
0.05307752639055252,
0.02708045020699501,
-0.04062379524111748,
-0.20040571689605713,
0.010760956443846226,
0.08071906864643097,
-0.005740154534578323,
-0.2676125764846802,
-0.05980009585618973,
0.007303819991648197,
-0.024287324398756027,
-0.05689355358481407,
0.08852949738502502,
0.1310121864080429,
0.04463832080364227,
-0.05664975568652153,
-0.11740267276763916,
-0.03332849591970444,
0.11328955739736557,
-0.132655531167984,
-0.06996845453977585
] |
null | null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
### Framework versions
- PEFT 0.4.0
- PEFT 0.4.0
- PEFT 0.4.0
- PEFT 0.4.0
- PEFT 0.4.0
| {"library_name": "peft"} | null | mahiatlinux/llama-2-7b-mahi_second | [
"peft",
"region:us"
] | 2024-02-11T06:26:40+00:00 | [] | [] | TAGS
#peft #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
### Framework versions
- PEFT 0.4.0
- PEFT 0.4.0
- PEFT 0.4.0
- PEFT 0.4.0
- PEFT 0.4.0
| [
"## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16",
"### Framework versions\n\n- PEFT 0.4.0\n- PEFT 0.4.0\n- PEFT 0.4.0\n- PEFT 0.4.0\n\n- PEFT 0.4.0"
] | [
"TAGS\n#peft #region-us \n",
"## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16",
"### Framework versions\n\n- PEFT 0.4.0\n- PEFT 0.4.0\n- PEFT 0.4.0\n- PEFT 0.4.0\n\n- PEFT 0.4.0"
] | [
9,
758,
35
] | [
"passage: TAGS\n#peft #region-us \n"
] | [
0.00829260516911745,
-0.026935266330838203,
-0.01106757577508688,
-0.027619877830147743,
0.0965428501367569,
0.02783246710896492,
0.03047206811606884,
0.03118034265935421,
0.22223077714443207,
0.032135702669620514,
0.12765143811702728,
0.00717725558206439,
-0.017288388684391975,
0.11208105087280273,
0.011466428637504578,
-0.25448721647262573,
0.06811107695102692,
-0.015424852259457111,
0.11628451943397522,
0.08756431937217712,
-0.06738471239805222,
-0.059713125228881836,
0.025575699284672737,
-0.08529175072908401,
-0.09165651351213455,
0.07663801312446594,
0.03061952441930771,
-0.008632208220660686,
0.11760688573122025,
-0.0012000498827546835,
0.19917184114456177,
-0.04629093408584595,
-0.09375205636024475,
-0.21022845804691315,
0.0316072478890419,
0.00964147225022316,
-0.08034966886043549,
0.05706947669386864,
0.10981794446706772,
-0.05661529302597046,
-0.007360587827861309,
0.11191857606172562,
0.007150724530220032,
0.020916473120450974,
-0.2690832018852234,
-0.14824481308460236,
-0.0661049410700798,
-0.020241467282176018,
0.08685098588466644,
0.03681342676281929,
0.02380278892815113,
0.22160083055496216,
-0.1881285309791565,
0.007108896505087614,
0.17894789576530457,
-0.2612558603286743,
-0.0016630706377327442,
0.06521748751401901,
0.03208031877875328,
0.16238480806350708,
-0.030822664499282837,
0.021785922348499298,
0.07581979036331177,
0.002358650788664818,
-0.15120729804039001,
-0.05934903770685196,
0.03027462586760521,
0.10525340586900711,
-0.11212706565856934,
-0.10374070703983307,
0.2901424467563629,
0.0013309430796653032,
0.025185968726873398,
0.14735907316207886,
-0.11714275181293488,
-0.1520368754863739,
0.04573168605566025,
0.0016394690610468388,
-0.024718135595321655,
0.12631870806217194,
0.24914556741714478,
-0.021238211542367935,
-0.11389974504709244,
0.0007092562736943364,
-0.22574861347675323,
0.19390201568603516,
0.01909891702234745,
0.09692930430173874,
-0.2496342957019806,
0.011947235092520714,
-0.13504475355148315,
0.0431712307035923,
0.05680457875132561,
-0.09950792789459229,
0.014267006888985634,
-0.030159316956996918,
-0.04260031878948212,
0.0707368478178978,
0.01747077889740467,
0.13935965299606323,
-0.13944175839424133,
0.06492915004491806,
-0.029226472601294518,
0.15646184980869293,
0.06880504637956619,
-0.003765254747122526,
0.06834596395492554,
0.09631616622209549,
-0.05287899821996689,
-0.17185020446777344,
-0.015597894787788391,
-0.04981674998998642,
-0.06465140730142593,
0.022935105487704277,
-0.08396808058023453,
0.10104977339506149,
-0.0347571037709713,
-0.10460817068815231,
-0.12190018594264984,
0.05380973964929581,
0.06913042813539505,
-0.03886610269546509,
-0.021800508722662926,
-0.00855002086609602,
0.06382840871810913,
0.14698800444602966,
-0.10721710324287415,
-0.010804299265146255,
0.0322653092443943,
0.1366417557001114,
-0.150248184800148,
0.027735399082303047,
-0.059793729335069656,
0.02573864348232746,
0.06200810894370079,
-0.07201194763183594,
0.01726044900715351,
-0.13068796694278717,
-0.030760297551751137,
-0.00763189559802413,
-0.01945461519062519,
-0.022918682545423508,
0.0898854061961174,
0.05114426463842392,
0.037263479083776474,
-0.05762849003076553,
-0.05124814808368683,
-0.14443525671958923,
-0.07566534727811813,
0.11029656231403351,
-0.07878974080085754,
0.02891438826918602,
-0.19349893927574158,
0.00705341761931777,
-0.08442474901676178,
0.09394831210374832,
-0.08711408823728561,
-0.07006033509969711,
0.0019854933489114046,
0.1587395966053009,
0.01394957210868597,
0.018298063427209854,
-0.28952649235725403,
0.039544519037008286,
-0.057536981999874115,
0.1840665489435196,
-0.05947275832295418,
-0.08931230008602142,
0.24385076761245728,
-0.10980256646871567,
-0.06802994012832642,
0.022471429780125618,
0.05828041210770607,
0.05130564421415329,
0.09229771047830582,
0.3642725348472595,
-0.04805094376206398,
-0.19874176383018494,
0.12475734204053879,
0.1651247888803482,
-0.10511025041341782,
-0.16525547206401825,
0.05144248530268669,
-0.1511985957622528,
-0.2054334431886673,
-0.028335582464933395,
0.09293857216835022,
0.06914662569761276,
-0.07771506905555725,
0.006772434338927269,
0.08606988936662674,
0.02832910791039467,
0.08347801864147186,
0.06389661878347397,
0.10276235640048981,
-0.06257472932338715,
0.08313433080911636,
0.07876557856798172,
-0.011720610782504082,
0.17166002094745636,
0.03117954358458519,
-0.014590014703571796,
0.06963992863893509,
-0.03228304535150528,
0.008311467245221138,
-0.15987969934940338,
-0.12005670368671417,
0.004957701079547405,
0.03634751960635185,
-0.011121698655188084,
0.12703059613704681,
0.08459290117025375,
-0.0853276252746582,
0.03272847831249237,
0.007893308065831661,
0.03293146565556526,
0.018919633701443672,
-0.028205491602420807,
0.00016943708760663867,
0.07418058067560196,
-0.0714426189661026,
-0.09006670862436295,
-0.05272950604557991,
-0.008701427839696407,
0.11057489365339279,
0.008298159576952457,
0.06957186758518219,
-0.02987775206565857,
-0.011285753920674324,
0.07983897626399994,
0.07165726274251938,
0.011737252585589886,
0.10009552538394928,
-0.015359455719590187,
0.054182268679142,
0.08990226686000824,
-0.0750376433134079,
0.2661861777305603,
0.13148777186870575,
-0.15996558964252472,
-0.04043395817279816,
-0.11310134828090668,
-0.0260782353579998,
-0.006012130994349718,
0.02873041480779648,
-0.09233678132295609,
-0.005533296149224043,
0.020608436316251755,
0.02687758021056652,
-0.04589942470192909,
-0.0315130315721035,
-0.035620518028736115,
-0.058723084628582,
-0.06375269591808319,
0.1126568615436554,
0.15871436893939972,
-0.07030481100082397,
0.15888680517673492,
0.3468194007873535,
0.14077147841453552,
0.1848190873861313,
-0.06887716799974442,
-0.06452131271362305,
0.00927924457937479,
0.05708961933851242,
-0.05610193684697151,
0.08892221748828888,
-0.08108772337436676,
-0.0015928051434457302,
0.03017391636967659,
0.05369308218359947,
0.08804487437009811,
-0.14908689260482788,
-0.12161914259195328,
-0.039148274809122086,
0.0168702881783247,
-0.15686431527137756,
0.04514508694410324,
-0.015203705988824368,
0.08026403933763504,
0.057843808084726334,
-0.04610232263803482,
0.09094742685556412,
0.01873389445245266,
-0.07945486158132553,
0.049448199570178986,
-0.17902858555316925,
-0.2450101673603058,
-0.09299172461032867,
-0.07675646990537643,
0.06373251974582672,
0.031029386445879936,
0.010353583842515945,
-0.1523970067501068,
0.02132292650640011,
0.07545062899589539,
0.0683353990316391,
-0.15411785244941711,
-0.015843898057937622,
-0.005877008195966482,
0.04017088562250137,
-0.07700120657682419,
0.02880442887544632,
-0.04029705002903938,
-0.10612481087446213,
0.032415810972452164,
0.09285221993923187,
-0.14453232288360596,
0.08344320952892303,
0.2001073956489563,
0.09364406764507294,
0.0796363353729248,
-0.022973867133259773,
0.18804925680160522,
-0.12029996514320374,
-0.06301040947437286,
0.09529715031385422,
-0.06621665507555008,
0.06777431070804596,
0.14112544059753418,
0.045953571796417236,
-0.14064911007881165,
0.011151605285704136,
-0.01861884817481041,
-0.13180211186408997,
-0.1980912983417511,
-0.08852202445268631,
-0.10357187688350677,
0.10918362438678741,
0.03257594257593155,
0.0786253958940506,
0.05955493822693825,
-0.02552901953458786,
0.09727311134338379,
-0.09487681835889816,
-0.05409891903400421,
-0.020538199692964554,
0.09330572187900543,
-0.0824040099978447,
-0.01151931844651699,
-0.07787874341011047,
-0.05482605844736099,
0.11700834333896637,
0.10372455418109894,
0.09112806618213654,
0.2548113465309143,
-0.03373616561293602,
0.035875946283340454,
0.12922453880310059,
0.1581374853849411,
0.10044097155332565,
0.04114210978150368,
-0.04255961626768112,
-0.023944418877363205,
0.01683424599468708,
-0.03285347670316696,
0.025654492899775505,
0.058934055268764496,
-0.17267832159996033,
0.024415437132120132,
-0.308407723903656,
0.07287555932998657,
0.02747616358101368,
0.08087440580129623,
-0.03113320842385292,
0.08262966573238373,
0.06314362585544586,
0.010024950839579105,
-0.043985314667224884,
0.1674550622701645,
0.0810137540102005,
-0.14478108286857605,
0.002474965061992407,
0.015177430585026741,
0.08888338506221771,
-0.01866341568529606,
0.09102074801921844,
-0.027758795768022537,
-0.13933004438877106,
0.002076496835798025,
0.031217029318213463,
-0.13545332849025726,
0.28288084268569946,
-0.007263700943440199,
-0.14929185807704926,
0.006822332739830017,
-0.08676858991384506,
-0.026593131944537163,
0.12830568850040436,
0.09959052503108978,
0.10081104189157486,
-0.049271173775196075,
-0.173585906624794,
0.0007395088323391974,
-0.012905269861221313,
0.1564965397119522,
-0.058909639716148376,
-0.14299613237380981,
-0.03556034713983536,
0.04823509603738785,
-0.0665925070643425,
0.03212990239262581,
0.04241814464330673,
-0.0378933809697628,
0.006969076115638018,
-0.006106061395257711,
-0.01574663259088993,
-0.00008219365554396063,
0.022644001990556717,
-0.058335646986961365,
-0.0751715824007988,
-0.044738296419382095,
-0.014916549436748028,
-0.0699189156293869,
-0.1830553412437439,
0.04060858115553856,
-0.06704728305339813,
-0.0002293033612659201,
-0.05446185544133186,
-0.14213667809963226,
-0.08581394702196121,
-0.1483146697282791,
0.16092267632484436,
-0.0383053682744503,
0.0977579727768898,
-0.04502404108643532,
0.20595401525497437,
-0.021143488585948944,
0.050595417618751526,
-0.07140254974365234,
0.03826044127345085,
-0.01612120307981968,
-0.08644762635231018,
0.07683910429477692,
-0.1032642126083374,
-0.021387556567788124,
0.10516642034053802,
-0.06223582848906517,
0.1404409110546112,
0.011972825042903423,
-0.027041606605052948,
0.205937922000885,
0.2508213222026825,
-0.005608283448964357,
0.16921362280845642,
0.19194354116916656,
-0.052535828202962875,
-0.25366199016571045,
-0.0531730130314827,
-0.17708808183670044,
-0.07580064982175827,
0.07333262264728546,
-0.2103428691625595,
0.0760616585612297,
0.21146932244300842,
-0.0522623136639595,
0.30628252029418945,
-0.31602466106414795,
0.016635769978165627,
0.13112017512321472,
-0.08368509262800217,
0.5422701239585876,
-0.144570454955101,
-0.1481245458126068,
0.04022558778524399,
-0.056422922760248184,
0.08527152240276337,
-0.039400000125169754,
0.00814841315150261,
0.021984079852700233,
-0.013534828089177608,
0.029225707054138184,
-0.0013622450642287731,
0.20132501423358917,
0.008832852356135845,
0.07040589302778244,
-0.06480301171541214,
-0.12356729805469513,
-0.062411364167928696,
-0.007833144627511501,
-0.06574476510286331,
0.16907280683517456,
-0.06983361393213272,
-0.17259527742862701,
0.03294156864285469,
-0.10998586565256119,
0.0017724701901897788,
0.06670014560222626,
-0.029522504657506943,
-0.032874319702386856,
-0.011159121990203857,
-0.14588800072669983,
-0.0014189399080350995,
0.2902820110321045,
-0.08497273921966553,
0.23336979746818542,
-0.000846382521558553,
-0.039852045476436615,
-0.1557127833366394,
-0.06918193399906158,
-0.06645924597978592,
-0.03852501139044762,
0.1266971230506897,
-0.11260335892438889,
0.0017314421711489558,
0.13847580552101135,
-0.015466325916349888,
0.05389922112226486,
0.06789152324199677,
-0.06536387652158737,
-0.022217418998479843,
0.14733831584453583,
-0.20408794283866882,
-0.12759141623973846,
-0.016380267217755318,
-0.018695104867219925,
0.13023988902568817,
0.01401706226170063,
0.07111828774213791,
0.1108362004160881,
0.0016200152458623052,
0.005015705246478319,
-0.008825467899441719,
-0.09497229754924774,
-0.020427772775292397,
0.0611126609146595,
-0.01232164166867733,
-0.09508147835731506,
0.12282982468605042,
0.059093255549669266,
-0.09734825044870377,
-0.05543386563658714,
0.2114614099264145,
-0.06207782030105591,
-0.0606360100209713,
-0.16070382297039032,
0.00968100130558014,
-0.03725052624940872,
-0.05321822687983513,
0.07973311841487885,
-0.052437908947467804,
0.05387916788458824,
0.1852327436208725,
0.04607284814119339,
0.08534316718578339,
0.05448426306247711,
-0.01852402649819851,
0.1301620453596115,
-0.1306999772787094,
-0.13062024116516113,
-0.015015154145658016,
-0.10089939087629318,
-0.10982528328895569,
0.007273608818650246,
0.12842686474323273,
-0.10152924805879593,
-0.1258324235677719,
-0.257371187210083,
0.09852533042430878,
-0.017329968512058258,
-0.10722918063402176,
-0.03702899068593979,
-0.0658356100320816,
0.040652837604284286,
-0.0182231105864048,
-0.02768743224442005,
-0.06613078713417053,
-0.16006122529506683,
0.09499682486057281,
0.05953313782811165,
0.046302679926157,
0.003658809931948781,
0.026994813233613968,
0.16134272515773773,
0.005131650250405073,
0.11230210214853287,
0.13897082209587097,
-0.012235188856720924,
0.18027588725090027,
-0.09917288273572922,
-0.034192267805337906,
0.15557342767715454,
-0.04288337007164955,
0.052826203405857086,
0.1662796288728714,
-0.051153991371393204,
-0.001299053430557251,
-0.007751125376671553,
0.09939704835414886,
-0.08498828858137131,
-0.10974106192588806,
0.035984911024570465,
0.004012351855635643,
-0.2354188710451126,
0.015330861322581768,
-0.19873663783073425,
0.12415129691362381,
0.031077899038791656,
0.018696846440434456,
0.06764515489339828,
0.09559421241283417,
0.01503404974937439,
0.0023713710252195597,
0.03050381690263748,
-0.09884880483150482,
0.04988659918308258,
-0.038695331662893295,
-0.010782679542899132,
0.05231096222996712,
0.2843349575996399,
-0.032793767750263214,
-0.020284075289964676,
0.020962122827768326,
0.11809604614973068,
-0.09135638177394867,
0.004603485111147165,
0.09645374864339828,
0.11472562700510025,
-0.07509025931358337,
-0.13589471578598022,
0.06244692578911781,
-0.06262598931789398,
-0.04540418088436127,
0.13919715583324432,
0.0902591198682785,
0.046293873339891434,
0.05272626131772995,
-0.02729443646967411,
-0.012299901805818081,
0.05238562449812889,
-0.15789471566677094,
0.02873970754444599,
-0.006949977017939091,
0.021044231951236725,
0.05127276852726936,
0.15367241203784943,
-0.0059141069650650024,
0.03925706446170807,
-0.05582598224282265,
0.01290066447108984,
-0.16246458888053894,
0.008943650871515274,
0.0501304492354393,
-0.13316206634044647,
0.013923092745244503,
-0.01026194728910923,
-0.029845893383026123,
0.2977370023727417,
0.026909615844488144,
0.009371691383421421,
0.12506797909736633,
-0.05069588124752045,
-0.14437833428382874,
0.0023494025226682425,
-0.0027437321841716766,
0.08414654433727264,
-0.13498073816299438,
-0.12035559117794037,
-0.06427259743213654,
-0.12377031147480011,
-0.08804898709058762,
0.03418029844760895,
-0.03585980832576752,
-0.08116903901100159,
-0.19007793068885803,
-0.05796924978494644,
-0.045107997953891754,
0.12881684303283691,
-0.1519797146320343,
0.141686350107193,
0.004668145906180143,
-0.003297630464658141,
0.013269239105284214,
0.13215011358261108,
-0.02982436865568161,
0.10925976932048798,
-0.043058983981609344,
0.2270074039697647,
-0.04200804978609085,
0.16145536303520203,
-0.09930017590522766,
0.005837715696543455,
-0.07202742248773575,
0.22990146279335022,
0.20259147882461548,
-0.07689560204744339,
0.004187891259789467,
0.0034347253385931253,
0.06765202432870865,
0.13084819912910461,
0.17336603999137878,
0.0631483867764473,
0.2597523331642151,
-0.03041158802807331,
0.05720274895429611,
0.0000468307662231382,
0.048570189625024796,
-0.06707733124494553,
-0.005741513334214687,
0.09754728525876999,
-0.020207606256008148,
-0.12468520551919937,
0.17555703222751617,
-0.18990550935268402,
0.17376936972141266,
0.08260717988014221,
-0.18442249298095703,
-0.05021568387746811,
-0.02310987189412117,
0.07841615378856659,
-0.05810707435011864,
0.1467532515525818,
-0.07218137383460999,
-0.16537104547023773,
-0.06027204170823097,
0.036261431872844696,
-0.30707818269729614,
-0.28148940205574036,
0.09261594712734222,
0.05305452644824982,
0.024236129596829414,
-0.016665684059262276,
-0.02278580516576767,
-0.042310554534196854,
0.021507710218429565,
-0.0009697260102257133,
0.019171815365552902,
0.04550950974225998,
0.00007233883661683649,
-0.24296307563781738,
-0.08109838515520096,
0.05802064761519432,
-0.08520670980215073,
0.07397517561912537,
-0.09320686757564545,
-0.05823308229446411,
0.011186439543962479,
-0.014270984567701817,
0.016405176371335983,
0.049730218946933746,
-0.13669061660766602,
0.031289875507354736,
0.05346722900867462,
0.03254113346338272,
-0.013465221039950848,
-0.020642874762415886,
-0.03248709440231323,
0.029590921476483345,
-0.14728154242038727,
-0.13612228631973267,
0.08239741623401642,
-0.0670107901096344,
0.04118546470999718,
-0.045597173273563385,
-0.05633913725614548,
0.04328852519392967,
-0.08406979590654373,
0.13654100894927979,
-0.11017346382141113,
0.029057931154966354,
-0.0010506710968911648,
0.02675064280629158,
0.04119735583662987,
-0.22002533078193665,
0.10693495720624924,
0.015554155223071575,
0.024709243327379227,
-0.01751067489385605
] |
null | null | null |
This model is a finetune of jondurbin's excellent [bagel](https://huggingface.co/jondurbin/bagel-34b-v0.2) model.
It has been trained with new datasets and a new technique, which we will share to the community soon.
This model has not utilised any form of merging.
### Evaluation Results
| Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
| --- | --- | --- | --- | --- | --- | --- |
| 77.29 | 74.23 | 86.76 | 76.66 | 70.22 | 83.66 | 72.18 |
### Contamination Results
With reference model jondurbin/bagel-34b-v0.2:
| ARC | TruthfulQA | GSM8K |
| --- | --- | --- |
| 0.08| 0.38| 0.88| | {"license": "other", "license_name": "yi-license", "license_link": "https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE", "base_model": "jondurbin/bagel-34b-v0.2"} | null | casualjim/abacusai-smaug-34B-v0.1 | [
"gguf",
"base_model:jondurbin/bagel-34b-v0.2",
"license:other",
"region:us"
] | 2024-02-11T06:30:11+00:00 | [] | [] | TAGS
#gguf #base_model-jondurbin/bagel-34b-v0.2 #license-other #region-us
| !image/png
!image/png
This model is a finetune of jondurbin's excellent bagel model.
It has been trained with new datasets and a new technique, which we will share to the community soon.
This model has not utilised any form of merging.
### Evaluation Results
### Contamination Results
With reference model jondurbin/bagel-34b-v0.2:
ARC: 0.08, TruthfulQA: 0.38, GSM8K: 0.88
| [
"### Evaluation Results",
"### Contamination Results\n\n\nWith reference model jondurbin/bagel-34b-v0.2:\n\n\nARC: 0.08, TruthfulQA: 0.38, GSM8K: 0.88"
] | [
"TAGS\n#gguf #base_model-jondurbin/bagel-34b-v0.2 #license-other #region-us \n",
"### Evaluation Results",
"### Contamination Results\n\n\nWith reference model jondurbin/bagel-34b-v0.2:\n\n\nARC: 0.08, TruthfulQA: 0.38, GSM8K: 0.88"
] | [
30,
5,
40
] | [
"passage: TAGS\n#gguf #base_model-jondurbin/bagel-34b-v0.2 #license-other #region-us \n### Evaluation Results### Contamination Results\n\n\nWith reference model jondurbin/bagel-34b-v0.2:\n\n\nARC: 0.08, TruthfulQA: 0.38, GSM8K: 0.88"
] | [
-0.06999551504850388,
0.23366649448871613,
-0.0038884717505425215,
-0.014665031805634499,
-0.030022932216525078,
-0.0001992067409446463,
0.10961528867483139,
0.04431368038058281,
0.07888025790452957,
0.05499354377388954,
0.15735004842281342,
0.10194404423236847,
-0.007440387271344662,
0.12799543142318726,
-0.0420534722507,
0.022791067138314247,
0.09163419902324677,
-0.04677842557430267,
0.02938327193260193,
0.09813564270734787,
0.03864887356758118,
-0.02159223146736622,
0.08716610819101334,
0.018445219844579697,
-0.03435101732611656,
0.11211485415697098,
0.06310420483350754,
-0.054585207253694534,
0.07816963642835617,
0.03521087393164635,
0.02892732061445713,
0.03456014767289162,
-0.0035749070812016726,
-0.11216811835765839,
0.02699965052306652,
-0.06174832582473755,
-0.0955839529633522,
0.0785917341709137,
0.015111701563000679,
-0.04261204972863197,
0.09154122322797775,
0.09440507739782333,
-0.05176638811826706,
0.10213998705148697,
-0.14810191094875336,
-0.1488553136587143,
-0.10474637895822525,
0.10996221005916595,
0.03882594779133797,
0.02902180328965187,
-0.02396232634782791,
0.18814469873905182,
-0.11014461517333984,
0.026234470307826996,
0.16436660289764404,
-0.1839623600244522,
0.03659693896770477,
0.26612260937690735,
-0.08577217161655426,
-0.06165366992354393,
-0.04012134298682213,
0.13468323647975922,
0.11909252405166626,
-0.03378799185156822,
-0.1740427017211914,
-0.004718212876468897,
0.01079622097313404,
0.11067058891057968,
-0.002740008058026433,
-0.063175730407238,
0.21689453721046448,
0.08941853046417236,
-0.10702749341726303,
0.08652981370687485,
-0.04912023991346359,
-0.04427332058548927,
0.029054909944534302,
0.02676505222916603,
-0.005487259943038225,
0.09594281762838364,
-0.014173452742397785,
0.06417965888977051,
-0.06707380712032318,
-0.09134858101606369,
-0.06854388117790222,
0.2119995802640915,
-0.02900775335729122,
0.08089560270309448,
-0.06112414225935936,
0.09642551839351654,
-0.24064037203788757,
-0.12619587779045105,
-0.10083401203155518,
-0.05230475589632988,
0.0922873318195343,
0.04546969383955002,
0.07453455030918121,
0.14993450045585632,
0.21167133748531342,
0.1991206854581833,
-0.039851102977991104,
-0.01200586836785078,
-0.046269919723272324,
0.04974173754453659,
0.011734182946383953,
0.009766088798642159,
-0.11013471335172653,
0.06258916109800339,
0.06682063639163971,
-0.07593581825494766,
0.08986944705247879,
-0.01376301795244217,
-0.058373164385557175,
-0.07232974469661713,
-0.036086779087781906,
0.1017751544713974,
-0.011575627140700817,
-0.05398969724774361,
-0.052048034965991974,
0.03919035568833351,
0.14937008917331696,
0.021969754248857498,
-0.08967794477939606,
0.0689818412065506,
0.019487136974930763,
-0.05341658741235733,
0.03738159313797951,
0.04145025089383125,
0.1571832299232483,
-0.009531551040709019,
-0.14977820217609406,
-0.0704924538731575,
0.008379841223359108,
-0.01178765669465065,
0.019763093441724777,
0.044328223913908005,
0.10559194535017014,
-0.1424776315689087,
-0.10358932614326477,
0.05215355008840561,
-0.008068552240729332,
-0.06961648911237717,
0.01968720741569996,
0.09050997346639633,
-0.04414349049329758,
-0.004120274912565947,
-0.025208594277501106,
-0.014658510684967041,
-0.11962360143661499,
0.07921246439218521,
0.026137355715036392,
-0.010372070595622063,
-0.09782350063323975,
-0.050097666680812836,
-0.09053170680999756,
0.0945078581571579,
-0.02007870376110077,
-0.0976034551858902,
-0.13928137719631195,
0.07892756909132004,
-0.10493060946464539,
-0.020618272945284843,
-0.08742140233516693,
-0.0969657152891159,
0.07006032764911652,
0.19207635521888733,
0.008916305378079414,
-0.060373060405254364,
0.037642620503902435,
-0.05997323989868164,
-0.01989307440817356,
-0.00586794875562191,
-0.008830050937831402,
0.024968694895505905,
0.04213994741439819,
0.11289795488119125,
-0.10792772471904755,
-0.15140604972839355,
-0.06238507479429245,
0.046221476048231125,
-0.022009696811437607,
0.04065771773457527,
0.12836480140686035,
-0.09924239665269852,
-0.1768317073583603,
0.042750950902700424,
0.04095637425780296,
0.11233887076377869,
-0.04862244054675102,
-0.08354620635509491,
-0.035378627479076385,
-0.09583375602960587,
0.11053821444511414,
-0.0741611048579216,
0.03056471236050129,
-0.06529473513364792,
-0.04982250556349754,
-0.16473886370658875,
0.14248041808605194,
0.028037823736667633,
-0.04851503297686577,
-0.09525667130947113,
0.22970913350582123,
-0.2041984647512436,
-0.05886656045913696,
-0.005688507575541735,
-0.00809869822114706,
-0.017352113500237465,
-0.07369966059923172,
-0.00373739842325449,
-0.01878739707171917,
0.0570903979241848,
0.056639090180397034,
-0.00731694558635354,
0.02729841135442257,
-0.08798926323652267,
0.02440536394715309,
0.06007302179932594,
-0.09775448590517044,
0.03583443537354469,
-0.007805257104337215,
0.08823531121015549,
-0.06781522184610367,
-0.0013576343189924955,
0.0881727784872055,
0.030362285673618317,
-0.0206853449344635,
-0.025750184431672096,
0.14018888771533966,
-0.1325342208147049,
-0.05382111296057701,
-0.022218571975827217,
0.004028611350804567,
-0.012570775113999844,
-0.09942158311605453,
0.05349978432059288,
0.06658924371004105,
0.2361879050731659,
0.10517311096191406,
0.08333937078714371,
0.002524907700717449,
0.024143939837813377,
-0.020305998623371124,
0.04052169620990753,
0.013196909800171852,
0.06960144639015198,
0.06492490321397781,
-0.06151328980922699,
-0.011642426252365112,
-0.06024026870727539,
0.03416440263390541,
0.026276282966136932,
-0.0747344121336937,
-0.06558719277381897,
0.13008488714694977,
0.09134508669376373,
-0.1771874874830246,
0.12786158919334412,
0.1366916298866272,
0.04020107164978981,
0.06751212477684021,
0.009476812556385994,
-0.10254660993814468,
-0.048867516219615936,
-0.011066830717027187,
-0.026577778160572052,
0.23091189563274384,
-0.11171260476112366,
0.1334122270345688,
0.06268927454948425,
-0.0459703654050827,
0.07338869571685791,
-0.07838372886180878,
-0.11068075150251389,
-0.025765320286154747,
-0.06821359694004059,
-0.16545961797237396,
0.1214025691151619,
-0.05746874585747719,
0.10036658495664597,
-0.006547830067574978,
-0.0017820352222770452,
0.0013336765114217997,
0.024153074249625206,
-0.11746547371149063,
0.2053391933441162,
-0.006897489074617624,
-0.11191003769636154,
-0.13066373765468597,
-0.01654943823814392,
-0.07948444783687592,
0.03585335984826088,
0.05176921933889389,
-0.1824679672718048,
-0.11335432529449463,
-0.01826084963977337,
-0.02442493475973606,
-0.01101970486342907,
0.028579402714967728,
0.13402599096298218,
0.006260889582335949,
0.038515109568834305,
-0.1163468211889267,
-0.0024667440447956324,
-0.02682979218661785,
-0.008112326264381409,
0.0609746091067791,
-0.06468168646097183,
0.11298538744449615,
0.11285432428121567,
-0.010968544520437717,
0.04342694953083992,
0.06538166850805283,
0.3235664665699005,
-0.02632112428545952,
-0.05633939802646637,
0.21813786029815674,
-0.014429011382162571,
-0.015721391886472702,
0.15066535770893097,
0.051829613745212555,
-0.1074196994304657,
-0.025738930329680443,
-0.04707004129886627,
-0.09406517446041107,
-0.21681618690490723,
-0.03756938874721527,
0.0027291602455079556,
-0.011420827358961105,
-0.07609338313341141,
0.08512265980243683,
0.0993570014834404,
0.1209501400589943,
-0.018488669767975807,
-0.1117948517203331,
-0.03717399761080742,
0.045972853899002075,
0.0057046078145504,
-0.03214038908481598,
0.027217375114560127,
-0.07906404882669449,
-0.012604715302586555,
0.1006903350353241,
0.03072109818458557,
0.04688699543476105,
0.15792767703533173,
0.0032170016784220934,
0.11997389048337936,
0.08212094753980637,
0.1260991245508194,
0.030936699360609055,
-0.006357648875564337,
-0.06061374768614769,
-0.023734673857688904,
-0.07716867327690125,
0.03284524753689766,
0.0831841453909874,
-0.08851820230484009,
0.0329301580786705,
0.10408440977334976,
-0.17480726540088654,
0.052850887179374695,
-0.1976093351840973,
0.21667148172855377,
-0.15954750776290894,
-0.09900791943073273,
0.04900924861431122,
0.09353488683700562,
-0.05982321873307228,
0.010561302304267883,
-0.07734836637973785,
-0.04583750665187836,
0.00296682957559824,
0.0468846894800663,
0.0019635348580777645,
0.14065030217170715,
0.0679474025964737,
-0.10178045183420181,
-0.14357073605060577,
-0.06636077910661697,
0.09669642150402069,
-0.1899619996547699,
0.2355145663022995,
0.05983610823750496,
-0.08550895005464554,
-0.00951728317886591,
-0.06004071980714798,
0.039581913501024246,
0.09968247264623642,
0.15349452197551727,
0.030398759990930557,
-0.04948510602116585,
-0.08887102454900742,
-0.20348884165287018,
0.09635862708091736,
-0.0739695206284523,
-0.019253866747021675,
-0.01575351506471634,
0.0817507728934288,
-0.004341163672506809,
-0.05030380189418793,
0.13702090084552765,
-0.29492583870887756,
0.04492277652025223,
0.07811595499515533,
0.011578371748328209,
0.048289936035871506,
-0.06185121461749077,
-0.06732504069805145,
0.015475291758775711,
0.19319114089012146,
-0.06699948757886887,
-0.09083284437656403,
-0.07609494775533676,
0.032367441803216934,
0.14986370503902435,
-0.0992509052157402,
0.008197738789021969,
-0.0895083099603653,
-0.058174584060907364,
0.035686567425727844,
-0.15512335300445557,
0.08849279582500458,
-0.02004341036081314,
-0.08060584217309952,
-0.02216431498527527,
0.14240762591362,
0.0024344928096979856,
0.07261468470096588,
0.0015871342038735747,
0.028170643374323845,
-0.017591727897524834,
-0.1233208104968071,
0.07759444415569305,
-0.05525581166148186,
0.05428267642855644,
0.08999045193195343,
0.03192239999771118,
-0.09244886785745621,
-0.04708953574299812,
-0.0360521599650383,
0.08021853864192963,
0.3312113881111145,
-0.062260113656520844,
0.06950581073760986,
0.18435876071453094,
-0.016888493672013283,
-0.1229516789317131,
-0.04032251611351967,
-0.12438289821147919,
0.06923525035381317,
-0.006296202074736357,
-0.12419351190328598,
0.029746195301413536,
0.1579761803150177,
-0.11856197565793991,
0.26920127868652344,
-0.1979733556509018,
-0.0976283997297287,
0.23759986460208893,
0.021470816805958748,
0.40850555896759033,
-0.09254784137010574,
-0.05666894093155861,
0.005379409529268742,
-0.3620135486125946,
-0.02863416261970997,
-0.02541433461010456,
0.06151394918560982,
-0.03535846620798111,
0.07318631559610367,
0.05257494002580643,
-0.0807521790266037,
0.2532542645931244,
0.04518653079867363,
0.07305897027254105,
-0.02183043584227562,
-0.17212428152561188,
0.05058733746409416,
0.043570034205913544,
0.09761966019868851,
0.08595436811447144,
0.08120689541101456,
-0.05819343402981758,
-0.03848253935575485,
-0.05978021398186684,
0.07816717773675919,
-0.015739066526293755,
-0.13347403705120087,
-0.11332462728023529,
-0.02087019570171833,
-0.10030839592218399,
-0.014300948940217495,
0.12996923923492432,
-0.09219276905059814,
0.1436706781387329,
0.065333791077137,
-0.07745873928070068,
-0.11907976120710373,
0.001004012767225504,
0.04704158753156662,
-0.0646941289305687,
0.0566379651427269,
-0.25826093554496765,
0.04896654933691025,
0.07300016283988953,
0.045354221016168594,
0.05447585880756378,
0.013114215806126595,
-0.1326880306005478,
0.10495664179325104,
0.11652839183807373,
-0.21414077281951904,
0.18899941444396973,
-0.0737571120262146,
-0.10768697410821915,
0.02497692033648491,
0.08460385352373123,
0.08381374925374985,
0.003894974710419774,
-0.01896444335579872,
0.003057190217077732,
0.025087151676416397,
-0.10108079016208649,
0.10463713109493256,
0.09275315701961517,
-0.010379822924733162,
-0.07880178093910217,
0.06695132702589035,
-0.00919717364013195,
0.1672409623861313,
-0.06685538589954376,
-0.13295932114124298,
-0.053524769842624664,
-0.039563149213790894,
-0.12692435085773468,
0.09750273078680038,
-0.10167495161294937,
-0.01050304714590311,
-0.11447475850582123,
-0.018190132454037666,
-0.023175911977887154,
0.10502889752388,
0.07816095650196075,
0.13256174325942993,
-0.019564740359783173,
-0.13644807040691376,
0.04781411960721016,
-0.00743890181183815,
-0.028845667839050293,
-0.015669293701648712,
-0.09229457378387451,
-0.05640413984656334,
-0.02686816081404686,
0.0770743191242218,
-0.06578949093818665,
-0.012957187369465828,
-0.13375736773014069,
0.01441845390945673,
-0.17059355974197388,
0.027461381629109383,
-0.0380304791033268,
-0.02376672811806202,
-0.017418596893548965,
-0.12816016376018524,
-0.10770772397518158,
0.06593897938728333,
-0.10914255678653717,
0.05124427750706673,
0.01755913347005844,
0.08961652219295502,
-0.0595075786113739,
0.016752850264310837,
0.10696560144424438,
0.031131695955991745,
0.07687737792730331,
0.12033192068338394,
0.06204129382967949,
0.10027597099542618,
-0.21958328783512115,
-0.032030489295721054,
0.09288202226161957,
-0.055801648646593094,
-0.0009470353834331036,
-0.1150490790605545,
0.04340356960892677,
0.007103977259248495,
-0.0453525185585022,
0.03846840187907219,
0.060174282640218735,
-0.06325746327638626,
-0.21774861216545105,
-0.04081137478351593,
-0.07417741417884827,
0.07660376280546188,
-0.09474615007638931,
0.12078329175710678,
0.023872779682278633,
-0.011525945737957954,
0.031236935406923294,
-0.02906477078795433,
-0.09278513491153717,
-0.00032988228485919535,
-0.06273453682661057,
-0.06581516563892365,
-0.18782082200050354,
-0.003696002531796694,
-0.03170217573642731,
-0.0004944712272845209,
0.2551056742668152,
-0.10804127156734467,
-0.09579849243164062,
-0.026619764044880867,
0.10483776032924652,
0.24950507283210754,
-0.02924424782395363,
0.24554875493049622,
0.04501963406801224,
0.06121288239955902,
-0.025841403752565384,
0.05551639571785927,
-0.015511254779994488,
-0.1825152188539505,
0.040047209709882736,
0.048867497593164444,
0.020755767822265625,
0.02245936542749405,
-0.015061247162520885,
-0.17370396852493286,
0.11154960840940475,
-0.03540293499827385,
-0.018768707290291786,
-0.05290624871850014,
0.06882639974355698,
0.017904888838529587,
0.24909432232379913,
-0.10495315492153168,
-0.0037093465216457844,
0.013108794577419758,
0.021278174594044685,
-0.17264431715011597,
-0.09768927097320557,
-0.07241321355104446,
-0.0865049734711647,
0.12988537549972534,
-0.0343439057469368,
-0.008629915304481983,
0.2173895686864853,
0.010387005284428596,
-0.01822947897017002,
0.07931456714868546,
0.004284389317035675,
-0.07917945832014084,
-0.027795476838946342,
0.006740562617778778,
-0.0302827600389719,
-0.07373245805501938,
0.000882376916706562,
0.09730567038059235,
-0.047507788985967636,
0.0276784710586071,
-0.021805522963404655,
0.07519174367189407,
-0.031442172825336456,
-0.08182790130376816,
-0.023058222606778145,
-0.12138858437538147,
0.05121437832713127,
0.00941262673586607,
0.10639640688896179,
-0.030423488467931747,
0.031052814796566963,
0.031677477061748505,
0.06573899835348129,
0.017612973228096962,
0.06737203896045685,
-0.051719218492507935,
0.042898017913103104,
-0.07205133885145187,
0.09779981523752213,
0.0035009109415113926,
-0.06242850050330162,
0.06017311289906502,
0.11075939238071442,
0.08982300013303757,
-0.02422035112977028,
0.013866539113223553,
-0.026728440076112747,
0.02455153502523899,
0.037699926644563675,
-0.0678238645195961,
0.020649483427405357,
0.07183151692152023,
-0.10152968019247055,
-0.1126004084944725,
0.0019268944161012769,
0.032279033213853836,
-0.07176857441663742,
0.07289224863052368,
-0.025747032836079597,
-0.08427594602108002,
-0.16087916493415833,
0.06307380646467209,
-0.08258296549320221,
0.13176295161247253,
0.012012927792966366,
-0.13903012871742249,
-0.09383506327867508,
-0.0016380464658141136,
-0.07083885371685028,
0.061151206493377686,
0.005883279722183943,
-0.14232458174228668,
-0.0021238671615719795,
-0.033288490027189255,
0.03887975588440895,
-0.19890110194683075,
-0.14008742570877075,
0.07625366002321243,
0.18196234107017517,
0.20544731616973877,
0.04343082383275032,
0.07688333094120026,
0.08389148861169815,
-0.059144239872694016,
-0.10287569463253021,
0.07511218637228012,
0.030000904574990273,
-0.1146831139922142,
-0.07129077613353729,
-0.0978841632604599,
0.07635694742202759,
0.011953950859606266,
0.024546455591917038,
0.004637714475393295,
0.04023726284503937,
0.05821949243545532,
-0.038468677550554276,
-0.03062545880675316,
0.04965052753686905,
-0.11857877671718597,
0.06516570597887039,
-0.007663138210773468,
-0.12239059805870056,
-0.050147078931331635,
-0.05297697335481644,
0.15600332617759705,
0.1172158420085907,
-0.1513434201478958,
0.04187370464205742,
-0.0453239381313324,
0.10509788244962692,
-0.008674181997776031,
-0.07826098054647446,
-0.174920916557312,
-0.008347786031663418,
-0.05332622304558754,
0.07944749295711517,
-0.03953642398118973,
0.04153119772672653,
0.04495353251695633,
0.021202879026532173,
0.014220280572772026,
-0.2606639862060547,
0.053383637219667435,
-0.00606735423207283,
-0.085856132209301,
-0.12176349759101868
] |
null | null | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
Install the RL Zoo (with SB3 and SB3-Contrib):
```bash
pip install rl_zoo3
```
```
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga haihuynh -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
```
If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
```
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga haihuynh -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
```
## Training (with the RL Zoo)
```
python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga haihuynh
```
## Hyperparameters
```python
OrderedDict([('batch_size', 32),
('buffer_size', 100000),
('env_wrapper',
['stable_baselines3.common.atari_wrappers.AtariWrapper']),
('exploration_final_eps', 0.01),
('exploration_fraction', 0.1),
('frame_stack', 4),
('gradient_steps', 1),
('learning_rate', 0.0001),
('learning_starts', 100000),
('n_timesteps', 1000000.0),
('optimize_memory_usage', False),
('policy', 'CnnPolicy'),
('target_update_interval', 1000),
('train_freq', 4),
('normalize', False)])
```
# Environment Arguments
```python
{'render_mode': 'rgb_array'}
```
| {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFrameskip-v4", "type": "SpaceInvadersNoFrameskip-v4"}, "metrics": [{"type": "mean_reward", "value": "607.00 +/- 203.83", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | haihuynh/dqn-SpaceInvadersNoFrameskip-v4 | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | 2024-02-11T06:30:20+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL Zoo: URL
SB3: URL
SB3 Contrib: URL
Install the RL Zoo (with SB3 and SB3-Contrib):
If you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:
## Training (with the RL Zoo)
## Hyperparameters
# Environment Arguments
| [
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage (with SB3 RL Zoo)\n\nRL Zoo: URL\nSB3: URL\nSB3 Contrib: URL\n\nInstall the RL Zoo (with SB3 and SB3-Contrib):\n\n\n\n\nIf you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:",
"## Training (with the RL Zoo)",
"## Hyperparameters",
"# Environment Arguments"
] | [
"TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage (with SB3 RL Zoo)\n\nRL Zoo: URL\nSB3: URL\nSB3 Contrib: URL\n\nInstall the RL Zoo (with SB3 and SB3-Contrib):\n\n\n\n\nIf you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:",
"## Training (with the RL Zoo)",
"## Hyperparameters",
"# Environment Arguments"
] | [
43,
90,
73,
9,
5,
7
] | [
"passage: TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.## Usage (with SB3 RL Zoo)\n\nRL Zoo: URL\nSB3: URL\nSB3 Contrib: URL\n\nInstall the RL Zoo (with SB3 and SB3-Contrib):\n\n\n\n\nIf you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:## Training (with the RL Zoo)## Hyperparameters# Environment Arguments"
] | [
0.043572068214416504,
0.2414778620004654,
-0.0026879787910729647,
0.012635791674256325,
0.05784223601222038,
0.0030472534708678722,
0.08585051447153091,
0.10650663822889328,
0.024212315678596497,
-0.001382096204906702,
0.003954293206334114,
0.17533031105995178,
0.03632635250687599,
0.13125447928905487,
-0.018073517829179764,
-0.2066594809293747,
-0.013479253277182579,
-0.06247470900416374,
-0.07153085619211197,
0.036099132150411606,
0.07206681370735168,
-0.030116932466626167,
0.036061208695173264,
-0.051406677812337875,
-0.057161085307598114,
0.036824777722358704,
-0.03157254680991173,
0.007067287806421518,
0.15158706903457642,
-0.1222257912158966,
0.12329676002264023,
0.020955175161361694,
0.1896144151687622,
-0.12332789599895477,
0.0339222252368927,
0.08982209116220474,
-0.036988191306591034,
0.013221588917076588,
0.00975361280143261,
-0.052562564611434937,
0.1590864509344101,
-0.09371145814657211,
0.07146181166172028,
0.010926910676062107,
-0.07592244446277618,
-0.1774153709411621,
-0.09356249868869781,
0.07947742193937302,
0.0617753230035305,
0.005319166928529739,
0.03726791962981224,
0.11306490749120712,
-0.020991774275898933,
0.06488905102014542,
0.11562903225421906,
-0.17549200356006622,
0.013578375801444054,
0.17859570682048798,
0.003242473118007183,
0.15767055749893188,
-0.05546637624502182,
0.019877681508660316,
0.02752300351858139,
0.04758313298225403,
0.06873945891857147,
-0.08186400681734085,
-0.1364826112985611,
-0.056155186146497726,
-0.15456219017505646,
-0.03352400287985802,
0.05195203423500061,
-0.011860138736665249,
-0.05783402919769287,
-0.010724928230047226,
-0.04010869935154915,
0.0008851495804265141,
-0.028637725859880447,
0.01805497519671917,
0.07031578570604324,
-0.01226285845041275,
0.02092539705336094,
-0.08391954004764557,
-0.0390290804207325,
-0.038563769310712814,
-0.018022390082478523,
0.12054917961359024,
0.08285853266716003,
0.0266572255641222,
-0.04135355353355408,
0.10274127870798111,
-0.07091585546731949,
-0.05454207584261894,
0.04555258899927139,
-0.03786851093173027,
-0.10615779459476471,
0.02120024710893631,
-0.05905991420149803,
0.026879185810685158,
0.09943640232086182,
0.18048083782196045,
-0.09862488508224487,
0.012620617635548115,
-0.03430783003568649,
0.08121664822101593,
-0.03196052461862564,
0.03197542577981949,
-0.0840383991599083,
-0.016251085326075554,
0.17835216224193573,
0.0030782297253608704,
0.022272996604442596,
0.002074616262689233,
-0.049819961190223694,
-0.02881433069705963,
-0.017756454646587372,
0.06631895154714584,
0.07032092660665512,
0.010587303899228573,
-0.0037596761249005795,
-0.027667716145515442,
-0.036921944469213486,
-0.05629328638315201,
-0.04952820762991905,
0.018803736194968224,
-0.04712437093257904,
-0.047942135483026505,
0.06027210131287575,
-0.005624116864055395,
0.11337806284427643,
-0.025607796385884285,
0.026316547766327858,
-0.019410157576203346,
-0.07494441419839859,
-0.13221681118011475,
-0.0304415225982666,
0.0691632330417633,
0.04371757060289383,
-0.22497159242630005,
-0.16994807124137878,
-0.008539012633264065,
0.017946386709809303,
-0.018741264939308167,
-0.11334165185689926,
0.02453240379691124,
-0.007166135590523481,
-0.049758363515138626,
-0.01601579785346985,
0.10474669933319092,
-0.020438622683286667,
0.018010856583714485,
-0.05593825876712799,
0.16603368520736694,
-0.14290283620357513,
0.031004127115011215,
-0.08706212788820267,
0.023509707301855087,
-0.21286657452583313,
0.041208744049072266,
-0.177636057138443,
0.04863585904240608,
-0.08500861376523972,
0.02327173389494419,
0.021320728585124016,
0.01968831568956375,
0.08580207824707031,
0.10143322497606277,
-0.23631145060062408,
0.05405791476368904,
0.07900930196046829,
-0.022739801555871964,
-0.04218491166830063,
0.06798892468214035,
-0.06558530032634735,
0.1382148116827011,
0.046505436301231384,
0.24831900000572205,
0.10361487418413162,
-0.2036508023738861,
0.061786454170942307,
0.0578593946993351,
-0.08880111575126648,
-0.004730981774628162,
-0.020022382959723473,
0.11598580330610275,
-0.01114928349852562,
0.03338807821273804,
-0.12186288088560104,
0.1456439197063446,
0.02738998830318451,
-0.0165485180914402,
-0.04454165697097778,
-0.1614885926246643,
0.10309953987598419,
-0.015504824928939342,
0.09532155096530914,
-0.042415786534547806,
0.0001161050095106475,
-0.011168917641043663,
0.18012429773807526,
-0.043841805309057236,
0.0007168867159634829,
0.07871408760547638,
0.10895700752735138,
0.028009075671434402,
-0.020230965688824654,
-0.20380273461341858,
-0.0423048660159111,
0.02367858961224556,
0.044489551335573196,
0.2190362960100174,
0.19936694204807281,
0.07770156860351562,
-0.022313760593533516,
-0.025487221777439117,
-0.003248062450438738,
-0.05106664076447487,
0.03467361256480217,
-0.027858436107635498,
-0.024532482028007507,
0.06065356358885765,
-0.09305168688297272,
0.02817818708717823,
-0.13112716376781464,
0.06307920068502426,
-0.17345242202281952,
0.06863926351070404,
0.021998396143317223,
-0.005436043255031109,
0.024577690288424492,
-0.011292695067822933,
-0.034188106656074524,
-0.06233125180006027,
0.07110602408647537,
0.06098933145403862,
0.014702376909554005,
0.0021991983521729708,
-0.0683600977063179,
-0.13828523457050323,
0.08231553435325623,
-0.04042381793260574,
-0.14305958151817322,
0.06392676383256912,
0.011172642931342125,
0.04875864461064339,
-0.05975872278213501,
0.016254881396889687,
0.22900153696537018,
0.05321883037686348,
0.09785865992307663,
-0.04092191904783249,
-0.022525805979967117,
-0.06617844104766846,
-0.06677833944559097,
0.09694591909646988,
0.10812206566333771,
0.060318704694509506,
-0.0030071530491113663,
0.07626225054264069,
0.10942911356687546,
-0.1035122498869896,
-0.0651884600520134,
0.03220061957836151,
-0.05973697826266289,
0.019652515649795532,
0.049140311777591705,
0.02971293032169342,
0.08619047701358795,
0.1833551675081253,
0.008245792239904404,
0.0386311337351799,
-0.025997694581747055,
0.026109617203474045,
-0.15547916293144226,
-0.03145433962345123,
0.04308181628584862,
0.00886955764144659,
-0.07408110797405243,
0.04994636029005051,
0.051439400762319565,
0.13607151806354523,
-0.08217083662748337,
-0.13170577585697174,
-0.059745315462350845,
-0.03804200142621994,
-0.04239124804735184,
0.14975430071353912,
-0.08507520705461502,
-0.19221234321594238,
-0.017164425924420357,
-0.15751953423023224,
-0.02518727444112301,
-0.005179801490157843,
0.002318724524229765,
-0.08325926214456558,
0.017780914902687073,
0.010001576505601406,
-0.03129372000694275,
-0.0684933215379715,
-0.06596160680055618,
-0.05786636844277382,
0.09124112874269485,
0.06932931393384933,
-0.12240120023488998,
-0.00961651187390089,
-0.03742414712905884,
-0.020465577021241188,
0.04516167193651199,
0.08452648669481277,
-0.007267598994076252,
0.07773483544588089,
-0.13209199905395508,
-0.06962883472442627,
0.02834828943014145,
0.2766247093677521,
0.02882981114089489,
0.004668009467422962,
0.17051753401756287,
-0.03629542142152786,
0.04912714660167694,
0.16181479394435883,
0.030781643465161324,
-0.14196757972240448,
0.07090470939874649,
-0.011341600678861141,
-0.09542687982320786,
-0.1706860214471817,
-0.10215658694505692,
-0.037867411971092224,
-0.05015881359577179,
0.05638284236192703,
0.004951419774442911,
-0.04476970434188843,
0.05910305306315422,
0.08782228082418442,
-0.017004497349262238,
-0.06151578947901726,
0.11129767447710037,
0.032263003289699554,
-0.030136963352560997,
0.08078382909297943,
-0.042354047298431396,
-0.04206389561295509,
0.0032403599470853806,
0.22643887996673584,
0.0937788337469101,
-0.01775507442653179,
-0.042567066848278046,
0.019317636266350746,
0.05095715448260307,
0.03613382205367088,
0.11312435567378998,
-0.06975842267274857,
-0.06826137751340866,
-0.035185977816581726,
0.027829548344016075,
-0.02945687249302864,
0.08205190300941467,
0.0630207508802414,
0.005563626065850258,
-0.04653681069612503,
-0.07972332090139389,
-0.04849022626876831,
0.08408913016319275,
-0.027642227709293365,
-0.10093270242214203,
0.09321888536214828,
0.048575710505247116,
0.0016974330646917224,
0.03055831417441368,
0.027994604781270027,
0.01462269201874733,
-0.07982148975133896,
-0.06775744259357452,
0.011468625627458096,
0.07076629996299744,
-0.06822766363620758,
-0.027886953204870224,
-0.19817815721035004,
0.14578363299369812,
0.010630400851368904,
0.04118429124355316,
-0.13048617541790009,
0.1209396943449974,
-0.023116756230592728,
-0.026430301368236542,
0.013811616227030754,
0.0014643745962530375,
0.08203291147947311,
-0.04806509613990784,
0.15762180089950562,
0.009528410620987415,
-0.28092408180236816,
-0.1418946087360382,
-0.08416824042797089,
-0.051183976233005524,
-0.022873088717460632,
0.014752174727618694,
0.0642135739326477,
0.01516205258667469,
0.003868846921250224,
-0.013076163828372955,
0.03185269236564636,
-0.09826882928609848,
-0.06493937969207764,
-0.04839126765727997,
-0.02250157669186592,
-0.06525848805904388,
-0.05647949501872063,
-0.0006809153710491955,
-0.17226077616214752,
0.12522587180137634,
0.11787347495555878,
-0.06451737880706787,
-0.041814323514699936,
-0.06554657220840454,
0.046191465109586716,
-0.07571537792682648,
0.0469326451420784,
0.003414976177737117,
0.019198855385184288,
-0.06806991249322891,
-0.17922484874725342,
0.016097763553261757,
-0.10899919271469116,
0.03772687539458275,
-0.05070559307932854,
0.020257100462913513,
0.08594245463609695,
0.17520126700401306,
0.05856714025139809,
0.01460097823292017,
-0.07239776104688644,
-0.07543374598026276,
-0.0017121878918260336,
-0.06344114243984222,
0.05762333422899246,
-0.009151889942586422,
-0.20333483815193176,
0.02763226442039013,
-0.11414948850870132,
0.06860900670289993,
0.3310066759586334,
0.3324824273586273,
-0.10698744654655457,
0.1177443116903305,
0.04819539934396744,
-0.042202454060316086,
-0.21051374077796936,
-0.002244179602712393,
0.012272895313799381,
0.024992236867547035,
0.13725964725017548,
-0.12924811244010925,
0.05453680083155632,
0.0794181227684021,
-0.024458877742290497,
0.01456840243190527,
-0.09078162908554077,
-0.10816970467567444,
0.20847418904304504,
0.14226987957954407,
0.04421741142868996,
-0.09421348571777344,
0.08391669392585754,
0.004295284394174814,
0.08375877887010574,
0.2107764035463333,
-0.052112679928541183,
0.10695768147706985,
0.005195184610784054,
0.19852910935878754,
0.0328996516764164,
-0.023768596351146698,
0.10834760218858719,
-0.009801650419831276,
0.07911337912082672,
0.03985166177153587,
-0.007676942739635706,
0.010487722232937813,
-0.04522453248500824,
0.014148596674203873,
-0.028376007452607155,
0.010284217074513435,
-0.2274095118045807,
0.0582297146320343,
-0.06368855386972427,
0.04604509472846985,
0.008256820961833,
-0.0999874547123909,
-0.03583388403058052,
0.06431841105222702,
0.08014573156833649,
0.01975327916443348,
0.0436067171394825,
-0.03867863491177559,
0.11051398515701294,
0.20660489797592163,
-0.009811338968575,
0.17751595377922058,
-0.0615963339805603,
0.01464168168604374,
-0.023011628538370132,
-0.04223164543509483,
-0.1462583988904953,
-0.035259708762168884,
0.03498423472046852,
0.057734888046979904,
0.015203364193439484,
0.049647457897663116,
-0.05656236410140991,
0.08498423546552658,
0.021687336266040802,
-0.041541360318660736,
0.033579520881175995,
0.08835696429014206,
0.12415177375078201,
0.010754258371889591,
-0.030121933668851852,
0.06147436052560806,
-0.08128108084201813,
-0.09446098655462265,
-0.004497923422604799,
-0.029991207644343376,
-0.1083834245800972,
0.11353230476379395,
0.16914646327495575,
0.039594944566488266,
-0.057076629251241684,
0.10688766092061996,
-0.02768099494278431,
0.10047874599695206,
0.009198128245770931,
0.06507332623004913,
-0.014091075398027897,
-0.03691792115569115,
0.10611724853515625,
-0.05442855879664421,
-0.01637818105518818,
0.07645545154809952,
-0.06522727757692337,
-0.023877469822764397,
-0.0801999643445015,
0.06034626066684723,
0.09222240000963211,
-0.16854619979858398,
-0.0639432892203331,
-0.032122284173965454,
-0.08628080040216446,
0.013965039514005184,
0.012447911314666271,
0.0710059329867363,
-0.08589600026607513,
0.06316167116165161,
-0.024337708950042725,
0.015639442950487137,
-0.03689891844987869,
0.019222697243094444,
-0.19525384902954102,
-0.002140450058504939,
-0.11280795186758041,
-0.00348020251840353,
-0.002931603929027915,
0.04463808611035347,
-0.04961875081062317,
-0.029358822852373123,
-0.0030675032176077366,
0.044366419315338135,
-0.16609135270118713,
0.002798673929646611,
-0.011639905162155628,
0.03210212290287018,
-0.0002893915225286037,
-0.0983390137553215,
0.014195028692483902,
-0.04294256120920181,
-0.04198618605732918,
0.04925514757633209,
0.009436776861548424,
0.06470516324043274,
-0.2795179784297943,
-0.14905457198619843,
0.030816160142421722,
0.0683867484331131,
0.05483196675777435,
-0.1830425262451172,
0.03568267077207565,
-0.08042316138744354,
-0.02253127470612526,
-0.037770628929138184,
0.018491698428988457,
-0.0539514496922493,
0.0018174031283706427,
-0.04225044324994087,
-0.023033907637000084,
-0.028055014088749886,
-0.07556360960006714,
0.0826747715473175,
0.12462522834539413,
0.07555580884218216,
-0.03807181864976883,
0.09595896303653717,
-0.10009756684303284,
-0.04657831788063049,
-0.04052736237645149,
-0.036951083689928055,
0.017965637147426605,
-0.0870552659034729,
0.048530060797929764,
0.05188591405749321,
0.18719671666622162,
-0.08520494401454926,
-0.058800119906663895,
-0.014255574904382229,
0.0746525228023529,
0.07849094271659851,
0.005095830652862787,
0.17779210209846497,
-0.045693784952163696,
0.05693846940994263,
0.021304311230778694,
0.046699028462171555,
0.10497613251209259,
-0.023569339886307716,
0.14490213990211487,
0.21171095967292786,
-0.037196725606918335,
-0.11048602312803268,
0.043668005615472794,
0.01745123788714409,
-0.002401199424639344,
0.05968761444091797,
0.11983796209096909,
-0.050589341670274734,
-0.10903856158256531,
0.23442286252975464,
0.054169271141290665,
-0.11218088120222092,
0.09546315670013428,
0.039532262831926346,
-0.015890996903181076,
-0.1301896870136261,
0.010444961488246918,
-0.0013640925753861666,
-0.11233190447092056,
0.03386834263801575,
-0.06087532266974449,
-0.025547027587890625,
0.11809267848730087,
0.008789865300059319,
0.03317064419388771,
-0.04139537364244461,
-0.03756232187151909,
-0.04352104663848877,
-0.04273213446140289,
-0.012549578212201595,
-0.02991986647248268,
-0.030186517164111137,
-0.07621737569570541,
-0.007770835887640715,
-0.012012424878776073,
0.030795488506555557,
-0.015285328030586243,
-0.02503054589033127,
-0.021192016080021858,
-0.06697061657905579,
-0.0026312144473195076,
-0.008178025484085083,
0.015549594536423683,
0.010121971368789673,
0.2358063906431198,
0.07042546570301056,
-0.10260069370269775,
-0.01036880537867546,
0.22197756171226501,
-0.03853277862071991,
-0.06528383493423462,
-0.07849395275115967,
0.25128230452537537,
-0.10482002794742584,
0.051095426082611084,
-0.005819917656481266,
-0.06550488620996475,
-0.07153836637735367,
0.2309868484735489,
0.13502730429172516,
-0.1677926480770111,
0.06329060345888138,
-0.0368385910987854,
-0.009490780532360077,
-0.14286863803863525,
0.16013580560684204,
0.1865294873714447,
0.09480160474777222,
-0.12259847670793533,
0.0023130534682422876,
-0.03518044203519821,
-0.018328361213207245,
-0.1660851687192917,
-0.004593863617628813,
-0.029364850372076035,
-0.0427238829433918,
-0.050771355628967285,
0.029773715883493423,
-0.15205919742584229,
-0.0927426889538765,
-0.1916799396276474,
-0.11482496559619904,
-0.12386849522590637,
-0.04549141973257065,
-0.11142764985561371,
-0.0019938007462769747,
0.02257080189883709,
-0.0641874223947525,
0.021061956882476807,
-0.0212461706250906,
-0.05887424945831299,
0.015386379323899746,
-0.08395619690418243,
0.0674985870718956,
0.06488548219203949,
0.15327942371368408,
-0.0790991559624672,
0.025424562394618988,
0.07090727984905243,
-0.057595450431108475,
-0.10164349526166916,
0.06067253649234772,
0.015708057209849358,
-0.1972588747739792,
0.007548294495791197,
0.17712996900081635,
-0.10420889407396317,
0.09745754301548004,
0.048501528799533844,
-0.012951982207596302,
0.0867827981710434,
-0.024721821770071983,
-0.016682926565408707,
-0.04852180927991867,
-0.011212974786758423,
-0.10143939405679703,
0.09892100840806961,
0.0876845121383667,
-0.0517118014395237,
0.07436849176883698,
-0.09508965909481049,
-0.04068392515182495,
0.13103286921977997,
-0.010057874955236912,
-0.08450483530759811,
-0.11667824536561966,
-0.04081142693758011,
0.09684515744447708,
-0.018041390925645828,
-0.20185889303684235,
-0.11639472097158432,
-0.11752668023109436,
-0.00014377340266946703,
-0.03563340753316879,
0.061800602823495865,
0.02430674433708191,
-0.02556120604276657,
-0.008150683715939522,
-0.17615078389644623,
-0.06614746153354645,
0.13479791581630707,
-0.10176112502813339,
-0.07456064969301224
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 500STEPS_1e6rate_01beta_DPO_Meditron7B
This model is a fine-tuned version of [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6302
- Rewards/chosen: 0.0115
- Rewards/rejected: -0.1672
- Rewards/accuracies: 0.5868
- Rewards/margins: 0.1788
- Logps/rejected: -29.4661
- Logps/chosen: -26.3659
- Logits/rejected: -0.7645
- Logits/chosen: -0.7643
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6902 | 0.1 | 50 | 0.6903 | 0.0090 | 0.0031 | 0.5121 | 0.0058 | -27.7623 | -26.3918 | -0.6125 | -0.6124 |
| 0.6766 | 0.2 | 100 | 0.6792 | -0.1559 | -0.1907 | 0.5099 | 0.0349 | -29.7009 | -28.0399 | -0.6382 | -0.6380 |
| 0.6667 | 0.29 | 150 | 0.6567 | -0.0224 | -0.1102 | 0.5714 | 0.0879 | -28.8959 | -26.7051 | -0.6559 | -0.6557 |
| 0.6656 | 0.39 | 200 | 0.6495 | -0.0303 | -0.1387 | 0.5802 | 0.1084 | -29.1808 | -26.7847 | -0.7108 | -0.7106 |
| 0.5939 | 0.49 | 250 | 0.6388 | -0.0202 | -0.1629 | 0.5890 | 0.1426 | -29.4223 | -26.6837 | -0.7329 | -0.7327 |
| 0.6328 | 0.59 | 300 | 0.6349 | -0.0421 | -0.2022 | 0.5758 | 0.1601 | -29.8158 | -26.9024 | -0.7492 | -0.7490 |
| 0.6231 | 0.68 | 350 | 0.6313 | -0.0004 | -0.1725 | 0.5758 | 0.1721 | -29.5189 | -26.4852 | -0.7571 | -0.7569 |
| 0.6419 | 0.78 | 400 | 0.6303 | 0.0123 | -0.1660 | 0.5868 | 0.1783 | -29.4536 | -26.3585 | -0.7639 | -0.7637 |
| 0.6045 | 0.88 | 450 | 0.6304 | 0.0120 | -0.1662 | 0.5846 | 0.1783 | -29.4560 | -26.3611 | -0.7645 | -0.7643 |
| 0.5984 | 0.98 | 500 | 0.6302 | 0.0115 | -0.1672 | 0.5868 | 0.1788 | -29.4661 | -26.3659 | -0.7645 | -0.7643 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.0.0+cu117
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "llama2", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "epfl-llm/meditron-7b", "model-index": [{"name": "500STEPS_1e6rate_01beta_DPO_Meditron7B", "results": []}]} | text-generation | tsavage68/500STEPS_1e6rate_01beta_DPO_Meditron7B_zeroshot | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"dpo",
"generated_from_trainer",
"base_model:epfl-llm/meditron-7b",
"license:llama2",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T06:33:50+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #trl #dpo #generated_from_trainer #base_model-epfl-llm/meditron-7b #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| 500STEPS\_1e6rate\_01beta\_DPO\_Meditron7B
==========================================
This model is a fine-tuned version of epfl-llm/meditron-7b on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6302
* Rewards/chosen: 0.0115
* Rewards/rejected: -0.1672
* Rewards/accuracies: 0.5868
* Rewards/margins: 0.1788
* Logps/rejected: -29.4661
* Logps/chosen: -26.3659
* Logits/rejected: -0.7645
* Logits/chosen: -0.7643
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 1e-06
* train\_batch\_size: 4
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 500
### Training results
### Framework versions
* Transformers 4.37.2
* Pytorch 2.0.0+cu117
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: 100\n* training\\_steps: 500",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.0.0+cu117\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #trl #dpo #generated_from_trainer #base_model-epfl-llm/meditron-7b #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: 100\n* training\\_steps: 500",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.0.0+cu117\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
82,
144,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #trl #dpo #generated_from_trainer #base_model-epfl-llm/meditron-7b #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: 100\n* training\\_steps: 500### Training results### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.0.0+cu117\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.1370444893836975,
0.11137712001800537,
-0.0028052947018295527,
0.06850133091211319,
0.1315784901380539,
0.020102262496948242,
0.11770295351743698,
0.1412091851234436,
-0.08467997610569,
0.09741789847612381,
0.1470157355070114,
0.13382075726985931,
0.06182865798473358,
0.18442164361476898,
-0.01987103372812271,
-0.3068523705005646,
-0.0064958250150084496,
-0.007786974776536226,
-0.15876048803329468,
0.13364824652671814,
0.08513610810041428,
-0.12293168902397156,
0.0469684861600399,
-0.03462096303701401,
-0.10993894934654236,
-0.04153785854578018,
-0.03359147161245346,
-0.04190453141927719,
0.12345650047063828,
-0.00869361124932766,
0.09833618998527527,
0.051737990230321884,
0.10844818502664566,
-0.24648603796958923,
0.010403677821159363,
0.058301396667957306,
0.041693076491355896,
0.0822744071483612,
0.06836456060409546,
-0.030550755560398102,
0.09499567002058029,
-0.1082860678434372,
0.07966400682926178,
0.02715575508773327,
-0.1129067912697792,
-0.23427638411521912,
-0.10450135916471481,
0.06982384622097015,
0.15650521218776703,
0.082139752805233,
-0.01952170766890049,
0.059845976531505585,
-0.08253970742225647,
0.0753118246793747,
0.2543110251426697,
-0.27443498373031616,
-0.07545756548643112,
0.05736389383673668,
0.06646878272294998,
0.05256512016057968,
-0.1258143186569214,
-0.018154434859752655,
0.027425741776823997,
0.0069501702673733234,
0.15300576388835907,
0.0027802097611129284,
0.10662225633859634,
0.0029245151672512293,
-0.14746838808059692,
-0.052899524569511414,
0.10981082916259766,
0.08208620548248291,
-0.035142842680215836,
-0.11712735146284103,
-0.021801616996526718,
-0.2558657228946686,
-0.03952455893158913,
-0.02116853930056095,
0.03705544024705887,
-0.05136609449982643,
-0.08959027379751205,
0.00762214558199048,
-0.07259184122085571,
-0.10712620615959167,
0.05798076093196869,
0.14277324080467224,
0.03990085795521736,
-0.0518999919295311,
0.035094212740659714,
0.16497229039669037,
0.0850413367152214,
-0.14607173204421997,
-0.0003039710863959044,
0.03381253033876419,
-0.07210442423820496,
-0.03581725060939789,
-0.008698011748492718,
0.014585350640118122,
0.012158526107668877,
0.1703733205795288,
-0.0248958021402359,
0.0355471596121788,
0.07584985345602036,
0.036487434059381485,
-0.11068522185087204,
0.1439056396484375,
-0.0710131898522377,
-0.0909663513302803,
-0.03374530375003815,
0.15844608843326569,
0.006684933323413134,
-0.005719734355807304,
-0.0776429995894432,
0.019989289343357086,
0.10941461473703384,
0.0788862407207489,
-0.023809166625142097,
0.030636660754680634,
-0.08432845771312714,
-0.016928767785429955,
0.03920454531908035,
-0.10211191326379776,
0.02566690556704998,
0.007267171051353216,
-0.07301948964595795,
-0.050661638379096985,
-0.0005758564220741391,
0.015117366798222065,
0.0004118831711821258,
0.1519617736339569,
-0.06890492886304855,
-0.028894435614347458,
-0.10056344419717789,
-0.08947007358074188,
0.015112239867448807,
-0.10149872303009033,
-0.000460554554592818,
-0.0660780593752861,
-0.15713751316070557,
-0.0700063705444336,
0.05365537106990814,
-0.04837024211883545,
-0.0778326690196991,
-0.09355765581130981,
-0.1016547754406929,
0.01783076487481594,
-0.013492798432707787,
0.1633024513721466,
-0.04848877713084221,
0.14081460237503052,
-0.007978479377925396,
0.0789191722869873,
0.08569502085447311,
0.05787995085120201,
-0.04842055216431618,
0.06485624611377716,
-0.17309074103832245,
0.06543978303670883,
-0.06653612852096558,
0.0741594135761261,
-0.13033199310302734,
-0.09889516979455948,
-0.037662576884031296,
-0.0033264588564634323,
0.08774160593748093,
0.15954376757144928,
-0.16883611679077148,
-0.0841873437166214,
0.19479477405548096,
-0.05288003012537956,
-0.11927908658981323,
0.10209287703037262,
-0.023934176191687584,
0.02965305559337139,
0.03228643536567688,
0.13769645988941193,
0.10035786777734756,
-0.08960173279047012,
0.012413258664309978,
-0.033662956207990646,
0.08765394240617752,
0.004336658399552107,
0.09869834035634995,
-0.04184449836611748,
0.04729031026363373,
-0.0069322483614087105,
-0.08182454109191895,
0.047701284289360046,
-0.09901715815067291,
-0.08330505341291428,
0.004009528085589409,
-0.09990198910236359,
0.05639704689383507,
0.046090029180049896,
0.03314248099923134,
-0.0830148234963417,
-0.11618723720312119,
-0.005633119959384203,
0.10819993913173676,
-0.08065858483314514,
0.008784555830061436,
-0.03614087030291557,
0.06071922555565834,
-0.01286742091178894,
0.0012257173657417297,
-0.14031068980693817,
-0.0378723181784153,
0.026560204103589058,
0.015498755499720573,
-0.02164842002093792,
-0.025115162134170532,
0.07990696281194687,
0.06246756762266159,
-0.07477686554193497,
-0.08974093943834305,
-0.07023056596517563,
-0.009322416968643665,
-0.10423718392848969,
-0.23269891738891602,
-0.06959120184183121,
-0.03585711121559143,
0.19245930016040802,
-0.24325329065322876,
0.05154384300112724,
0.0026396086905151606,
0.11039320379495621,
0.04479086399078369,
-0.05198584496974945,
0.009397835470736027,
0.05782529339194298,
-0.017083048820495605,
-0.09686371684074402,
0.043830666691064835,
-0.014478076249361038,
-0.13344703614711761,
-0.02212899550795555,
-0.12283044308423996,
0.12535279989242554,
0.10193545371294022,
0.03044588305056095,
-0.13463564217090607,
-0.1032181978225708,
-0.0724567323923111,
-0.03979574516415596,
-0.036943960934877396,
0.00292016239836812,
0.10427342355251312,
0.0442923940718174,
0.11960112303495407,
-0.07575640082359314,
-0.06460484117269516,
0.02895524725317955,
0.0008705828222446144,
0.011925882659852505,
0.1580309271812439,
0.07028286159038544,
-0.03958938643336296,
0.12807166576385498,
0.13010816276073456,
-0.036400750279426575,
0.13202489912509918,
-0.05651337280869484,
-0.09861641377210617,
-0.029463570564985275,
0.07275039702653885,
0.04172695428133011,
0.12438751757144928,
-0.08794009685516357,
-0.002506541321054101,
0.01182776503264904,
0.017413755878806114,
-0.008493502624332905,
-0.21520954370498657,
-0.05351022630929947,
0.04607759043574333,
-0.06438371539115906,
-0.000019787223209277727,
-0.024770546704530716,
-0.023233337327837944,
0.10252603143453598,
0.035987913608551025,
-0.054317906498909,
0.010924136266112328,
-0.005772308446466923,
-0.08065500855445862,
0.22171372175216675,
-0.08350435644388199,
-0.12655308842658997,
-0.10942086577415466,
0.0402870699763298,
0.009838604368269444,
0.007656086701899767,
0.023364771157503128,
-0.09110509604215622,
0.0073280008509755135,
-0.07070311903953552,
0.012420032173395157,
-0.028444452211260796,
0.03398549184203148,
-0.0170992873609066,
0.027035601437091827,
0.03031979687511921,
-0.08207220584154129,
0.01591094210743904,
-0.021302249282598495,
-0.04893346130847931,
0.051786113530397415,
0.021776966750621796,
0.1056646928191185,
0.1730422079563141,
0.023958180099725723,
0.019996879622340202,
-0.04934591427445412,
0.13105255365371704,
-0.13718855381011963,
0.005232049152255058,
0.10375122725963593,
0.03465266153216362,
0.05213795229792595,
0.1437351554632187,
0.04616936296224594,
-0.1006707176566124,
0.044002700597047806,
0.04083917662501335,
-0.022746695205569267,
-0.21557866036891937,
-0.00017147837206721306,
-0.04394281283020973,
0.013681204989552498,
0.12413167208433151,
0.035096000880002975,
0.009352757595479488,
0.06058254465460777,
-0.024682965129613876,
-0.0033100578002631664,
0.013057210482656956,
0.07478491961956024,
-0.00763461971655488,
0.022570155560970306,
0.1107000783085823,
-0.011376870796084404,
-0.047711826860904694,
0.007944361306726933,
0.026269135996699333,
0.2428794652223587,
-0.022735964506864548,
0.13834170997142792,
0.04906054213643074,
0.1497374176979065,
-0.014208265580236912,
0.08394423872232437,
0.0348617285490036,
-0.03949849680066109,
0.002898324513807893,
-0.05491434410214424,
-0.03542649745941162,
0.04888537526130676,
0.027408208698034286,
0.05576071888208389,
-0.1357797384262085,
0.024753937497735023,
0.026495980098843575,
0.3318392336368561,
0.08269764482975006,
-0.3076070547103882,
-0.08151434361934662,
0.01019333302974701,
-0.04897478595376015,
-0.032227326184511185,
0.01771935448050499,
0.11791269481182098,
-0.11222546547651291,
0.04266137629747391,
-0.08484994620084763,
0.06931143254041672,
-0.08297529816627502,
-0.007230343762785196,
0.053740259259939194,
0.0750671848654747,
-0.025614339858293533,
0.057711515575647354,
-0.29281240701675415,
0.3079744577407837,
-0.011096280068159103,
0.07840018719434738,
-0.04966726154088974,
0.016657443717122078,
0.020858755335211754,
0.017694411799311638,
0.13163675367832184,
-0.006221976596862078,
-0.007121794857084751,
-0.2000391036272049,
-0.09739646315574646,
-0.0061480398289859295,
0.14105655252933502,
-0.14666765928268433,
0.12321311235427856,
-0.01580153964459896,
-0.028540901839733124,
0.04165884479880333,
-0.08619729429483414,
-0.06300472468137741,
-0.08619066327810287,
0.02064451575279236,
-0.044083524495363235,
0.09318951517343521,
-0.11186426877975464,
-0.09959850460290909,
-0.055859580636024475,
0.15180912613868713,
-0.11696001887321472,
-0.035542670637369156,
-0.14053259789943695,
0.08158285915851593,
0.12098323553800583,
-0.06971726566553116,
0.047556616365909576,
0.02244655229151249,
0.08760960400104523,
-0.0010466636158525944,
0.023110100999474525,
0.11119025945663452,
-0.07513986527919769,
-0.24972330033779144,
-0.07142114639282227,
0.1842835694551468,
0.04265091195702553,
0.06194689869880676,
-0.021759076043963432,
0.01401066780090332,
0.007350782863795757,
-0.08748587965965271,
0.07977468520402908,
0.0266933124512434,
0.05946281552314758,
0.038256291300058365,
-0.05247645825147629,
0.08222224563360214,
-0.06656263768672943,
-0.0722469612956047,
0.12847885489463806,
0.330059289932251,
-0.09760168194770813,
0.033851392567157745,
0.04247696325182915,
-0.03631239011883736,
-0.17470955848693848,
0.018829356878995895,
0.11113469302654266,
0.044629279524087906,
0.012629685923457146,
-0.19720478355884552,
0.026786962524056435,
0.1065797433257103,
-0.027652613818645477,
0.11884384602308273,
-0.3476732075214386,
-0.12910966575145721,
0.0725511685013771,
0.12977029383182526,
-0.009814739227294922,
-0.17453402280807495,
-0.060013547539711,
0.0021581409964710474,
-0.06254548579454422,
0.060819365084171295,
-0.005587100051343441,
0.12741024792194366,
-0.01918300986289978,
0.004808514844626188,
0.029980605468153954,
-0.06595732271671295,
0.1293625831604004,
0.006532253231853247,
0.07808401435613632,
-0.019009102135896683,
-0.002308659488335252,
0.00659683533012867,
-0.07846303284168243,
0.018470073118805885,
-0.09190063178539276,
0.02241804450750351,
-0.11109644919633865,
-0.03274225816130638,
-0.0851965993642807,
0.03307396546006203,
-0.06116069480776787,
-0.07686243951320648,
-0.019739830866456032,
0.05703229457139969,
0.060967471450567245,
-0.0013626068830490112,
0.0961850956082344,
-0.03286019712686539,
0.15653358399868011,
0.07185506075620651,
0.10479345917701721,
0.003940506838262081,
-0.07398904860019684,
-0.008135788142681122,
-0.019676921889185905,
0.05016192048788071,
-0.13711120188236237,
-0.004866500850766897,
0.14208580553531647,
0.06172630563378334,
0.14533492922782898,
0.06346800923347473,
-0.05841290205717087,
-0.010732078924775124,
0.07469283789396286,
-0.09173253178596497,
-0.1338113397359848,
-0.008455158211290836,
-0.02009926363825798,
-0.15473224222660065,
0.04223741218447685,
0.091743603348732,
-0.05976519361138344,
-0.011260876432061195,
0.0031191501766443253,
0.027367031201720238,
-0.026011839509010315,
0.21821758151054382,
0.06381022185087204,
0.10593165457248688,
-0.07571298629045486,
0.07767589390277863,
0.03205905482172966,
-0.12845638394355774,
0.011500508524477482,
0.08488618582487106,
-0.08859225362539291,
-0.020657898858189583,
0.05156439170241356,
0.06236616149544716,
0.014556553214788437,
-0.00938078761100769,
-0.12016592919826508,
-0.12915682792663574,
0.07730843871831894,
0.08134775608778,
0.042493272572755814,
0.03680405393242836,
-0.015240360051393509,
0.04479813575744629,
-0.13323119282722473,
0.11050749570131302,
0.07262761145830154,
0.08557925373315811,
-0.1388959139585495,
0.1654922068119049,
-0.010129471309483051,
0.006501240190118551,
0.000003825887233688263,
0.03224444016814232,
-0.11847147345542908,
0.009922292083501816,
-0.020344190299510956,
-0.07344254851341248,
-0.058363426476716995,
-0.020544350147247314,
-0.010097096674144268,
-0.033663466572761536,
-0.00487688509747386,
-0.0028989810962229967,
-0.10705437511205673,
-0.06150074303150177,
-0.013590430840849876,
0.05008886009454727,
-0.09522580355405807,
-0.038970597088336945,
0.02546326257288456,
-0.11723753064870834,
0.0938883125782013,
0.009986916556954384,
0.05258888378739357,
-0.0008780204807408154,
-0.1104881763458252,
0.052210960537195206,
0.03741449862718582,
-0.028433389961719513,
0.021069340407848358,
-0.14310666918754578,
-0.018124716356396675,
-0.06444413214921951,
0.006188256200402975,
0.020480608567595482,
0.0006151768611744046,
-0.1503971368074417,
0.003103512106463313,
-0.042107000946998596,
-0.04306777939200401,
-0.0751689225435257,
0.056524116545915604,
0.060210470110177994,
-0.0036938379053026438,
0.15093302726745605,
-0.0649375170469284,
0.061172276735305786,
-0.22224053740501404,
-0.01495748944580555,
-0.018340012058615685,
-0.06518096476793289,
-0.07599414139986038,
-0.02721763588488102,
0.09540671855211258,
-0.0541430339217186,
0.04452826455235481,
-0.054143499583005905,
0.038405001163482666,
0.02105678990483284,
-0.10616215318441391,
0.08431069552898407,
0.05075724795460701,
0.17948012053966522,
0.056331608444452286,
-0.04286149889230728,
0.03932040184736252,
0.04064331576228142,
0.06478769332170486,
0.07039719074964523,
0.18609075248241425,
0.1403115689754486,
0.004727451130747795,
0.08343514800071716,
0.023364460095763206,
-0.12811477482318878,
-0.15887866914272308,
0.09813465923070908,
-0.029783159494400024,
0.09208696335554123,
-0.024800866842269897,
0.22251950204372406,
0.12118364870548248,
-0.20894938707351685,
0.03210451453924179,
-0.018374141305685043,
-0.08561266213655472,
-0.0863877460360527,
-0.07291156053543091,
-0.06154682859778404,
-0.16264115273952484,
0.00789135042577982,
-0.0997103825211525,
0.017890693619847298,
0.06887296587228775,
0.022215090692043304,
0.03184462711215019,
0.1523260623216629,
0.06984175741672516,
0.02770409733057022,
0.1053919792175293,
0.03331135958433151,
0.004536785185337067,
-0.05653492361307144,
-0.10888417065143585,
0.012347156181931496,
-0.07380358129739761,
0.043278977274894714,
-0.07727500051259995,
-0.10057543963193893,
0.056270185858011246,
0.03709607571363449,
-0.09763529896736145,
0.02375962771475315,
-0.0011392517480999231,
0.07113136351108551,
0.09169641882181168,
0.01712600700557232,
-0.01247415691614151,
-0.028865840286016464,
0.2604939937591553,
-0.09588586539030075,
-0.051405955106019974,
-0.10514871776103973,
0.2451775074005127,
0.03604252636432648,
-0.0017895237542688847,
0.019355740398168564,
-0.08672194927930832,
0.022999828681349754,
0.17351092398166656,
0.16932597756385803,
-0.03531164303421974,
-0.008746461942791939,
0.025442244485020638,
-0.01471795979887247,
-0.035094063729047775,
0.08017487823963165,
0.1260363757610321,
0.043627578765153885,
-0.07358124852180481,
-0.008089672774076462,
-0.025394229218363762,
-0.06303118169307709,
-0.03768511489033699,
0.07441036403179169,
0.05625202879309654,
0.00817836169153452,
-0.03049778938293457,
0.11250109225511551,
-0.026772452518343925,
-0.13802886009216309,
0.08119278401136398,
-0.19199538230895996,
-0.1749647557735443,
-0.059813324362039566,
0.015361031517386436,
0.006848587188869715,
0.06732097268104553,
0.009555604308843613,
-0.020080214366316795,
0.0945185124874115,
-0.00023479449737351388,
-0.045404184609651566,
-0.09366081655025482,
0.057487547397613525,
-0.04775848239660263,
0.18539130687713623,
-0.05634356290102005,
-0.003987257368862629,
0.12925946712493896,
0.031642381101846695,
-0.0878560021519661,
0.050553467124700546,
0.08754841983318329,
-0.0747513398528099,
0.05853909254074097,
0.15437214076519012,
-0.03194039687514305,
0.09805755317211151,
0.0369357131421566,
-0.13270024955272675,
0.019832590594887733,
-0.0963529422879219,
-0.06340289115905762,
-0.08849857747554779,
0.021224884316325188,
-0.01914980448782444,
0.13971281051635742,
0.23553578555583954,
-0.06519075483083725,
0.015726083889603615,
-0.04891485720872879,
0.012214420363307,
0.057881154119968414,
0.10059785097837448,
-0.02214725688099861,
-0.23389585316181183,
0.006487399339675903,
0.038323186337947845,
-0.0031800135038793087,
-0.24754434823989868,
-0.09598669409751892,
0.02050384320318699,
-0.058713946491479874,
-0.0913548469543457,
0.0898413136601448,
0.04815834388136864,
0.059895940124988556,
-0.04816649854183197,
-0.10439252108335495,
-0.05511923506855965,
0.19163087010383606,
-0.18278396129608154,
-0.0596168227493763
] |
null | null | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
```
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarLander-v2"}, "metrics": [{"type": "mean_reward", "value": "289.84 +/- 16.31", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | nburley/ppo-LunarLander-v2 | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | 2024-02-11T06:34:29+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
39,
41,
17
] | [
"passage: TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
0.03942384943366051,
0.04900386184453964,
-0.005304091144353151,
0.026427261531352997,
0.107408307492733,
-0.026511888951063156,
0.11188238859176636,
0.0814051404595375,
0.10722193866968155,
0.04762078449130058,
0.08338645845651627,
0.06030960753560066,
0.05080918222665787,
0.2571701407432556,
0.04754156619310379,
-0.22987541556358337,
0.036159250885248184,
-0.04869936779141426,
0.12395193427801132,
0.07178173214197159,
-0.0038484656251966953,
-0.06485428661108017,
0.020415637642145157,
-0.013290755450725555,
0.05367108806967735,
0.04282612353563309,
-0.01716216839849949,
-0.08207534998655319,
0.07169748842716217,
-0.06345846503973007,
0.06986866891384125,
0.07677983492612839,
0.13218913972377777,
-0.17832116782665253,
0.029566360637545586,
0.02571309357881546,
-0.07189024239778519,
0.01342033501714468,
0.008019951172173023,
0.05120139941573143,
0.17303818464279175,
0.019879888743162155,
0.07844575494527817,
-0.0025605305563658476,
-0.15412317216396332,
-0.018950799480080605,
0.0436202734708786,
0.12546207010746002,
0.08808347582817078,
0.04605821147561073,
0.01970590092241764,
0.17503218352794647,
-0.054352790117263794,
-0.028833400458097458,
0.21759237349033356,
-0.2881564497947693,
-0.031460098922252655,
0.321048766374588,
0.06997483223676682,
0.09725230932235718,
-0.07540661096572876,
-0.03619609400629997,
0.007783263456076384,
-0.013137873262166977,
-0.028666524216532707,
-0.07447073608636856,
0.17313385009765625,
0.05152064561843872,
-0.05057951435446739,
-0.09541505575180054,
0.16948209702968597,
0.006921638268977404,
0.0018855923553928733,
-0.019282981753349304,
0.009060598909854889,
0.07402525842189789,
-0.016097044572234154,
-0.07255112379789352,
0.057438433170318604,
0.05330665782094002,
0.019649166613817215,
-0.1435653269290924,
-0.10762494057416916,
-0.022740179672837257,
-0.008012006990611553,
0.17786912620067596,
-0.009255532175302505,
0.042902372777462006,
0.003065188182517886,
0.10384012013673782,
-0.12480384111404419,
-0.03354184702038765,
-0.0454259067773819,
-0.07565800100564957,
-0.0223417766392231,
-0.02058211714029312,
-0.03580251708626747,
0.07184842973947525,
0.11971849203109741,
0.027368178591132164,
0.09350208193063736,
0.047715865075588226,
-0.03206788748502731,
0.06343851238489151,
0.05555703118443489,
0.14222665131092072,
0.05807621404528618,
0.012854371219873428,
0.13179877400398254,
0.055213116109371185,
0.033023182302713394,
-0.0613492950797081,
-0.18252409994602203,
0.07489913702011108,
-0.07031869143247604,
0.007941240444779396,
0.12051256000995636,
-0.04480670019984245,
-0.1183447614312172,
-0.037500523030757904,
-0.017392054200172424,
-0.06224250793457031,
-0.025395862758159637,
0.0547584593296051,
-0.02883218228816986,
-0.03973718360066414,
0.0011496668448671699,
0.09384800493717194,
0.00953749567270279,
-0.1752052903175354,
0.03303423151373863,
-0.025042934343218803,
-0.10782608389854431,
0.009975161403417587,
0.0022444494534283876,
0.03394931182265282,
0.04408763721585274,
-0.11822668462991714,
-0.30899152159690857,
-0.07652641832828522,
0.05490870401263237,
-0.06516939401626587,
-0.18425025045871735,
-0.13193942606449127,
0.02454492449760437,
-0.09037084132432938,
-0.044885024428367615,
-0.12759265303611755,
-0.028549788519740105,
0.01743689924478531,
0.011519349180161953,
0.10758619755506516,
-0.0106219332665205,
-0.012188062071800232,
-0.1571401208639145,
0.008273907005786896,
-0.20951123535633087,
0.0890483483672142,
-0.019150104373693466,
0.037884220480918884,
-0.032381169497966766,
-0.07404014468193054,
0.030707746744155884,
0.052499737590551376,
-0.01474119070917368,
0.13510210812091827,
-0.15592676401138306,
-0.03691192343831062,
-0.007996266707777977,
-0.13611900806427002,
-0.04786273464560509,
-0.10358831286430359,
-0.04357128217816353,
0.13354332745075226,
0.018664736300706863,
0.15356586873531342,
-0.08709818124771118,
-0.0722038671374321,
0.20489206910133362,
-0.010411538183689117,
-0.12820468842983246,
-0.076752208173275,
0.10165707021951675,
0.021510310471057892,
-0.056606587022542953,
-0.02523270808160305,
-0.1839766949415207,
-0.0152357779443264,
-0.04550420492887497,
-0.047039128839969635,
0.01796751655638218,
-0.010888241231441498,
0.13837894797325134,
0.08494598418474197,
0.05018039792776108,
-0.06086122244596481,
-0.006730288732796907,
0.10779471695423126,
0.08823856711387634,
0.008680110797286034,
0.023406028747558594,
-0.05774238705635071,
0.09552932530641556,
-0.04003755748271942,
-0.0142367510125041,
-0.08283266425132751,
-0.036246106028556824,
-0.026256313547492027,
0.17507147789001465,
0.09440762549638748,
0.2257927656173706,
0.09567736834287643,
0.039160262793302536,
0.031270865350961685,
-0.13181598484516144,
-0.1425403207540512,
-0.0017254541162401438,
0.09020978957414627,
-0.14270411431789398,
-0.04119925573468208,
-0.08974775671958923,
-0.17768175899982452,
-0.12202505767345428,
0.0006432619411498308,
-0.17960017919540405,
0.06390921026468277,
0.05408334732055664,
-0.035177867859601974,
0.03272094577550888,
0.13032332062721252,
-0.011533179320394993,
-0.03967514634132385,
0.0831870287656784,
0.0379033200442791,
-0.041234664618968964,
-0.021742934361100197,
0.11885567009449005,
0.15673065185546875,
0.13124459981918335,
-0.03511447086930275,
0.004914294462651014,
0.07076404243707657,
-0.02309088408946991,
0.06539414077997208,
0.0558244064450264,
0.20973342657089233,
0.188301220536232,
0.038996949791908264,
0.008822928182780743,
-0.07048165798187256,
0.0855446457862854,
-0.0742373839020729,
-0.14302679896354675,
-0.05579735338687897,
0.08729292452335358,
0.016605578362941742,
0.023469142615795135,
0.08711627870798111,
0.024545932188630104,
0.09132762253284454,
0.15968108177185059,
0.01990218088030815,
-0.09659269452095032,
-0.050218869000673294,
0.01175848301500082,
0.027713103219866753,
0.04794301092624664,
-0.04514073207974434,
-0.00937939714640379,
0.017020760104060173,
-0.10303554683923721,
0.031789086759090424,
-0.1413339376449585,
-0.1358717679977417,
0.044326696544885635,
0.003906996920704842,
0.010907664895057678,
0.02786896750330925,
-0.0038291432429105043,
0.019039705395698547,
0.04351753741502762,
-0.06975466758012772,
0.047416772693395615,
-0.024745507165789604,
-0.020031947642564774,
0.03340689837932587,
-0.057257164269685745,
-0.205775648355484,
-0.17696654796600342,
0.00013708483311347663,
-0.09910997003316879,
0.10194740444421768,
0.018308809027075768,
-0.12373185902833939,
0.047737859189510345,
-0.05822649225592613,
0.027574289590120316,
-0.01875593699514866,
-0.049130141735076904,
0.10507171601057053,
0.1525275856256485,
-0.016146350651979446,
0.018018173053860664,
-0.04865182936191559,
-0.10157987475395203,
-0.19632206857204437,
0.0691583976149559,
0.04680244252085686,
0.014610917307436466,
0.10669491440057755,
0.018072687089443207,
0.02367905154824257,
-0.007674071006476879,
-0.016521066427230835,
-0.011659215204417706,
-0.08781040459871292,
0.31909599900245667,
0.04510033503174782,
-0.025173069909214973,
0.02041010931134224,
-0.0043001663871109486,
-0.028083480894565582,
0.03263787180185318,
-0.0985708013176918,
-0.07548979669809341,
-0.08774089068174362,
-0.04367410019040108,
-0.09784720093011856,
0.053299110382795334,
0.05916472524404526,
0.003188040340319276,
-0.07727594673633575,
0.04221395403146744,
0.11369874328374863,
-0.0923808291554451,
-0.07137343287467957,
0.07477962225675583,
0.0972946360707283,
-0.07331304252147675,
0.00012658814375754446,
0.00874367356300354,
0.023951783776283264,
0.037102166563272476,
0.06778035312891006,
-0.03966575115919113,
0.08589404821395874,
-0.19917890429496765,
0.0372927263379097,
0.106058269739151,
0.023754918947815895,
0.0638108178973198,
0.07643651217222214,
-0.1058402881026268,
-0.008500572293996811,
-0.032518330961465836,
-0.21341575682163239,
0.1668180525302887,
0.1355515867471695,
0.06788124144077301,
-0.025637222453951836,
-0.00461410591378808,
-0.0649740919470787,
0.05773647129535675,
0.02723747305572033,
-0.14758841693401337,
0.004883295856416225,
0.06064270809292793,
0.026899009943008423,
0.01614922471344471,
0.07971042394638062,
0.014697225764393806,
-0.1801026314496994,
-0.014406266622245312,
0.10730406641960144,
0.002390873385593295,
0.0053148469887673855,
-0.03175045922398567,
-0.1755964607000351,
0.0751047357916832,
0.004285442177206278,
0.07233936339616776,
-0.1676585078239441,
0.14297930896282196,
-0.10089799761772156,
0.07726949453353882,
-0.004285062663257122,
-0.021311495453119278,
0.02507244050502777,
-0.0541163794696331,
0.15163759887218475,
0.01058570109307766,
-0.021810131147503853,
-0.1200498715043068,
-0.1717042326927185,
-0.019227758049964905,
-0.11788936704397202,
-0.11679866164922714,
0.050424277782440186,
0.062185097485780716,
0.04923136904835701,
-0.061147067695856094,
0.1518532931804657,
-0.047422297298908234,
0.060713399201631546,
-0.06893875449895859,
-0.06755045056343079,
0.03764858841896057,
-0.12588608264923096,
-0.08176055550575256,
0.05573027580976486,
0.19166934490203857,
0.15833087265491486,
-0.02816431224346161,
-0.03472423925995827,
-0.047419581562280655,
-0.006212298292666674,
-0.007802055217325687,
0.0275666993111372,
0.023223137483000755,
0.07315318286418915,
-0.07681374251842499,
-0.11649256944656372,
0.033787861466407776,
-0.06713802367448807,
-0.055589709430933,
-0.015439179725944996,
0.1513158082962036,
0.04671623185276985,
0.07720734924077988,
-0.018946662545204163,
0.03887668624520302,
-0.001724981120787561,
-0.056474871933460236,
0.16197094321250916,
0.03885216265916824,
-0.05193585529923439,
0.06837689876556396,
0.053174007683992386,
0.043745119124650955,
0.03011113777756691,
-0.026783017441630363,
0.206032395362854,
0.1980147808790207,
0.014206883497536182,
0.2175983190536499,
0.03177616000175476,
-0.03772832080721855,
-0.1300560086965561,
-0.065880686044693,
-0.006372632458806038,
0.03559038043022156,
0.08070417493581772,
-0.18207235634326935,
-0.015011128038167953,
-0.05689644813537598,
-0.034518610686063766,
-0.15059494972229004,
-0.28553900122642517,
-0.05957856774330139,
0.20075850188732147,
0.14706264436244965,
0.27519428730010986,
-0.10432573407888412,
0.035197313874959946,
0.02663275972008705,
-0.04912831634283066,
-0.006501141935586929,
0.00018665487004909664,
0.10268618166446686,
-0.15421873331069946,
0.1176437959074974,
0.08486983180046082,
-0.019002694636583328,
0.01058861706405878,
-0.1619086116552353,
0.00936629343777895,
-0.12191236019134521,
0.05354422330856323,
0.1400289237499237,
-0.048128653317689896,
-0.054873593151569366,
0.14033560454845428,
-0.024562934413552284,
-0.22685599327087402,
-0.04648222774267197,
-0.043600670993328094,
-0.010640020482242107,
0.026607351377606392,
-0.1013401448726654,
0.04101909324526787,
0.1330099105834961,
0.009380043484270573,
0.1147187277674675,
0.11749245226383209,
-0.052566803991794586,
0.10792597383260727,
0.2257719188928604,
-0.018785694614052773,
0.04689010605216026,
-0.12743118405342102,
-0.0012336712097749114,
-0.028270328417420387,
0.013657891191542149,
-0.09504974633455276,
-0.09938385337591171,
0.02366873063147068,
0.02872389927506447,
0.009118586778640747,
0.0921793207526207,
-0.029922157526016235,
0.0759170651435852,
0.06817561388015747,
-0.13014446198940277,
-0.16288450360298157,
0.015828335657715797,
-0.007344507612287998,
0.08354310691356659,
0.00027861111448146403,
0.08878035843372345,
-0.11932205408811569,
-0.018093237653374672,
-0.03153328225016594,
-0.03319635987281799,
-0.130486860871315,
-0.07138993591070175,
0.06156524643301964,
0.028095467016100883,
-0.06602972000837326,
0.1398407518863678,
0.026440169662237167,
0.15942534804344177,
0.049197953194379807,
0.012499804608523846,
0.07227300107479095,
-0.05345509201288223,
0.1283530443906784,
0.13818155229091644,
-0.00868943240493536,
-0.05460423603653908,
-0.1013643890619278,
-0.10236792266368866,
0.08925779908895493,
-0.05773641914129257,
0.07476430386304855,
-0.14885357022285461,
-0.06675903499126434,
0.015772046521306038,
0.016141414642333984,
-0.09562095999717712,
0.02571965754032135,
-0.01625603251159191,
-0.18119946122169495,
0.056570518761873245,
-0.048285093158483505,
0.0440407395362854,
-0.06347788125276566,
-0.1110161691904068,
-0.17226378619670868,
0.06091433763504028,
0.08593481779098511,
-0.053876690566539764,
-0.12229149043560028,
0.011023230850696564,
-0.00012518465518951416,
-0.06341652572154999,
-0.05023367330431938,
0.09722746908664703,
-0.11020902544260025,
0.031452205032110214,
-0.012567701749503613,
0.08853451162576675,
-0.03510405123233795,
-0.011538895778357983,
0.044220831245183945,
-0.08039166033267975,
-0.009481523185968399,
0.03534642979502678,
-0.026372017338871956,
-0.04127239063382149,
-0.2689029574394226,
0.0036654395516961813,
0.0341104120016098,
0.02497158572077751,
0.07856601476669312,
0.011906822212040424,
0.021174922585487366,
0.03993808850646019,
-0.15396519005298615,
-0.013395369984209538,
0.14574195444583893,
-0.07689505815505981,
-0.022186370566487312,
0.05703273415565491,
-0.09054436534643173,
0.013882770203053951,
-0.030287226662039757,
0.1345842480659485,
0.023923413828015327,
0.06404478847980499,
-0.0851147472858429,
0.10106813907623291,
-0.1451139897108078,
-0.04998219385743141,
-0.01244612317532301,
0.09761348366737366,
0.07019034773111343,
-0.10272270441055298,
0.014697125181555748,
0.04210108891129494,
0.19416837394237518,
0.016384804621338844,
-0.0356343574821949,
-0.03396720811724663,
0.004015897400677204,
0.22076453268527985,
0.03044266067445278,
0.10457023978233337,
0.07281364500522614,
-0.026583973318338394,
0.12624378502368927,
0.09929762035608292,
0.11280370503664017,
-0.055645186454057693,
0.13904185593128204,
0.04667386785149574,
0.038641396909952164,
0.0614289753139019,
0.06836545467376709,
0.09098632633686066,
-0.0008288522367365658,
0.1138714924454689,
0.013811973854899406,
-0.02422109805047512,
-0.021335409954190254,
0.17759373784065247,
0.10501719266176224,
-0.14769648015499115,
0.029047364369034767,
-0.01258957851678133,
0.039933037012815475,
-0.014194529503583908,
-0.15634691715240479,
-0.07240267097949982,
-0.3315149247646332,
0.1226184144616127,
-0.07119352370500565,
0.019930170848965645,
0.007913772016763687,
-0.037425633519887924,
-0.03296699747443199,
-0.04477746784687042,
0.13151589035987854,
-0.013641550205647945,
-0.006079165264964104,
-0.04815853759646416,
-0.015360191464424133,
-0.11607866734266281,
-0.11200575530529022,
-0.013207737356424332,
-0.13671602308750153,
-0.010119039565324783,
0.05595948174595833,
0.003977729007601738,
0.01821410097181797,
-0.03142618387937546,
0.0024383175186812878,
0.06541839241981506,
-0.05751744285225868,
0.056182678788900375,
0.12097269296646118,
0.08766137808561325,
-0.1058853268623352,
0.031048951670527458,
0.2011747509241104,
0.04359564557671547,
-0.12483977526426315,
0.01449228823184967,
0.1819491684436798,
0.004885740112513304,
0.017068125307559967,
-0.006097703706473112,
-0.0540788508951664,
-0.07554277032613754,
0.1251034289598465,
0.08296554535627365,
-0.09985227137804031,
0.015833314508199692,
-0.0726347416639328,
-0.01594804972410202,
-0.06374675035476685,
0.10130585730075836,
0.09538925439119339,
0.04440245032310486,
-0.10621760785579681,
-0.08487539738416672,
-0.10891728103160858,
0.040588874369859695,
-0.08629853278398514,
-0.07311757653951645,
0.09629398584365845,
-0.07057105004787445,
-0.07029950618743896,
0.025521177798509598,
-0.17978744208812714,
-0.009467960335314274,
0.1711762249469757,
-0.24654000997543335,
-0.0916430801153183,
-0.10857923328876495,
0.14477859437465668,
0.016497576609253883,
0.1013975441455841,
-0.006207061931490898,
-0.007889035157859325,
-0.20577777922153473,
0.024890204891562462,
-0.05293011665344238,
-0.02073732763528824,
0.07814782857894897,
-0.09476397186517715,
0.22629831731319427,
-0.08276885002851486,
0.020940175279974937,
0.012659613974392414,
0.0870661810040474,
-0.030675338581204414,
0.09283176809549332,
-0.03660329803824425,
-0.12576518952846527,
-0.03620953485369682,
0.03001813031733036,
0.013904244638979435,
0.10071761906147003,
0.09772487729787827,
-0.03414725139737129,
0.03389119729399681,
0.09747414290904999,
0.04172342270612717,
-0.023843804374337196,
0.0360250361263752,
-0.17077107727527618,
0.02182629331946373,
-0.018498148769140244,
-0.06935930997133255,
0.03687669709324837,
-0.06603235751390457,
0.1639697551727295,
0.04022442549467087,
0.0670473501086235,
-0.036152735352516174,
0.0073931049555540085,
-0.014454689808189869,
-0.013775371946394444,
-0.026180334389209747,
-0.17259705066680908,
-0.10422050207853317,
-0.1347656100988388,
-0.012701659463346004,
-0.034971047192811966,
0.04591470584273338,
0.023234914988279343,
-0.0003200018545612693,
-0.014577031135559082,
-0.12090865522623062,
0.04360328987240791,
0.11146783083677292,
-0.04631396010518074,
-0.026193076744675636
] |
null | null | transformers | # This model was merged, trained, and so on, thanks to the knowledge I gained from reading Maxime Labonne's course. Special thanks to him!
[Labonne LLM Course](https://github.com/mlabonne/llm-course)
# NeuTrixOmniBe-DPO
NeuTrixOmniBe-DPO is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
MODEL_NAME = "NeuTrixOmniBe-DPO"
yaml_config = """
slices:
- sources:
- model: CultriX/NeuralTrix-7B-dpo
layer_range: [0, 32]
- model: paulml/OmniBeagleSquaredMBX-v3-7B-v2
layer_range: [0, 32]
merge_method: slerp
base_model: CultriX/NeuralTrix-7B-dpo
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
"""
```
It was then trained with DPO using:
* Intel/orca_dpo_pairs
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/NeuTrixOmniBe-DPO"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=128, do_sample=True, temperature=0.5, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` | {"license": "apache-2.0", "tags": ["merge", "mergekit", "#dpo", "MaximeLabonne", "#mergeofmerge"], "base_model": ["CultriX/NeuralTrix-7B-dpo", "paulml/OmniBeagleSquaredMBX-v3-7B-v2"]} | text-generation | Kukedlc/NeuTrixOmniBe-DPO | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"#dpo",
"MaximeLabonne",
"#mergeofmerge",
"base_model:CultriX/NeuralTrix-7B-dpo",
"base_model:paulml/OmniBeagleSquaredMBX-v3-7B-v2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T06:40:32+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit ##dpo #MaximeLabonne ##mergeofmerge #base_model-CultriX/NeuralTrix-7B-dpo #base_model-paulml/OmniBeagleSquaredMBX-v3-7B-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # This model was merged, trained, and so on, thanks to the knowledge I gained from reading Maxime Labonne's course. Special thanks to him!
Labonne LLM Course
!NeuTrixOmniBe
# NeuTrixOmniBe-DPO
NeuTrixOmniBe-DPO is a merge of the following models using LazyMergekit:
## Configuration
It was then trained with DPO using:
* Intel/orca_dpo_pairs
## Usage
| [
"# This model was merged, trained, and so on, thanks to the knowledge I gained from reading Maxime Labonne's course. Special thanks to him! \nLabonne LLM Course\n\n!NeuTrixOmniBe",
"# NeuTrixOmniBe-DPO\n\nNeuTrixOmniBe-DPO is a merge of the following models using LazyMergekit:",
"## Configuration\n\n\n\nIt was then trained with DPO using: \n* Intel/orca_dpo_pairs",
"## Usage"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit ##dpo #MaximeLabonne ##mergeofmerge #base_model-CultriX/NeuralTrix-7B-dpo #base_model-paulml/OmniBeagleSquaredMBX-v3-7B-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# This model was merged, trained, and so on, thanks to the knowledge I gained from reading Maxime Labonne's course. Special thanks to him! \nLabonne LLM Course\n\n!NeuTrixOmniBe",
"# NeuTrixOmniBe-DPO\n\nNeuTrixOmniBe-DPO is a merge of the following models using LazyMergekit:",
"## Configuration\n\n\n\nIt was then trained with DPO using: \n* Intel/orca_dpo_pairs",
"## Usage"
] | [
121,
49,
33,
25,
3
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit ##dpo #MaximeLabonne ##mergeofmerge #base_model-CultriX/NeuralTrix-7B-dpo #base_model-paulml/OmniBeagleSquaredMBX-v3-7B-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# This model was merged, trained, and so on, thanks to the knowledge I gained from reading Maxime Labonne's course. Special thanks to him! \nLabonne LLM Course\n\n!NeuTrixOmniBe# NeuTrixOmniBe-DPO\n\nNeuTrixOmniBe-DPO is a merge of the following models using LazyMergekit:## Configuration\n\n\n\nIt was then trained with DPO using: \n* Intel/orca_dpo_pairs## Usage"
] | [
-0.0936422124505043,
0.09453251212835312,
-0.005848356522619724,
0.056599210947752,
0.04926410689949989,
0.005158677697181702,
0.19733978807926178,
0.08051993697881699,
0.023164553567767143,
0.014000015333294868,
0.09033790975809097,
0.16067618131637573,
0.019364263862371445,
0.11335030198097229,
-0.030290216207504272,
-0.18260151147842407,
0.05174574628472328,
0.01462789811193943,
-0.1394071877002716,
0.062174636870622635,
0.13217799365520477,
-0.03762533515691757,
0.042845118790864944,
-0.03806662559509277,
-0.09399230778217316,
0.02142449840903282,
-0.016852764412760735,
-0.023712895810604095,
0.11289888620376587,
0.04090609773993492,
0.09625085443258286,
0.04826843738555908,
0.04126535728573799,
-0.15829773247241974,
0.03907650336623192,
0.04642130434513092,
0.017489004880189896,
0.0381925143301487,
0.062276002019643784,
-0.0073223719373345375,
0.15003591775894165,
-0.060478903353214264,
0.0376867912709713,
-0.000262698158621788,
-0.10808000713586807,
-0.04257475957274437,
-0.10056987404823303,
0.08103852719068527,
0.030971525236964226,
0.08501750975847244,
0.015422120690345764,
0.1411350816488266,
-0.0034737230744212866,
0.07241557538509369,
0.0993179976940155,
-0.21675293147563934,
-0.05543877184391022,
0.17559221386909485,
0.06499127298593521,
0.039117924869060516,
-0.026621421799063683,
-0.011789828538894653,
0.04194149002432823,
-0.02347090281546116,
0.05544739216566086,
-0.0377831906080246,
0.1855359822511673,
-0.010205197148025036,
-0.12567414343357086,
0.024124663323163986,
0.09970066696405411,
0.035082705318927765,
-0.006718009244650602,
-0.023799695074558258,
-0.06692579388618469,
-0.017920218408107758,
0.009855303913354874,
-0.1561911255121231,
0.06031380593776703,
0.008452446199953556,
0.13756902515888214,
-0.06449121981859207,
-0.04138464108109474,
-0.07628893852233887,
-0.1142362505197525,
0.22575613856315613,
-0.01120761875063181,
-0.0489509291946888,
0.010988656431436539,
0.07225456088781357,
-0.11299654841423035,
-0.04394310712814331,
-0.03050335682928562,
-0.028928667306900024,
0.05218878760933876,
-0.08196830004453659,
-0.06387598067522049,
-0.07302679866552353,
0.07736488431692123,
0.10306911915540695,
0.055079929530620575,
-0.030397294089198112,
0.04216768220067024,
0.03146343678236008,
-0.020929371938109398,
0.015255945734679699,
-0.08960604667663574,
-0.04732602834701538,
0.08391806483268738,
0.0833183005452156,
0.013337474316358566,
0.011074150912463665,
-0.07985319197177887,
-0.03018946759402752,
-0.011420346796512604,
0.04141918569803238,
0.048178814351558685,
0.05225611850619316,
-0.043266359716653824,
-0.08575214445590973,
0.08200963586568832,
-0.11591170728206635,
0.00801179464906454,
-0.010626567527651787,
-0.07352948933839798,
0.1240537092089653,
0.02011452428996563,
0.04361298307776451,
-0.031686682254076004,
0.026006868109107018,
-0.034185297787189484,
-0.03246733546257019,
-0.09899377077817917,
-0.05377838760614395,
-0.0015190341509878635,
0.07492656260728836,
-0.0059277876280248165,
-0.18746411800384521,
-0.19671805202960968,
-0.0071853287518024445,
0.08383040130138397,
-0.006949767004698515,
-0.04571564123034477,
-0.11446525156497955,
-0.015240865759551525,
-0.056194599717855453,
0.03127354755997658,
-0.01686066947877407,
-0.01566794142127037,
0.04373195394873619,
0.00306288106366992,
0.04158198460936546,
-0.18148992955684662,
0.043964970856904984,
-0.027284130454063416,
0.07421587407588959,
-0.15029017627239227,
0.07484883815050125,
-0.05229294300079346,
0.030175115913152695,
-0.09684668481349945,
-0.022847887128591537,
-0.059046387672424316,
-0.018138015642762184,
0.07468822598457336,
0.12821492552757263,
-0.1909465193748474,
-0.06845919042825699,
0.13261742889881134,
-0.10515640676021576,
-0.10744183510541916,
0.11435485631227493,
-0.01877466030418873,
0.09496127814054489,
0.0600757971405983,
0.17493949830532074,
0.15297530591487885,
-0.15512187778949738,
0.014394698664546013,
-0.016751276329159737,
0.07037321478128433,
0.029626818373799324,
0.09282608330249786,
0.05104862526059151,
-0.009997471235692501,
0.02398824878036976,
-0.09007956087589264,
0.022649342194199562,
-0.01347529049962759,
-0.10135243088006973,
-0.025371817871928215,
-0.08569937944412231,
0.06824987381696701,
-0.0376056432723999,
0.011670015752315521,
-0.001805621199309826,
-0.01569332927465439,
0.04558609053492546,
0.14505374431610107,
-0.0631466805934906,
0.0001690175267867744,
-0.05367599427700043,
0.09734395146369934,
0.005339346826076508,
0.029081320390105247,
-0.09492965787649155,
-0.012997163459658623,
-0.004252946469932795,
-0.11197756975889206,
0.027845637872815132,
0.0811682865023613,
0.05852285772562027,
0.05217236652970314,
-0.06223509460687637,
0.025765234604477882,
-0.09459391981363297,
0.06181876361370087,
0.005597667768597603,
-0.12627637386322021,
0.041932545602321625,
-0.05225512385368347,
0.21696029603481293,
-0.18996232748031616,
0.0492706298828125,
-0.05230792239308357,
0.10124117881059647,
0.028604548424482346,
0.010516046546399593,
-0.07944057881832123,
0.05724012479186058,
-0.03102208860218525,
-0.0412033312022686,
0.06030082702636719,
0.03070284239947796,
-0.07900853455066681,
0.006685989443212748,
-0.10834821313619614,
0.0652359127998352,
0.13673938810825348,
-0.013400747440755367,
-0.07736017554998398,
-0.11043408513069153,
-0.016055135056376457,
-0.058810289949178696,
0.09631908684968948,
-0.06049322709441185,
0.0959528461098671,
0.0020489192102104425,
0.0647268146276474,
-0.06852859258651733,
0.009142747148871422,
0.0009765097056515515,
-0.024825433269143105,
-0.04122600331902504,
0.07157939672470093,
0.09728249907493591,
-0.12651488184928894,
0.12032749503850937,
0.20744772255420685,
-0.055748820304870605,
0.06605568528175354,
0.003952408209443092,
-0.0441385917365551,
-0.0752001628279686,
0.04445524141192436,
0.019019154831767082,
0.03808026388287544,
-0.09895284473896027,
0.06311673671007156,
0.007084568031132221,
0.008350634016096592,
0.04872126877307892,
-0.09384468197822571,
-0.01037133764475584,
0.034422483295202255,
-0.031345099210739136,
0.0323745496571064,
0.01686614565551281,
-0.0691286027431488,
0.10496149212121964,
0.05398833379149437,
-0.1253606081008911,
0.05468947812914848,
0.0019157654605805874,
-0.06258957833051682,
0.12311732023954391,
-0.1234976202249527,
-0.18237364292144775,
-0.013030247762799263,
0.028295598924160004,
-0.12917234003543854,
0.004387002903968096,
-0.009245302528142929,
0.03762930631637573,
0.00773930549621582,
-0.05065704137086868,
0.024975823238492012,
-0.0073044197633862495,
-0.03498858958482742,
-0.0030086790211498737,
0.08272117376327515,
-0.03541446104645729,
-0.08830278366804123,
-0.04577771946787834,
-0.009176823310554028,
-0.05699281394481659,
0.05633227899670601,
-0.06833602488040924,
0.024533402174711227,
0.1102340891957283,
0.00554414140060544,
-0.04079238325357437,
0.01691248267889023,
0.10832851380109787,
-0.05571046844124794,
-0.007379055488854647,
0.13046830892562866,
0.011092247441411018,
0.02686242014169693,
0.13835282623767853,
0.028905663639307022,
-0.08900448679924011,
0.029112081974744797,
0.0060972729697823524,
0.018031690269708633,
-0.20093771815299988,
-0.14403778314590454,
-0.08921077102422714,
0.04866338521242142,
0.026863031089305878,
0.02216970920562744,
0.05760858580470085,
-0.007855648174881935,
0.009383377619087696,
0.01887129247188568,
0.042299240827560425,
0.052450116723775864,
0.13797250390052795,
-0.023414669558405876,
0.03869260847568512,
-0.0019039936596527696,
-0.08818359673023224,
0.05941903591156006,
0.10063392668962479,
0.12203953415155411,
0.08629243075847626,
0.1049436628818512,
0.008675241842865944,
0.006208682432770729,
-0.03268655017018318,
0.041854966431856155,
0.06397315859794617,
-0.010664844885468483,
-0.029341215267777443,
-0.09308268874883652,
-0.027779648080468178,
0.05435432121157646,
0.00018493655079510063,
0.017657840624451637,
-0.03914029896259308,
0.028485333546996117,
0.09446152299642563,
0.19058816134929657,
0.003447027411311865,
-0.23922346532344818,
-0.0447692945599556,
-0.03693370521068573,
-0.009490874595940113,
0.001752298790961504,
0.014974094927310944,
-0.022401487454771996,
-0.0560552179813385,
0.05331163480877876,
-0.014007369056344032,
0.04512519761919975,
-0.08034124225378036,
0.03885813057422638,
-0.06917433440685272,
0.055711835622787476,
0.029209265485405922,
0.08139166235923767,
-0.366968035697937,
0.19020819664001465,
-0.018813060596585274,
0.038189247250556946,
0.018336288630962372,
-0.004072168841958046,
0.052921224385499954,
0.15201804041862488,
0.10547995567321777,
0.02355130948126316,
0.0632166936993599,
0.01353145856410265,
-0.1562519669532776,
-0.004775474313646555,
0.03548244386911392,
-0.1108478307723999,
0.02150268852710724,
-0.023642925545573235,
-0.04505343735218048,
0.01840920001268387,
0.10160647332668304,
-0.13966873288154602,
-0.10691098123788834,
0.12512515485286713,
-0.017064593732357025,
0.037504855543375015,
-0.0730585902929306,
-0.060115113854408264,
-0.14112043380737305,
0.25710591673851013,
0.02677163854241371,
0.01704135350883007,
-0.057940226048231125,
0.02179892174899578,
-0.032699715346097946,
-0.04115773364901543,
0.019559942185878754,
0.02545633167028427,
0.07576463371515274,
-0.05930601432919502,
-0.10817268490791321,
0.08886416256427765,
-0.07810550183057785,
-0.0009039626456797123,
-0.06514006853103638,
0.06402838230133057,
0.01644682139158249,
-0.01285957358777523,
0.028800584375858307,
-0.022488534450531006,
-0.030146639794111252,
-0.03209596872329712,
-0.01865510828793049,
0.12657208740711212,
-0.03775635361671448,
0.033918432891368866,
-0.09175162017345428,
-0.10036467015743256,
-0.048920635133981705,
-0.06137075647711754,
0.11995117366313934,
0.21296410262584686,
-0.002305538859218359,
0.012838799506425858,
0.10878846049308777,
-0.07850311696529388,
-0.2371899038553238,
0.010680598206818104,
0.0331881158053875,
-0.017030207440257072,
-0.01887848787009716,
-0.14439326524734497,
0.04889203608036041,
0.11845897883176804,
0.0041709644719958305,
0.07658874243497849,
-0.2642945647239685,
-0.10256048291921616,
0.0467747338116169,
0.10801875591278076,
0.14819172024726868,
-0.06974808871746063,
-0.01781982183456421,
-0.06439486145973206,
-0.109919473528862,
0.19750787317752838,
-0.048261456191539764,
0.0656375139951706,
0.020342105999588966,
0.03343928977847099,
0.04037300869822502,
-0.03030673786997795,
0.18893083930015564,
-0.05630282312631607,
0.016672950237989426,
-0.07658146321773529,
-0.045948326587677,
-0.01637125387787819,
-0.03685912489891052,
-0.0003713444748427719,
0.015406687743961811,
0.02026018127799034,
0.02474329248070717,
-0.06489302217960358,
0.011027621105313301,
0.10027719289064407,
-0.022607453167438507,
-0.10894876718521118,
0.026443589478731155,
0.13241493701934814,
0.026738278567790985,
0.030740149319171906,
-0.05326269939541817,
-0.05022600293159485,
0.05266117677092552,
0.0827256515622139,
0.08378580957651138,
-0.027067476883530617,
0.004292423836886883,
-0.010287100449204445,
-0.023069974035024643,
0.0701136514544487,
-0.011373423039913177,
0.01815789006650448,
0.14304053783416748,
0.010770710185170174,
0.0786953717470169,
0.044550999999046326,
-0.0599302314221859,
-0.05300746113061905,
0.037227049469947815,
-0.18361394107341766,
-0.12132588773965836,
-0.026728613302111626,
0.06210454925894737,
0.02175983227789402,
0.05108311027288437,
0.1526447981595993,
-0.1110895425081253,
-0.00025170721346512437,
0.04770951345562935,
-0.0061233858577907085,
-0.14213047921657562,
0.07290738821029663,
0.00004870227712672204,
0.006324521731585264,
-0.016972385346889496,
0.04155523329973221,
0.07984547317028046,
-0.14704841375350952,
-0.03408563882112503,
-0.01393384300172329,
-0.06429368257522583,
-0.09558776766061783,
-0.0738491415977478,
0.176529198884964,
-0.013351581059396267,
-0.05067647993564606,
-0.08190911263227463,
-0.07013800740242004,
0.013133962638676167,
0.0018002891447395086,
0.0843951627612114,
0.04295152798295021,
-0.010855414904654026,
0.03133299946784973,
-0.08315093070268631,
0.07509921491146088,
-0.020711882039904594,
0.09235168993473053,
-0.060729384422302246,
0.018284521996974945,
-0.06591664999723434,
0.05875306576490402,
-0.011860709637403488,
0.0016847208607941866,
-0.1321386992931366,
-0.014755737036466599,
-0.01045825332403183,
-0.031212395057082176,
-0.050450704991817474,
0.04689071699976921,
0.030016247183084488,
0.026345526799559593,
0.014611533842980862,
-0.0077878995798528194,
-0.06331127882003784,
-0.020181629806756973,
0.011369004845619202,
0.03278996795415878,
-0.04295245185494423,
-0.06021197885274887,
-0.0004335109842941165,
-0.07240187376737595,
0.09774138778448105,
0.07556808739900589,
0.03758811578154564,
-0.03849560767412186,
-0.1879742294549942,
0.03579483926296234,
-0.007615695707499981,
0.11807061731815338,
0.014455444179475307,
-0.17614032328128815,
0.008329149335622787,
0.049072958528995514,
-0.03835732489824295,
0.001637193257920444,
0.06742511689662933,
-0.0873735174536705,
-0.04406285285949707,
-0.052732404321432114,
-0.06659170240163803,
-0.024589860811829567,
-0.003974870778620243,
0.022494034841656685,
0.07297004014253616,
0.06239006668329239,
-0.031059935688972473,
0.05049784108996391,
-0.07534191012382507,
-0.012025373056530952,
0.01436437014490366,
-0.08292695879936218,
0.03513646498322487,
-0.054983753710985184,
0.044761497527360916,
-0.006441326811909676,
0.07621055096387863,
0.027232719585299492,
-0.09107474982738495,
0.01686645671725273,
-0.19275690615177155,
0.040192075073719025,
0.038948312401771545,
0.16904893517494202,
0.08471028506755829,
0.03618193790316582,
-0.05710557848215103,
0.06128610670566559,
0.029360469430685043,
0.16830399632453918,
0.13458958268165588,
0.13501514494419098,
-0.010898995213210583,
0.03212166205048561,
0.07775788754224777,
-0.01851074770092964,
-0.039606980979442596,
0.00833484809845686,
-0.007172001991420984,
0.04698070511221886,
-0.04908721521496773,
0.11527212709188461,
0.08536510914564133,
-0.16701450943946838,
0.04564886540174484,
-0.022544417530298233,
-0.043555114418268204,
-0.0788470208644867,
-0.08579342812299728,
-0.048214443027973175,
-0.11673939228057861,
-0.04375728219747543,
-0.061178795993328094,
-0.022589385509490967,
-0.06861602514982224,
0.05121724307537079,
-0.05938519164919853,
0.09987670928239822,
-0.04944859445095062,
-0.016641147434711456,
0.09775765985250473,
-0.023350410163402557,
-0.0667184367775917,
-0.1282467544078827,
-0.06798641383647919,
-0.030752452090382576,
0.029696127399802208,
-0.015736214816570282,
0.013532574288547039,
0.013008909299969673,
0.02042221836745739,
-0.036766890436410904,
-0.030218912288546562,
-0.02185720019042492,
-0.015912940725684166,
-0.02534325048327446,
0.1561124622821808,
0.034996647387742996,
-0.045800160616636276,
0.03938085585832596,
0.15208463370800018,
0.0016544106183573604,
-0.11811018735170364,
-0.1153634637594223,
0.1387045979499817,
-0.016801409423351288,
0.08244974911212921,
-0.013498466461896896,
-0.02247493714094162,
-0.0060487003065645695,
0.16640527546405792,
0.1901981085538864,
-0.09106774628162384,
0.028876785188913345,
0.07621381431818008,
0.009862392209470272,
-0.02061500772833824,
0.07222886383533478,
0.09722842276096344,
0.10626597702503204,
-0.051903136074543,
0.0038746166974306107,
-0.046150341629981995,
0.005307368468493223,
-0.06545627862215042,
0.028668878600001335,
0.05221482366323471,
0.0006520695169456303,
-0.011557198129594326,
0.07662706077098846,
-0.04679900407791138,
-0.11437658220529556,
0.014291996136307716,
-0.1304803341627121,
-0.08892030268907547,
-0.060227058827877045,
0.014243625104427338,
-0.0555020235478878,
0.04693774878978729,
-0.07415010035037994,
-0.03630378097295761,
0.1403215229511261,
-0.013106115162372589,
-0.004115442745387554,
-0.07626622915267944,
0.05420863628387451,
0.0771532654762268,
0.1108253076672554,
-0.04274372383952141,
0.13051946461200714,
0.08140280097723007,
0.05044415965676308,
-0.08351796120405197,
0.05719928815960884,
0.05840538069605827,
-0.056393831968307495,
0.0668766051530838,
-0.02956484630703926,
-0.06750064343214035,
0.03845614939928055,
0.04481261596083641,
0.005773314740508795,
0.014355910941958427,
0.14135392010211945,
-0.08352077752351761,
-0.06590989977121353,
0.15699712932109833,
-0.10112302005290985,
0.1333397775888443,
0.13029928505420685,
-0.03666482865810394,
0.02855260856449604,
-0.0769607350230217,
0.0676107257604599,
0.04072390869259834,
0.03284134715795517,
-0.04299352318048477,
-0.21828550100326538,
-0.023998402059078217,
-0.01790751703083515,
0.09056060761213303,
-0.19576768577098846,
-0.09442811459302902,
-0.04329370707273483,
-0.03848458081483841,
-0.0448007769882679,
0.031241239979863167,
0.12211816757917404,
-0.02587316371500492,
-0.0659903809428215,
-0.10769285261631012,
-0.08184801787137985,
0.09657733887434006,
-0.06598998606204987,
-0.09791144728660583
] |
null | null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ai4privacy_v2_adapter_it
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0807
- Overall Precision: 0.8556
- Overall Recall: 0.8901
- Overall F1: 0.8725
- Overall Accuracy: 0.9669
- Accountname F1: 0.9869
- Accountnumber F1: 0.9762
- Age F1: 0.9719
- Amount F1: 0.7971
- Bic F1: 0.9536
- Bitcoinaddress F1: 0.9092
- Buildingnumber F1: 0.8371
- City F1: 0.8562
- Companyname F1: 0.9699
- County F1: 0.8920
- Creditcardcvv F1: 0.8794
- Creditcardissuer F1: 0.9681
- Creditcardnumber F1: 0.8276
- Currency F1: 0.5914
- Currencycode F1: 0.6059
- Currencyname F1: 0.0
- Currencysymbol F1: 0.8541
- Date F1: 0.6932
- Dob F1: 0.4620
- Email F1: 0.9911
- Ethereumaddress F1: 0.9856
- Eyecolor F1: 0.9257
- Firstname F1: 0.8746
- Gender F1: 0.9656
- Height F1: 0.9689
- Iban F1: 0.9936
- Ip F1: 0.0
- Ipv4 F1: 0.8059
- Ipv6 F1: 0.7656
- Jobarea F1: 0.9611
- Jobtitle F1: 0.9633
- Jobtype F1: 0.9625
- Lastname F1: 0.8054
- Litecoinaddress F1: 0.7454
- Mac F1: 0.9646
- Maskednumber F1: 0.7425
- Middlename F1: 0.4467
- Nearbygpscoordinate F1: 0.9989
- Ordinaldirection F1: 0.9868
- Password F1: 0.9839
- Phoneimei F1: 0.9878
- Phonenumber F1: 0.9787
- Pin F1: 0.6881
- Prefix F1: 0.9727
- Secondaryaddress F1: 0.9697
- Sex F1: 0.9858
- Ssn F1: 0.9778
- State F1: 0.8914
- Street F1: 0.8813
- Time F1: 0.9567
- Url F1: 0.9915
- Useragent F1: 0.9769
- Username F1: 0.9686
- Vehiclevin F1: 0.9635
- Vehiclevrm F1: 0.9747
- Zipcode F1: 0.8485
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Accountname F1 | Accountnumber F1 | Age F1 | Amount F1 | Bic F1 | Bitcoinaddress F1 | Buildingnumber F1 | City F1 | Companyname F1 | County F1 | Creditcardcvv F1 | Creditcardissuer F1 | Creditcardnumber F1 | Currency F1 | Currencycode F1 | Currencyname F1 | Currencysymbol F1 | Date F1 | Dob F1 | Email F1 | Ethereumaddress F1 | Eyecolor F1 | Firstname F1 | Gender F1 | Height F1 | Iban F1 | Ip F1 | Ipv4 F1 | Ipv6 F1 | Jobarea F1 | Jobtitle F1 | Jobtype F1 | Lastname F1 | Litecoinaddress F1 | Mac F1 | Maskednumber F1 | Middlename F1 | Nearbygpscoordinate F1 | Ordinaldirection F1 | Password F1 | Phoneimei F1 | Phonenumber F1 | Pin F1 | Prefix F1 | Secondaryaddress F1 | Sex F1 | Ssn F1 | State F1 | Street F1 | Time F1 | Url F1 | Useragent F1 | Username F1 | Vehiclevin F1 | Vehiclevrm F1 | Zipcode F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
| 0.7047 | 1.0 | 1275 | 0.3394 | 0.3552 | 0.4679 | 0.4038 | 0.8991 | 0.7758 | 0.6518 | 0.8829 | 0.1009 | 0.3687 | 0.7553 | 0.3720 | 0.0 | 0.1118 | 0.0698 | 0.0 | 0.0 | 0.5544 | 0.0 | 0.0 | 0.0 | 0.2279 | 0.3929 | 0.0953 | 0.9181 | 0.8440 | 0.0 | 0.3652 | 0.1346 | 0.1034 | 0.8137 | 0.0 | 0.7184 | 0.6402 | 0.0143 | 0.5859 | 0.0 | 0.0661 | 0.0 | 0.7596 | 0.0112 | 0.0 | 0.9590 | 0.0 | 0.7307 | 0.9290 | 0.4443 | 0.0 | 0.0132 | 0.5173 | 0.6060 | 0.1941 | 0.0113 | 0.1307 | 0.7603 | 0.9491 | 0.8830 | 0.0048 | 0.4413 | 0.1774 | 0.3969 |
| 0.16 | 2.0 | 2550 | 0.1239 | 0.7404 | 0.8016 | 0.7698 | 0.9550 | 0.9820 | 0.9461 | 0.9464 | 0.4123 | 0.6098 | 0.8438 | 0.7318 | 0.5930 | 0.9095 | 0.6646 | 0.7774 | 0.9154 | 0.6495 | 0.4255 | 0.3522 | 0.0 | 0.6151 | 0.5260 | 0.1902 | 0.9729 | 0.9601 | 0.6775 | 0.8040 | 0.7830 | 0.8411 | 0.9417 | 0.0 | 0.8056 | 0.7966 | 0.8342 | 0.9225 | 0.7701 | 0.6583 | 0.5681 | 0.9002 | 0.6007 | 0.0633 | 0.9935 | 0.9803 | 0.9649 | 0.9900 | 0.9462 | 0.0103 | 0.9599 | 0.9538 | 0.9509 | 0.9607 | 0.7129 | 0.7718 | 0.9339 | 0.9847 | 0.9481 | 0.8711 | 0.9539 | 0.8225 | 0.6985 |
| 0.1169 | 3.0 | 3825 | 0.1027 | 0.7616 | 0.8481 | 0.8025 | 0.9573 | 0.9836 | 0.9518 | 0.9628 | 0.5499 | 0.9358 | 0.9409 | 0.7946 | 0.7442 | 0.9514 | 0.8136 | 0.8579 | 0.9422 | 0.7882 | 0.5091 | 0.5460 | 0.0 | 0.6629 | 0.7015 | 0.3203 | 0.9834 | 0.9885 | 0.8499 | 0.8486 | 0.9179 | 0.9423 | 0.9465 | 0.0086 | 0.8009 | 0.3113 | 0.9312 | 0.9444 | 0.9125 | 0.7483 | 0.7813 | 0.9513 | 0.6076 | 0.3184 | 0.9957 | 0.9837 | 0.9646 | 0.9911 | 0.9541 | 0.3744 | 0.9662 | 0.9657 | 0.9781 | 0.9667 | 0.7927 | 0.8152 | 0.9317 | 0.9890 | 0.9595 | 0.9338 | 0.9545 | 0.9578 | 0.7431 |
| 0.0928 | 4.0 | 5100 | 0.0893 | 0.8261 | 0.8714 | 0.8482 | 0.9647 | 0.9861 | 0.9574 | 0.9691 | 0.6684 | 0.9497 | 0.9340 | 0.8159 | 0.8093 | 0.9498 | 0.8534 | 0.87 | 0.9569 | 0.7950 | 0.5274 | 0.5591 | 0.0 | 0.7556 | 0.5915 | 0.4577 | 0.9893 | 0.9828 | 0.8894 | 0.8577 | 0.9431 | 0.9630 | 0.9801 | 0.0 | 0.8068 | 0.8130 | 0.9414 | 0.9530 | 0.9425 | 0.7637 | 0.8190 | 0.9515 | 0.6809 | 0.4021 | 0.9989 | 0.9868 | 0.9747 | 0.9878 | 0.9736 | 0.6169 | 0.9639 | 0.9649 | 0.9851 | 0.9778 | 0.8287 | 0.8536 | 0.9459 | 0.9890 | 0.9567 | 0.9385 | 0.9408 | 0.9531 | 0.8158 |
| 0.0827 | 5.0 | 6375 | 0.0821 | 0.8531 | 0.8845 | 0.8685 | 0.9666 | 0.9885 | 0.9687 | 0.9712 | 0.7602 | 0.9500 | 0.9053 | 0.8303 | 0.8370 | 0.9699 | 0.8782 | 0.8691 | 0.9709 | 0.8098 | 0.5908 | 0.6369 | 0.0 | 0.8270 | 0.6587 | 0.4759 | 0.9881 | 0.9871 | 0.9303 | 0.8716 | 0.9633 | 0.9727 | 0.9810 | 0.0 | 0.8149 | 0.8104 | 0.9588 | 0.9655 | 0.9573 | 0.8000 | 0.7339 | 0.9690 | 0.7423 | 0.4433 | 0.9989 | 0.9868 | 0.9831 | 0.9944 | 0.9787 | 0.6794 | 0.9735 | 0.9681 | 0.9858 | 0.9787 | 0.8805 | 0.8731 | 0.9544 | 0.9907 | 0.9740 | 0.9616 | 0.9536 | 0.9650 | 0.8385 |
| 0.077 | 6.0 | 7650 | 0.0807 | 0.8556 | 0.8901 | 0.8725 | 0.9669 | 0.9869 | 0.9762 | 0.9719 | 0.7971 | 0.9536 | 0.9092 | 0.8371 | 0.8562 | 0.9699 | 0.8920 | 0.8794 | 0.9681 | 0.8276 | 0.5914 | 0.6059 | 0.0 | 0.8541 | 0.6932 | 0.4620 | 0.9911 | 0.9856 | 0.9257 | 0.8746 | 0.9656 | 0.9689 | 0.9936 | 0.0 | 0.8059 | 0.7656 | 0.9611 | 0.9633 | 0.9625 | 0.8054 | 0.7454 | 0.9646 | 0.7425 | 0.4467 | 0.9989 | 0.9868 | 0.9839 | 0.9878 | 0.9787 | 0.6881 | 0.9727 | 0.9697 | 0.9858 | 0.9778 | 0.8914 | 0.8813 | 0.9567 | 0.9915 | 0.9769 | 0.9686 | 0.9635 | 0.9747 | 0.8485 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-multilingual-cased", "model-index": [{"name": "ai4privacy_v2_adapter_it", "results": []}]} | null | Isotonic/ai4privacy_v2_adapter_it | [
"safetensors",
"generated_from_trainer",
"base_model:distilbert-base-multilingual-cased",
"license:apache-2.0",
"region:us"
] | 2024-02-11T06:40:36+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-distilbert-base-multilingual-cased #license-apache-2.0 #region-us
| ai4privacy\_v2\_adapter\_it
===========================
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0807
* Overall Precision: 0.8556
* Overall Recall: 0.8901
* Overall F1: 0.8725
* Overall Accuracy: 0.9669
* Accountname F1: 0.9869
* Accountnumber F1: 0.9762
* Age F1: 0.9719
* Amount F1: 0.7971
* Bic F1: 0.9536
* Bitcoinaddress F1: 0.9092
* Buildingnumber F1: 0.8371
* City F1: 0.8562
* Companyname F1: 0.9699
* County F1: 0.8920
* Creditcardcvv F1: 0.8794
* Creditcardissuer F1: 0.9681
* Creditcardnumber F1: 0.8276
* Currency F1: 0.5914
* Currencycode F1: 0.6059
* Currencyname F1: 0.0
* Currencysymbol F1: 0.8541
* Date F1: 0.6932
* Dob F1: 0.4620
* Email F1: 0.9911
* Ethereumaddress F1: 0.9856
* Eyecolor F1: 0.9257
* Firstname F1: 0.8746
* Gender F1: 0.9656
* Height F1: 0.9689
* Iban F1: 0.9936
* Ip F1: 0.0
* Ipv4 F1: 0.8059
* Ipv6 F1: 0.7656
* Jobarea F1: 0.9611
* Jobtitle F1: 0.9633
* Jobtype F1: 0.9625
* Lastname F1: 0.8054
* Litecoinaddress F1: 0.7454
* Mac F1: 0.9646
* Maskednumber F1: 0.7425
* Middlename F1: 0.4467
* Nearbygpscoordinate F1: 0.9989
* Ordinaldirection F1: 0.9868
* Password F1: 0.9839
* Phoneimei F1: 0.9878
* Phonenumber F1: 0.9787
* Pin F1: 0.6881
* Prefix F1: 0.9727
* Secondaryaddress F1: 0.9697
* Sex F1: 0.9858
* Ssn F1: 0.9778
* State F1: 0.8914
* Street F1: 0.8813
* Time F1: 0.9567
* Url F1: 0.9915
* Useragent F1: 0.9769
* Username F1: 0.9686
* Vehiclevin F1: 0.9635
* Vehiclevrm F1: 0.9747
* Zipcode F1: 0.8485
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 6
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.2\n* num\\_epochs: 6",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#safetensors #generated_from_trainer #base_model-distilbert-base-multilingual-cased #license-apache-2.0 #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.2\n* num\\_epochs: 6",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
43,
116,
4,
33
] | [
"passage: TAGS\n#safetensors #generated_from_trainer #base_model-distilbert-base-multilingual-cased #license-apache-2.0 #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: 0.2\n* num\\_epochs: 6### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.10187412798404694,
0.030679218471050262,
-0.0013444607611745596,
0.1160336583852768,
0.1429014801979065,
0.017121508717536926,
0.15973567962646484,
0.08045288175344467,
-0.08108053356409073,
0.04906095936894417,
0.10214482992887497,
0.10047328472137451,
0.007974560372531414,
0.14775563776493073,
-0.055213019251823425,
-0.21338608860969543,
0.028125574812293053,
-0.03250459209084511,
-0.030238425359129906,
0.11835934221744537,
0.08213379234075546,
-0.1251591145992279,
0.07268892973661423,
-0.04611899331212044,
-0.18063537776470184,
0.024436382576823235,
0.020954817533493042,
-0.03538532555103302,
0.13986875116825104,
-0.01171921193599701,
0.13234581053256989,
0.019298261031508446,
0.12444368004798889,
-0.21908323466777802,
0.007812121883034706,
0.06283790618181229,
0.00447246665135026,
0.052148833870887756,
0.04673387482762337,
-0.04096323251724243,
0.09398963302373886,
-0.11819085478782654,
0.047543931752443314,
0.01864491030573845,
-0.13088130950927734,
-0.20869393646717072,
-0.09640226513147354,
-0.00588263152167201,
0.07039199024438858,
0.06772059202194214,
-0.010605166666209698,
0.13860014081001282,
-0.07860761135816574,
0.09359829872846603,
0.2420767843723297,
-0.3120308220386505,
-0.06554342061281204,
0.07985424995422363,
0.026211777701973915,
0.11015909165143967,
-0.10823193937540054,
-0.01632663421332836,
0.07260463386774063,
0.034968916326761246,
0.1198611631989479,
-0.03744184970855713,
-0.16362491250038147,
0.009028006345033646,
-0.14546474814414978,
0.016929417848587036,
0.0729445368051529,
0.04524305462837219,
-0.0647595226764679,
-0.0003682644455693662,
-0.07533033192157745,
-0.11372021585702896,
-0.05971216782927513,
-0.011576859280467033,
0.07887061685323715,
-0.026798635721206665,
-0.040520600974559784,
-0.0074644992128014565,
-0.08281680196523666,
-0.09672312438488007,
-0.05297171324491501,
0.21604661643505096,
0.04335497319698334,
0.02272411808371544,
-0.015504708513617516,
0.09832513332366943,
-0.08233404904603958,
-0.1332654058933258,
0.023352252319455147,
0.01455307099968195,
-0.0033688400872051716,
-0.04156474769115448,
-0.061083778738975525,
-0.036882203072309494,
0.050431132316589355,
0.13157320022583008,
-0.12769843637943268,
0.06121893972158432,
-0.017977187409996986,
0.019341306760907173,
-0.1056613177061081,
0.13559387624263763,
-0.04505596309900284,
-0.045998748391866684,
0.023810142651200294,
0.0871397852897644,
0.05051165074110031,
0.0003699090739246458,
-0.07955963164567947,
0.01991676725447178,
0.09651338309049606,
0.036653611809015274,
-0.09855599701404572,
0.046817027032375336,
-0.04771978035569191,
0.029833892360329628,
-0.013342073187232018,
-0.11546868085861206,
0.03772522136569023,
0.010685778222978115,
-0.06555292010307312,
-0.06079921871423721,
0.010496538132429123,
0.029117101803421974,
0.015889625996351242,
0.10030989348888397,
-0.07249799370765686,
0.05980226397514343,
-0.09799828380346298,
-0.12252147495746613,
-0.0036658106837421656,
-0.04371136054396629,
0.010889687575399876,
-0.0867731124162674,
-0.18370398879051208,
-0.01217692345380783,
0.05509883165359497,
-0.049958936870098114,
0.02284936234354973,
-0.07073844224214554,
-0.08572685718536377,
0.0032185425516217947,
-0.01774023286998272,
0.09863420575857162,
-0.08598985522985458,
0.0893569216132164,
0.044873498380184174,
0.06691848486661911,
-0.08721227198839188,
0.017200028523802757,
-0.10702861100435257,
0.020250901579856873,
-0.2410125583410263,
0.03870173916220665,
-0.08319772779941559,
0.061564475297927856,
-0.08133149147033691,
-0.08456069231033325,
0.0013841186882928014,
-0.0022069814149290323,
0.10910408198833466,
0.1313134729862213,
-0.21061120927333832,
-0.03353289142251015,
0.19395455718040466,
-0.11305401474237442,
-0.10647261142730713,
0.11584670841693878,
-0.05658898130059242,
0.048649806529283524,
0.07774394750595093,
0.21565312147140503,
-0.009402076713740826,
-0.1246015727519989,
0.022448047995567322,
-0.021263420581817627,
0.058995019644498825,
-0.010039332322776318,
0.049846336245536804,
-0.0015912919770926237,
-0.03437616303563118,
0.02210399881005287,
-0.03791099786758423,
0.05389143154025078,
-0.10492052137851715,
-0.07912147790193558,
-0.05545081943273544,
-0.11311405897140503,
0.03535076230764389,
0.03389681875705719,
0.051395807415246964,
-0.13958771526813507,
-0.05322279408574104,
0.055043380707502365,
0.08093133568763733,
-0.060362860560417175,
0.03581039607524872,
-0.0545298270881176,
0.04821208491921425,
-0.018208075314760208,
-0.031168092042207718,
-0.163583442568779,
-0.057429809123277664,
0.0287680272012949,
0.012608819641172886,
0.029026024043560028,
-0.05935268849134445,
0.07774682343006134,
0.10005880892276764,
-0.08166182041168213,
-0.015355591662228107,
-0.028337562456727028,
0.010842169634997845,
-0.11548799276351929,
-0.23115329444408417,
0.001922020222991705,
-0.03739386796951294,
0.10933899134397507,
-0.19439469277858734,
0.03181134909391403,
-0.04087665677070618,
0.058838941156864166,
0.016091125085949898,
-0.004191585350781679,
-0.031706299632787704,
0.08648613840341568,
-0.009475902654230595,
-0.06639626622200012,
0.049096040427684784,
-0.008392834104597569,
-0.07614262402057648,
-0.04747401177883148,
-0.11017104238271713,
0.15183338522911072,
0.12781848013401031,
-0.04964880645275116,
-0.08458179980516434,
-0.00756498659029603,
-0.038066282868385315,
-0.030505526810884476,
-0.049055296927690506,
0.05264664813876152,
0.12687160074710846,
-0.009575819596648216,
0.1149040088057518,
-0.08967261761426926,
0.001249032444320619,
0.0020429997239261866,
-0.04460212588310242,
0.04885711148381233,
0.09763369709253311,
0.07266221195459366,
-0.07624158263206482,
0.11115501075983047,
0.17209210991859436,
-0.09764066338539124,
0.08902613073587418,
-0.05550828203558922,
-0.056128885596990585,
-0.02873220108449459,
0.025659756734967232,
-0.019527621567249298,
0.13692831993103027,
-0.05095899850130081,
0.02972654066979885,
-0.012664400041103363,
0.04440639168024063,
0.007708957884460688,
-0.2254326492547989,
-0.04008178412914276,
-0.005182106047868729,
-0.07845667749643326,
-0.043913595378398895,
-0.03208582475781441,
0.004912740550935268,
0.10303980112075806,
-0.03523731976747513,
-0.09410788118839264,
0.011572781018912792,
-0.007879379205405712,
-0.06730230152606964,
0.2214122861623764,
-0.11182189732789993,
-0.0550137534737587,
-0.07416889071464539,
-0.06283263862133026,
-0.06137670949101448,
0.004858510568737984,
0.06388486921787262,
-0.09294839203357697,
-0.03166256844997406,
-0.11155234277248383,
0.022949445992708206,
0.05836646631360054,
0.02567882090806961,
0.006993964314460754,
-0.011101480573415756,
0.08272543549537659,
-0.12243492156267166,
-0.008360461331903934,
-0.05853590369224548,
-0.06824134290218353,
0.05350447818636894,
0.06765197962522507,
0.09914514422416687,
0.12348243594169617,
-0.020305586978793144,
-0.01490966696292162,
-0.028729675337672234,
0.2593331038951874,
-0.026394637301564217,
-0.025180116295814514,
0.10077665001153946,
-0.006112057715654373,
0.057471878826618195,
0.15525731444358826,
0.07819737493991852,
-0.13592727482318878,
0.026456592604517937,
0.0369684174656868,
-0.023406021296977997,
-0.22154591977596283,
-0.03579966723918915,
-0.018349381163716316,
-0.04755324870347977,
0.04498908668756485,
0.02495490573346615,
-0.038698647171258926,
0.04436240717768669,
0.04384096711874008,
0.027797887101769447,
-0.003069529077038169,
0.04799717664718628,
0.04778677970170975,
0.050859998911619186,
0.10814729332923889,
-0.04287821799516678,
-0.046807482838630676,
0.04066246747970581,
-0.009608656167984009,
0.21699444949626923,
0.005810425616800785,
0.06572507321834564,
0.06107763200998306,
0.19868087768554688,
-0.02206355147063732,
0.09733572602272034,
-0.0006739122327417135,
-0.047008369117975235,
-0.016746222972869873,
-0.06401348859071732,
-0.01393013633787632,
0.02739568240940571,
-0.1303001195192337,
0.059295956045389175,
-0.09952487051486969,
0.013439351692795753,
0.0829562246799469,
0.2640901803970337,
0.036381617188453674,
-0.29263290762901306,
-0.048872120678424835,
0.021626340225338936,
-0.013446420431137085,
-0.016168473288416862,
0.03280145674943924,
0.14404428005218506,
-0.0386531800031662,
0.06212439015507698,
-0.04775754362344742,
0.07173269242048264,
0.030325282365083694,
0.03427433595061302,
0.01992541365325451,
0.12733688950538635,
-0.0167823638767004,
0.034263040870428085,
-0.28469181060791016,
0.2920030951499939,
0.026281842961907387,
0.10370554774999619,
-0.03026283159852028,
-0.01171559002250433,
0.033426471054553986,
0.08325494080781937,
0.0647430494427681,
-0.01241295412182808,
-0.09808770567178726,
-0.17523208260536194,
-0.05918509140610695,
0.05760037153959274,
0.1387293040752411,
0.012899922206997871,
0.10356532037258148,
-0.012693062424659729,
0.003228368703275919,
0.08561266213655472,
-0.05131688341498375,
-0.15803992748260498,
-0.03989380598068237,
-0.05457967519760132,
0.05558229237794876,
-0.018026672303676605,
-0.08029235899448395,
-0.09224628657102585,
-0.1134331226348877,
0.09347211569547653,
0.011332010850310326,
-0.018518565222620964,
-0.09933041781187057,
0.05217953398823738,
0.10263659805059433,
-0.059982381761074066,
0.04053277149796486,
0.02420951798558235,
0.022471796721220016,
0.033748045563697815,
-0.04960692673921585,
0.12658707797527313,
-0.07414305210113525,
-0.15287011861801147,
-0.05424218252301216,
0.09901385754346848,
0.048931632190942764,
0.039069775491952896,
-0.015992429107427597,
0.008708668872714043,
0.008845318108797073,
-0.1047578752040863,
0.002305623609572649,
-0.023259509354829788,
0.061357282102108,
0.058755360543727875,
-0.08934332430362701,
-0.036723170429468155,
-0.058454662561416626,
-0.021301886066794395,
0.14009608328342438,
0.33948245644569397,
-0.07420827448368073,
0.02242242358624935,
0.09926644712686539,
-0.0597335584461689,
-0.18654745817184448,
0.05305619165301323,
0.027389032766222954,
-0.0019053679425269365,
0.08092393726110458,
-0.13625629246234894,
0.1202360987663269,
0.11568012833595276,
-0.017997518181800842,
0.10267133265733719,
-0.3004167079925537,
-0.13917219638824463,
0.09516182541847229,
0.17446641623973846,
0.151154026389122,
-0.1627427488565445,
-0.017017880454659462,
-0.03343116492033005,
-0.10025948286056519,
0.0892556831240654,
-0.17933738231658936,
0.1017712950706482,
-0.002918839454650879,
0.060738854110240936,
0.0006556780426762998,
-0.04893036186695099,
0.14256104826927185,
0.017246173694729805,
0.14807111024856567,
-0.04714712128043175,
0.012862781062722206,
0.052496109157800674,
-0.040287960320711136,
0.036602187901735306,
-0.10845663398504257,
0.04508150368928909,
0.008649677969515324,
-0.007758619263768196,
-0.06775859743356705,
0.028915802016854286,
-0.03425566852092743,
-0.061055950820446014,
-0.02767511084675789,
0.02880607172846794,
0.04634023457765579,
-0.022619379684329033,
0.09887100756168365,
0.010914490558207035,
0.15254086256027222,
0.12136095017194748,
0.050390247255563736,
-0.08213040977716446,
0.03806457296013832,
0.03244786337018013,
-0.02397095039486885,
0.04512474685907364,
-0.14188852906227112,
0.03550611436367035,
0.1093616783618927,
0.008521833457052708,
0.12616223096847534,
0.06825461238622665,
-0.028137583285570145,
0.009232263080775738,
0.07514489442110062,
-0.1619955152273178,
-0.10604451596736908,
0.042739737778902054,
-0.046960242092609406,
-0.08184784650802612,
0.07913166284561157,
0.10620111227035522,
-0.06795774400234222,
-0.0018124172929674387,
-0.03285716846585274,
0.03212329000234604,
-0.07653988152742386,
0.20294305682182312,
0.058266375213861465,
0.037607885897159576,
-0.10479909926652908,
0.11052339524030685,
0.029376685619354248,
-0.037955429404973984,
0.0046548726968467236,
0.0717136487364769,
-0.08474460989236832,
-0.023310808464884758,
0.1196419894695282,
0.1940975785255432,
-0.023677190765738487,
-0.05727727338671684,
-0.12905612587928772,
-0.11528712511062622,
0.018672747537493706,
0.19995039701461792,
0.09544511139392853,
0.0010199368698522449,
0.0005960940034128726,
0.011280667968094349,
-0.096156544983387,
0.08553199470043182,
0.03781226649880409,
0.07538194209337234,
-0.1206698939204216,
0.12730760872364044,
0.0023229813668876886,
0.010560392402112484,
-0.028171299025416374,
0.06022271141409874,
-0.12416993826627731,
0.01279657892882824,
-0.15116064250469208,
-0.012503216043114662,
-0.01888422481715679,
0.016367685049772263,
0.010442850179970264,
-0.0794953927397728,
-0.07153137028217316,
0.022351620718836784,
-0.11531634628772736,
-0.010171739384531975,
0.022701919078826904,
0.051309119910001755,
-0.14591558277606964,
-0.04778692498803139,
0.020274532958865166,
-0.05501735210418701,
0.061502519994974136,
0.05876941978931427,
-0.0011929627507925034,
0.08546682447195053,
-0.2308381199836731,
0.002981019439175725,
0.06911680102348328,
-0.009897767566144466,
0.05546678230166435,
-0.07424891740083694,
-0.03379169851541519,
0.000010016740816354286,
0.08630896359682083,
0.019800422713160515,
0.10849347710609436,
-0.11489364504814148,
-0.001469182432629168,
-0.04955942556262016,
-0.07231146842241287,
-0.025414645671844482,
-0.010476786643266678,
0.09839341044425964,
0.0015768831362947822,
0.17302261292934418,
-0.10217634588479996,
0.004157467745244503,
-0.19356290996074677,
-0.010737009346485138,
-0.016958696767687798,
-0.09911497682332993,
-0.15943509340286255,
-0.049839697778224945,
0.07079597562551498,
-0.04720258712768555,
0.14371050894260406,
0.0073481216095387936,
0.05258527398109436,
0.01613566279411316,
-0.06252922862768173,
0.013342870399355888,
0.04043206945061684,
0.21001122891902924,
0.022734014317393303,
-0.03154445067048073,
0.03413620963692665,
0.037110090255737305,
0.10537615418434143,
0.06085120141506195,
0.22609297931194305,
0.18837808072566986,
-0.0071396175771951675,
0.11280299723148346,
0.0393548347055912,
-0.0741797536611557,
-0.08828079700469971,
0.06449993699789047,
-0.03582720831036568,
0.0486694760620594,
-0.037622421979904175,
0.23919540643692017,
0.0602438747882843,
-0.16184517741203308,
0.039205554872751236,
-0.04899223521351814,
-0.08759315311908722,
-0.12065140902996063,
0.019248085096478462,
-0.09035126119852066,
-0.18720391392707825,
0.001375500694848597,
-0.11248232424259186,
0.0342327244579792,
0.12423382699489594,
0.012491339817643166,
0.012157250195741653,
0.1973106861114502,
0.012582183815538883,
0.04559260606765747,
0.03663511574268341,
-0.00045602850150316954,
-0.0332600362598896,
-0.03755418211221695,
-0.1186315193772316,
0.009525211527943611,
-0.021119559183716774,
0.023996738716959953,
-0.042920369654893875,
-0.05325552076101303,
0.058602914214134216,
-0.02888302132487297,
-0.08903506398200989,
0.01824009232223034,
0.030434831976890564,
0.06776440143585205,
0.052656225860118866,
0.03843974694609642,
-0.01168945711106062,
0.0055567133240401745,
0.23136913776397705,
-0.07249246537685394,
-0.11169827729463577,
-0.08263343572616577,
0.24909473955631256,
0.026235738769173622,
0.029966669157147408,
-0.00631578266620636,
-0.09154726564884186,
0.0053319321013987064,
0.1713017374277115,
0.16565172374248505,
-0.12977759540081024,
-0.0047888667322695255,
-0.04613107070326805,
-0.014482375234365463,
-0.05367652326822281,
0.11435850709676743,
0.12664397060871124,
-0.005698797293007374,
-0.09692629426717758,
-0.03240214288234711,
-0.055695317685604095,
-0.015317736193537712,
-0.07012607157230377,
0.032668717205524445,
-0.008478209376335144,
-0.0008945842855609953,
-0.05025510489940643,
0.08195414394140244,
-0.042070526629686356,
-0.12040392309427261,
0.06157618761062622,
-0.17298075556755066,
-0.15161308646202087,
-0.014682764187455177,
0.11906445771455765,
0.00048721744678914547,
0.04157733917236328,
-0.050625912845134735,
-0.000004945680302625988,
0.04070381820201874,
-0.041454631835222244,
-0.03135431557893753,
-0.13057324290275574,
0.06143214926123619,
-0.10586655884981155,
0.22866427898406982,
-0.015589875169098377,
0.07279864698648453,
0.11519290506839752,
0.041415974497795105,
-0.07344741374254227,
0.11504977941513062,
0.04522691294550896,
-0.10976015776395798,
0.013815813697874546,
0.08757457137107849,
-0.06812708079814911,
0.0895576924085617,
0.03953351452946663,
-0.09317289292812347,
0.021762873977422714,
-0.000025151955924229696,
-0.09235833585262299,
-0.055445488542318344,
-0.06908749043941498,
-0.07744430005550385,
0.11772727221250534,
0.1746578961610794,
-0.028543461114168167,
0.05900491401553154,
-0.06026042625308037,
0.04939837381243706,
0.03837941586971283,
0.05708855018019676,
-0.05196620151400566,
-0.266257107257843,
0.05054602399468422,
0.13722547888755798,
-0.015762198716402054,
-0.21428431570529938,
-0.08015573769807816,
0.012325551360845566,
-0.030376384034752846,
-0.11091670393943787,
0.09716849029064178,
0.10957714915275574,
0.040667824447155,
-0.042496636509895325,
-0.21438057720661163,
-0.07259775698184967,
0.17031076550483704,
-0.12766291201114655,
-0.10589152574539185
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": [], "datasets": "ArianAskari/SOLID"} | text-generation | ArianAskari/SOLID_SFT-WoDPO-WoMixQ | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"en",
"dataset:ArianAskari/SOLID",
"arxiv:1910.09700",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T06:44:14+00:00 | [
"1910.09700"
] | [
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #conversational #en #dataset-ArianAskari/SOLID #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #conversational #en #dataset-ArianAskari/SOLID #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
81,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #mistral #text-generation #conversational #en #dataset-ArianAskari/SOLID #arxiv-1910.09700 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]"
] | [
-0.08591114729642868,
0.18951410055160522,
-0.0033713625743985176,
0.022266317158937454,
0.09957055747509003,
-0.0011251148534938693,
0.059102218598127365,
0.12024262547492981,
0.022303961217403412,
0.1301860213279724,
0.051019661128520966,
0.15435779094696045,
0.107495978474617,
0.20398804545402527,
0.0019805266056209803,
-0.15283428132534027,
0.039414722472429276,
-0.09943387657403946,
0.027260450646281242,
0.11693242192268372,
0.13333328068256378,
-0.11049968749284744,
0.06592319905757904,
-0.03267781436443329,
-0.002022090833634138,
-0.06199624016880989,
-0.07250470668077469,
-0.028583087027072906,
0.04150979593396187,
0.021239934489130974,
0.05376110598444939,
-0.010742194019258022,
0.08744451403617859,
-0.2901124060153961,
0.022842584177851677,
0.0485212616622448,
-0.0017796496395021677,
0.07630124688148499,
0.09095916152000427,
-0.05410704389214516,
0.08763454109430313,
-0.08292148262262344,
0.1270849108695984,
0.10611572116613388,
-0.07227595895528793,
-0.1651565134525299,
-0.075367771089077,
0.1111975684762001,
0.1790151745080948,
0.06474190205335617,
-0.03376016765832901,
0.12017020583152771,
-0.03213946148753166,
0.03724733740091324,
0.044842761009931564,
-0.05471503362059593,
-0.05572173371911049,
0.042899828404188156,
0.12484990805387497,
0.04225701466202736,
-0.12191780656576157,
-0.0019060199847444892,
0.025276480242609978,
0.04046973958611488,
0.10134588927030563,
0.02000250853598118,
0.16189776360988617,
0.020992033183574677,
-0.14044798910617828,
-0.052640270441770554,
0.04825855419039726,
0.0181200560182333,
-0.041390545666217804,
-0.25917497277259827,
-0.005468228831887245,
-0.044545650482177734,
-0.03781736269593239,
-0.06377661973237991,
0.03515990078449249,
0.0037296300288289785,
0.11075441539287567,
-0.052958954125642776,
-0.08164630830287933,
-0.025297194719314575,
0.07798552513122559,
0.07309716939926147,
0.01828034594655037,
-0.025118820369243622,
0.03161930665373802,
0.09600728005170822,
0.09970615804195404,
-0.11522892117500305,
-0.04717804491519928,
-0.06340683251619339,
-0.07976372539997101,
-0.02989640273153782,
0.053809188306331635,
0.06479813903570175,
0.055789828300476074,
0.24224527180194855,
0.004872492980211973,
0.036379262804985046,
0.025253843516111374,
-0.00022044511570129544,
0.04856210947036743,
0.07400048524141312,
-0.0510658398270607,
-0.16834498941898346,
-0.019700143486261368,
0.100941002368927,
-0.0020966820884495974,
-0.037669647485017776,
-0.04390076920390129,
0.03787677735090256,
0.08134777098894119,
0.1052965372800827,
0.14250242710113525,
0.012465027160942554,
-0.0721745640039444,
-0.07178683578968048,
0.2067420929670334,
-0.1490723341703415,
0.03175797685980797,
0.010890942066907883,
-0.015492487698793411,
-0.06279323995113373,
0.0093216672539711,
0.02679617889225483,
-0.03862566500902176,
0.07456154376268387,
-0.06362278759479523,
-0.04901086166501045,
-0.11192686855792999,
-0.018724525347352028,
0.05105894058942795,
-0.020058566704392433,
-0.040508586913347244,
-0.05080017074942589,
-0.09641260653734207,
-0.09262187778949738,
0.09625022113323212,
-0.05899379402399063,
-0.05469419062137604,
-0.03942353278398514,
-0.0762234777212143,
0.033354345709085464,
0.0025586688425391912,
0.08315546065568924,
-0.028627494350075722,
0.05162280797958374,
-0.035812459886074066,
0.05065896362066269,
0.10143027454614639,
0.03564368188381195,
-0.06475099921226501,
0.06836478412151337,
-0.16765567660331726,
0.09521768242120743,
-0.07747264951467514,
0.03799491003155708,
-0.16434603929519653,
-0.0023962759878486395,
0.049202632158994675,
0.030180253088474274,
0.017385808750987053,
0.147915780544281,
-0.17594081163406372,
-0.013952301815152168,
0.17978331446647644,
-0.10041902214288712,
-0.13655312359333038,
0.04058404639363289,
-0.05704823508858681,
0.1869451254606247,
0.05159022659063339,
-0.012890767306089401,
0.06855574250221252,
-0.14087168872356415,
-0.06638427823781967,
-0.06036901846528053,
-0.01128858420997858,
0.10120076686143875,
0.0734618604183197,
-0.06581661850214005,
0.057426828891038895,
0.0201321542263031,
-0.04840515926480293,
-0.02343326434493065,
-0.036143478006124496,
-0.09638531506061554,
0.02645096741616726,
-0.09498225152492523,
0.020638953894376755,
-0.014116978272795677,
-0.07909931987524033,
-0.0003651797887869179,
-0.1623964011669159,
-0.0196976438164711,
0.08402704447507858,
0.006334508303552866,
-0.017391294240951538,
-0.09774032235145569,
0.020764444023370743,
-0.021108895540237427,
-0.003496028482913971,
-0.13055238127708435,
-0.058796193450689316,
0.028371669352054596,
-0.15084494650363922,
0.015560870990157127,
-0.15134941041469574,
0.04931439459323883,
0.018444349989295006,
-0.04701909422874451,
-0.039214152842760086,
0.028308270499110222,
0.015857039019465446,
-0.04085249826312065,
-0.22762233018875122,
-0.03304901346564293,
-0.05571984872221947,
0.1221156045794487,
-0.1838909536600113,
0.04857059568166733,
0.032088082283735275,
0.14346154034137726,
-0.005432146601378918,
-0.06627129018306732,
0.029376499354839325,
-0.06572920083999634,
-0.01405918225646019,
-0.06108192354440689,
0.01643037609755993,
-0.02216598205268383,
-0.046639952808618546,
0.04501141235232353,
-0.17690297961235046,
-0.0629289373755455,
0.1101449504494667,
0.03948267921805382,
-0.1271558403968811,
-0.06403711438179016,
-0.019428426399827003,
-0.0843457356095314,
-0.038206472992897034,
-0.08128256350755692,
0.08287390321493149,
0.06362864375114441,
0.02629874460399151,
-0.05784231796860695,
-0.08279623091220856,
0.009589358232915401,
0.0030292565934360027,
-0.01637669838964939,
0.07914599031209946,
0.027421679347753525,
-0.17498062551021576,
0.10552344471216202,
0.07292444258928299,
0.05943441763520241,
0.09095818549394608,
-0.006180671975016594,
-0.09002769738435745,
-0.04325848072767258,
0.04754214361310005,
0.02575576864182949,
0.13144296407699585,
-0.0943843424320221,
0.021420160308480263,
0.03651288524270058,
-0.046079859137535095,
0.04347645863890648,
-0.053194209933280945,
0.023470405489206314,
0.0021141006145626307,
0.0005579995340667665,
0.061772480607032776,
-0.0396815687417984,
-0.0008660968160256743,
0.058744706213474274,
0.0760321319103241,
0.03436155244708061,
0.037537723779678345,
-0.04949759319424629,
-0.12246540188789368,
0.13930481672286987,
-0.10360046476125717,
-0.21216371655464172,
-0.15138190984725952,
-0.01332154218107462,
0.037512268871068954,
-0.009922226890921593,
0.001954267732799053,
-0.042666688561439514,
-0.09381214529275894,
-0.07360909134149551,
0.024256350472569466,
0.041591908782720566,
-0.06499204784631729,
-0.05179423838853836,
0.0589577816426754,
0.03201922029256821,
-0.1158737987279892,
0.015236659906804562,
0.05508697032928467,
-0.04298005998134613,
-0.012654871679842472,
0.079257532954216,
0.10421723127365112,
0.1528315544128418,
0.020987221971154213,
-0.014384711161255836,
0.04109276086091995,
0.20888066291809082,
-0.1427038609981537,
0.0986129492521286,
0.13800325989723206,
-0.07164572924375534,
0.07148110121488571,
0.20800955593585968,
0.032779235392808914,
-0.0758822038769722,
0.033028408885002136,
0.036740660667419434,
-0.019172044470906258,
-0.24666911363601685,
-0.0681489035487175,
-0.009638508781790733,
-0.07870946079492569,
0.08955040574073792,
0.07775488495826721,
0.1054048165678978,
0.03622778132557869,
-0.09216933697462082,
-0.08375802636146545,
0.05951887369155884,
0.1228976622223854,
-0.01720024272799492,
-0.0013506599934771657,
0.09191402047872543,
-0.004085235763341188,
0.019875019788742065,
0.08268055319786072,
-0.0001765630440786481,
0.15473893284797668,
0.027463169768452644,
0.1784254014492035,
0.08076410740613937,
0.07750341296195984,
-0.02370513416826725,
0.033715397119522095,
0.031207602471113205,
0.050495922565460205,
0.0058638532646000385,
-0.07994958758354187,
-0.018029509112238884,
0.13463029265403748,
0.017555976286530495,
0.010689089074730873,
0.024890149012207985,
-0.03097381815314293,
0.06426969915628433,
0.19360235333442688,
-0.02228063903748989,
-0.20124611258506775,
-0.08559868484735489,
0.07746205478906631,
-0.08731615543365479,
-0.13906006515026093,
-0.013039813376963139,
0.014492535963654518,
-0.15630744397640228,
0.015714148059487343,
-0.04881053790450096,
0.10320991277694702,
-0.11320079863071442,
-0.021100979298353195,
0.07428882271051407,
0.048650771379470825,
0.0035275998525321484,
0.048808757215738297,
-0.17617353796958923,
0.1045973002910614,
0.031072931364178658,
0.08414750546216965,
-0.09890686720609665,
0.08970693498849869,
0.011286185123026371,
-0.07314646989107132,
0.18064577877521515,
-0.010738139040768147,
-0.0694650188088417,
-0.09453598409891129,
-0.11837100237607956,
-0.02726702019572258,
0.10227955877780914,
-0.14026488363742828,
0.09417592734098434,
-0.03641578182578087,
-0.03401083126664162,
0.005219758953899145,
-0.07935810834169388,
-0.11700950562953949,
-0.17629259824752808,
0.06388171017169952,
-0.10724657773971558,
0.04094449058175087,
-0.09698031842708588,
-0.05551959201693535,
0.009462553076446056,
0.21563945710659027,
-0.2205141931772232,
-0.09556426107883453,
-0.13847346603870392,
-0.06836716830730438,
0.14751750230789185,
-0.05964501202106476,
0.09806060045957565,
0.0017309810500591993,
0.14051106572151184,
-0.009076863527297974,
-0.007576607633382082,
0.08575788140296936,
-0.09029825031757355,
-0.1891731321811676,
-0.05288151279091835,
0.1325221061706543,
0.14185570180416107,
0.024270936846733093,
-0.008372500538825989,
0.030560052022337914,
-0.02933473512530327,
-0.1015915721654892,
0.032950110733509064,
0.19625476002693176,
0.0920095443725586,
-0.004152963869273663,
-0.025343650951981544,
-0.1535644680261612,
-0.08521492779254913,
-0.061786215752363205,
-0.0005300347693264484,
0.1992185264825821,
-0.06171563267707825,
0.16717329621315002,
0.16103315353393555,
-0.06240608170628548,
-0.21536792814731598,
-0.016204072162508965,
0.032778676599264145,
-0.006342306267470121,
0.02949732355773449,
-0.16765886545181274,
0.07935850322246552,
-0.038786835968494415,
-0.07533682882785797,
0.11726700514554977,
-0.13281740248203278,
-0.13774770498275757,
0.1007973849773407,
0.04325760155916214,
-0.18878419697284698,
-0.13924741744995117,
-0.11246135085821152,
-0.021350998431444168,
-0.10132578015327454,
0.08525710552930832,
0.004764101002365351,
-0.00354272173717618,
0.029304277151823044,
0.015254397876560688,
0.04497908428311348,
-0.06542695313692093,
0.18087945878505707,
-0.03826899826526642,
0.0029263384640216827,
-0.08073239773511887,
-0.09020382165908813,
0.038588058203458786,
-0.06295407563447952,
0.09007441997528076,
-0.017774123698472977,
0.013888939283788204,
-0.08299001306295395,
-0.05981450155377388,
-0.06696662306785583,
0.02645951695740223,
-0.08893732726573944,
-0.09624781459569931,
-0.018495704978704453,
0.10162613540887833,
0.11547663807868958,
-0.015178020112216473,
0.023715490475296974,
-0.07661876082420349,
0.060629528015851974,
0.24850469827651978,
0.1865287870168686,
0.07004489004611969,
-0.03249715268611908,
-0.004796118009835482,
-0.03821421414613724,
0.039546530693769455,
-0.1689022332429886,
0.04890618100762367,
0.05118025466799736,
0.013387631624937057,
0.08358875662088394,
-0.009707284159958363,
-0.15496408939361572,
-0.07026869803667068,
0.07576935738325119,
-0.04827704280614853,
-0.18592816591262817,
-0.01683025248348713,
0.06391692906618118,
-0.20023861527442932,
-0.041615214198827744,
0.05948876589536667,
-0.0005087462486699224,
-0.03974737226963043,
0.016980772837996483,
0.10129724442958832,
-0.004164275713264942,
0.08713217824697495,
0.06588397920131683,
0.08972740918397903,
-0.0916028693318367,
0.06921800225973129,
0.1018603965640068,
-0.060369823127985,
0.043673500418663025,
0.11816508322954178,
-0.04888302460312843,
-0.04832867905497551,
0.06316325813531876,
0.06346286088228226,
0.0069361296482384205,
-0.04177531599998474,
0.020308077335357666,
-0.023852862417697906,
0.04984608665108681,
0.10398845374584198,
0.017023544758558273,
0.008761642500758171,
0.0681496411561966,
0.05425215885043144,
-0.06768125295639038,
0.13304312527179718,
0.0572650283575058,
0.020188961178064346,
-0.05409325286746025,
-0.03502468764781952,
-0.003865145845338702,
-0.015512671321630478,
-0.018833089619874954,
-0.0005200320156291127,
-0.07575608789920807,
-0.007251439616084099,
-0.16512878239154816,
0.04271606355905533,
-0.12122757732868195,
0.000758568465244025,
0.01757586933672428,
-0.028753815218806267,
0.015823930501937866,
0.004630325362086296,
-0.05824412778019905,
-0.07961151748895645,
-0.01621859520673752,
0.10554816573858261,
-0.15987098217010498,
0.000006971866241656244,
0.08041578531265259,
-0.10180455446243286,
0.08254267275333405,
-0.004729445558041334,
0.005627367179840803,
0.001556327915750444,
-0.15077221393585205,
0.052106812596321106,
-0.03683033213019371,
-0.008052549324929714,
-0.0028627223800867796,
-0.1978321224451065,
-0.022987497970461845,
-0.03588982671499252,
-0.06754298508167267,
0.0010133404284715652,
0.0021536697167903185,
-0.10626740008592606,
0.06582276523113251,
0.02484598383307457,
-0.04247516021132469,
-0.031127311289310455,
0.03359273448586464,
0.09694145619869232,
-0.026543520390987396,
0.08433426171541214,
-0.015508226118981838,
0.07229591906070709,
-0.1663266271352768,
0.011730297468602657,
-0.018677784129977226,
0.040602993220090866,
-0.022090008482336998,
-0.03073965571820736,
0.04723985120654106,
-0.01781122200191021,
0.16422079503536224,
-0.04028577730059624,
0.05164588615298271,
0.049013588577508926,
-0.007309996988624334,
0.014953473582863808,
0.08314485102891922,
0.05880444124341011,
-0.0014755617594346404,
0.0019702643621712923,
0.029677774757146835,
-0.023262159898877144,
-0.060997169464826584,
-0.15071363747119904,
0.02580154687166214,
0.19596615433692932,
0.09773294627666473,
0.0013188386801630259,
0.04597467929124832,
-0.1274193972349167,
-0.09621517360210419,
0.1213398426771164,
-0.031184211373329163,
-0.03826535493135452,
-0.09135549515485764,
0.17124825716018677,
0.12666195631027222,
-0.18048261106014252,
0.07708001136779785,
-0.05411146208643913,
-0.04289722442626953,
-0.09348294138908386,
-0.21678252518177032,
-0.056193772703409195,
-0.018026480451226234,
-0.020782630890607834,
-0.046267107129096985,
0.048903029412031174,
0.05317362770438194,
-0.013364640064537525,
-0.014126998372375965,
0.08278103172779083,
0.00421117153018713,
-0.018623115494847298,
0.047679562121629715,
0.05786889046430588,
0.008600653149187565,
-0.0751769170165062,
0.007157966960221529,
-0.010349872522056103,
0.06228027120232582,
0.07416076213121414,
0.023152993991971016,
-0.050502710044384,
0.02431231550872326,
-0.014113523066043854,
-0.12686440348625183,
0.0414765328168869,
-0.013578114099800587,
-0.040865086019039154,
0.19634321331977844,
0.025065679103136063,
0.0008438621880486608,
-0.015283580869436264,
0.2330462485551834,
-0.06837407499551773,
-0.08385100960731506,
-0.13369156420230865,
0.05355008319020271,
-0.06361609697341919,
0.02434631623327732,
0.024886183440685272,
-0.10945887118577957,
0.015274260193109512,
0.15641985833644867,
0.1469704508781433,
-0.0210683923214674,
0.010695376433432102,
0.03625712916254997,
0.0054151699878275394,
-0.044735491275787354,
0.019756468012928963,
0.041862256824970245,
0.17302173376083374,
-0.06642885506153107,
0.08851856738328934,
0.015724120661616325,
-0.09131169319152832,
-0.004371588584035635,
0.08552920818328857,
-0.026815932244062424,
0.043405547738075256,
-0.07227680832147598,
0.12302740663290024,
-0.07759073376655579,
-0.2301245927810669,
0.03242829814553261,
-0.06911255419254303,
-0.1213684231042862,
-0.030683457851409912,
0.042058832943439484,
-0.013241901062428951,
0.016053473576903343,
0.08648666739463806,
-0.028633546084165573,
0.17428931593894958,
0.027320576831698418,
-0.07319273054599762,
-0.04112134128808975,
0.05919177085161209,
-0.12016452848911285,
0.2961375415325165,
0.0057159005664289,
0.04355718195438385,
0.11353806406259537,
-0.021398240700364113,
-0.15568998456001282,
-0.014709829352796078,
0.0977022722363472,
-0.08142223209142685,
0.07461071759462357,
0.21640299260616302,
-0.011462527327239513,
0.11084781587123871,
0.06922407448291779,
-0.07168732583522797,
0.028895165771245956,
-0.06540285050868988,
-0.0845891535282135,
-0.11322290450334549,
0.08100200444459915,
-0.0810452401638031,
0.16764654219150543,
0.10923725366592407,
-0.06698185205459595,
0.00631897896528244,
-0.02422751858830452,
0.06645002961158752,
-0.009003838524222374,
0.12591047585010529,
-0.002101090969517827,
-0.20487265288829803,
0.04100646451115608,
0.04141320660710335,
0.11466335505247116,
-0.20673632621765137,
-0.07495803385972977,
0.05126289278268814,
-0.009052442386746407,
-0.0788300558924675,
0.1133040115237236,
0.05219925194978714,
0.012903459370136261,
-0.041713688522577286,
-0.07311321794986725,
-0.011673279106616974,
0.1296810805797577,
-0.11166002601385117,
-0.02372674085199833
] |
null | null | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
- A *longer tutorial* to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
### Resume the training
```bash
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser**
1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: nickmiller795/ppo-PyramidsTraining
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
| {"library_name": "ml-agents", "tags": ["Pyramids", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | reinforcement-learning | nickmiller795/ppo-PyramidsTraining | [
"ml-agents",
"tensorboard",
"onnx",
"Pyramids",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | 2024-02-11T06:50:34+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your
browser: URL
- A *longer tutorial* to understand how works ML-Agents:
URL
### Resume the training
### Watch your Agent play
You can watch your agent playing directly in your browser
1. If the environment is part of ML-Agents official environments, go to URL
2. Step 1: Find your model_id: nickmiller795/ppo-PyramidsTraining
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play
| [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: nickmiller795/ppo-PyramidsTraining\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
"TAGS\n#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n",
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: nickmiller795/ppo-PyramidsTraining\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
48,
206
] | [
"passage: TAGS\n#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your\n browser: URL\n - A *longer tutorial* to understand how works ML-Agents:\n URL\n\n ### Resume the training\n \n\n ### Watch your Agent play\n You can watch your agent playing directly in your browser\n\n 1. If the environment is part of ML-Agents official environments, go to URL\n 2. Step 1: Find your model_id: nickmiller795/ppo-PyramidsTraining\n 3. Step 2: Select your *.nn /*.onnx file\n 4. Click on Watch the agent play"
] | [
-0.016196811571717262,
0.06401723623275757,
-0.004027994815260172,
0.06565862149000168,
0.14840513467788696,
-0.01976119726896286,
0.1459774374961853,
0.14075443148612976,
0.19125932455062866,
0.11167649924755096,
0.03842828795313835,
0.09042171388864517,
0.06153663247823715,
0.1234845221042633,
0.07293304800987244,
-0.17375041544437408,
-0.03530922532081604,
-0.058558810502290726,
0.09188209474086761,
0.10087530314922333,
0.042111460119485855,
-0.06868857145309448,
0.06408791244029999,
0.02837906964123249,
-0.0350409634411335,
-0.0007212806958705187,
-0.08304651826620102,
-0.03146694600582123,
0.043331701308488846,
-0.030042672529816628,
-0.004846400581300259,
-0.045243535190820694,
0.0853356346487999,
-0.1445586234331131,
0.02641371078789234,
0.09922225028276443,
-0.012915086932480335,
0.0044336519204080105,
0.12648098170757294,
0.012118371203541756,
0.1069975346326828,
-0.09502985328435898,
0.06273668259382248,
0.050549253821372986,
-0.07464271038770676,
-0.00270914938300848,
-0.1275082230567932,
0.07260692119598389,
0.2148425579071045,
0.13743092119693756,
0.00039736213511787355,
0.140068918466568,
-0.012595820240676403,
0.04329973831772804,
0.1727350503206253,
-0.27530625462532043,
-0.06754765659570694,
0.11519044637680054,
-0.009819405153393745,
0.03352933004498482,
-0.0008542966679669917,
0.04991700127720833,
-0.04968923330307007,
0.03310174494981766,
0.0198261346668005,
-0.022006412968039513,
0.18419697880744934,
-0.03217567875981331,
-0.09288579970598221,
-0.07923515886068344,
0.08024358749389648,
0.05503987893462181,
-0.016789430752396584,
-0.18814527988433838,
-0.015788661316037178,
0.11271689832210541,
-0.025103099644184113,
0.029212964698672295,
0.04570191726088524,
0.003954739309847355,
0.008469099178910255,
-0.11453454196453094,
-0.032793134450912476,
-0.07836003601551056,
0.04334895685315132,
0.1295214593410492,
0.021742718294262886,
-0.031362246721982956,
0.058607641607522964,
0.060696762055158615,
0.07350331544876099,
-0.05879099667072296,
-0.013535267673432827,
-0.010774842463433743,
-0.11457306146621704,
-0.03601004555821419,
0.02481214702129364,
-0.06374344229698181,
0.03623634949326515,
0.04729137569665909,
0.07791446149349213,
0.042238280177116394,
0.009898995980620384,
0.051280755549669266,
0.0047595989890396595,
0.09684669971466064,
-0.007501469925045967,
0.05454886332154274,
0.03369583934545517,
0.06306102126836777,
0.02762448787689209,
-0.06386582553386688,
-0.06650235503911972,
0.08839547634124756,
-0.05253554880619049,
0.09753471612930298,
0.1363387107849121,
0.006748047191649675,
-0.026648707687854767,
-0.06263431161642075,
-0.021600229665637016,
-0.14961960911750793,
0.07109387964010239,
0.045372724533081055,
-0.03313480690121651,
-0.06079656630754471,
-0.02437148615717888,
-0.006504006218165159,
-0.11149634420871735,
0.012278168462216854,
-0.01857154630124569,
0.04478291794657707,
-0.029866697266697884,
-0.020481538027524948,
0.052096977829933167,
-0.024321289733052254,
-0.041872553527355194,
-0.17043109238147736,
-0.19926954805850983,
-0.08437393605709076,
0.03756213188171387,
-0.06441093236207962,
-0.07906705141067505,
-0.026649480685591698,
0.04536225274205208,
-0.08810178190469742,
0.013465849682688713,
-0.03839482367038727,
-0.05098029226064682,
0.0033057203982025385,
-0.055199552327394485,
0.043157197535037994,
0.19285039603710175,
0.03756646439433098,
-0.027705209329724312,
0.058342356234788895,
-0.1802491396665573,
0.13602285087108612,
-0.10909466445446014,
0.1845807284116745,
-0.09981749206781387,
0.03567897900938988,
0.04045480862259865,
0.0018099239096045494,
0.020713726058602333,
0.15693344175815582,
-0.10111377388238907,
-0.07702288031578064,
0.11441132426261902,
-0.038052089512348175,
-0.15712293982505798,
0.04289150983095169,
0.022860879078507423,
0.07188525050878525,
0.07074818015098572,
0.2194254994392395,
0.12306507676839828,
-0.20055124163627625,
0.03770555928349495,
-0.02126133069396019,
-0.09721875935792923,
-0.013064751401543617,
0.1091676652431488,
-0.10257110744714737,
-0.02972068451344967,
-0.024540763348340988,
-0.15658697485923767,
0.06929511576890945,
-0.017817962914705276,
-0.0480441115796566,
0.0329270176589489,
-0.04899262636899948,
-0.050209056586027145,
0.029445765540003777,
0.048519790172576904,
-0.02265063300728798,
-0.06761632114648819,
-0.09186925739049911,
0.07736925780773163,
-0.028199998661875725,
0.03537372127175331,
-0.051974114030599594,
0.16383585333824158,
-0.008458775468170643,
0.044804055243730545,
-0.14021946489810944,
-0.10738125443458557,
0.024216461926698685,
0.0014128133188933134,
0.0807342529296875,
-0.1522158980369568,
0.07110819965600967,
0.0654495358467102,
0.03323318436741829,
-0.06710674613714218,
-0.07807599008083344,
0.004042276181280613,
-0.0838332250714302,
-0.09127463400363922,
-0.0580582395195961,
-0.04131704941391945,
0.027240047231316566,
-0.05746610090136528,
0.05821506679058075,
-0.11583805829286575,
0.10236552357673645,
-0.0067914617247879505,
-0.06433753669261932,
0.04111843556165695,
0.018626900389790535,
0.04621206223964691,
-0.0772424265742302,
0.09785617887973785,
0.01631326787173748,
-0.03397352993488312,
-0.008777680806815624,
-0.020196039229631424,
-0.08932921290397644,
0.09897672384977341,
-0.011428790166974068,
-0.008572867140173912,
0.004492271691560745,
-0.04458390176296234,
0.014861512929201126,
-0.0813349187374115,
-0.01132502406835556,
0.19442610442638397,
0.10459013283252716,
0.1053178682923317,
-0.06883960962295532,
-0.05542305111885071,
-0.01621820777654648,
-0.045795150101184845,
-0.04193342477083206,
0.13545069098472595,
0.07429438084363937,
-0.028572604060173035,
0.0603395476937294,
0.06260904669761658,
0.08545903861522675,
0.05600861832499504,
-0.013778610154986382,
-0.12261705845594406,
0.0022197735961526632,
0.06705662608146667,
0.05591769143939018,
0.007547909393906593,
0.012933091260492802,
-0.025147417560219765,
0.01426703017205,
-0.0316452831029892,
0.002198846312239766,
-0.11062484234571457,
-0.05300483852624893,
0.03686659783124924,
-0.004857645370066166,
0.038362253457307816,
-0.03587555140256882,
-0.02138322964310646,
0.05890519917011261,
0.06927770376205444,
0.017085565254092216,
-0.00962766446173191,
-0.06571506708860397,
-0.11533524096012115,
0.07397639006376266,
-0.08176063001155853,
-0.26009780168533325,
-0.09066803753376007,
-0.08803538233041763,
-0.07000245898962021,
0.017695371061563492,
0.03508703038096428,
-0.13834738731384277,
-0.00802561268210411,
-0.09382119029760361,
-0.012471688911318779,
0.012050105258822441,
-0.04686750844120979,
0.1969020664691925,
0.09274528175592422,
0.003530870657414198,
-0.0615101233124733,
-0.022979963570833206,
-0.0003355849767103791,
-0.04549795016646385,
-0.0005442960537038743,
0.03971254080533981,
0.07608643174171448,
0.10516128689050674,
0.06856061518192291,
0.07057864218950272,
-0.005850335117429495,
0.11397580057382584,
-0.06911353021860123,
-0.011835929937660694,
0.12367726117372513,
0.020334158092737198,
0.06484439969062805,
0.03236571326851845,
0.049867305904626846,
-0.023902153596282005,
0.021105270832777023,
0.014242228120565414,
-0.045453835278749466,
-0.19150975346565247,
-0.11767299473285675,
-0.03656237572431564,
0.09902334958314896,
0.13114503026008606,
0.0990435779094696,
-0.04379669949412346,
-0.005999461282044649,
0.006225913763046265,
-0.043823231011629105,
0.09506664425134659,
0.1122327446937561,
-0.047799937427043915,
-0.02683495730161667,
-0.007013581693172455,
-0.04245296120643616,
0.02570975013077259,
0.05199970677495003,
-0.00389263522811234,
0.13688577711582184,
0.04896586760878563,
0.05283958837389946,
0.028239427134394646,
-0.042781416326761246,
-0.0424562506377697,
0.07516855746507645,
0.024613603949546814,
0.009944207035005093,
0.007948629558086395,
-0.08446726948022842,
-0.03956443816423416,
0.06762947887182236,
0.10560164600610733,
-0.0197738166898489,
-0.09778819978237152,
0.04977741837501526,
0.09418955445289612,
0.16021400690078735,
0.0013498208718374372,
-0.16503766179084778,
-0.030854491516947746,
-0.0032150279730558395,
-0.09010709822177887,
0.016085423529148102,
0.009800104424357414,
-0.03394150733947754,
-0.1749020218849182,
0.034481462091207504,
0.0056119030341506,
0.1352938711643219,
-0.04827234521508217,
-0.017040500417351723,
0.05337323620915413,
0.0402921624481678,
-0.012432760559022427,
0.056285373866558075,
-0.13650579750537872,
0.11752824485301971,
0.0104854516685009,
0.09811954200267792,
-0.06730514764785767,
0.022929349914193153,
0.08571670204401016,
-0.03933296352624893,
0.20195384323596954,
0.029909079894423485,
-0.00856447871774435,
-0.09557396173477173,
-0.17664478719234467,
-0.06340149790048599,
-0.03404085338115692,
-0.11205783486366272,
0.07291224598884583,
0.03327729552984238,
-0.04241849109530449,
-0.09899262338876724,
0.07502425462007523,
-0.05205225199460983,
-0.08163119852542877,
0.004984558094292879,
-0.05028843507170677,
-0.04569339007139206,
-0.05485045909881592,
-0.031841959804296494,
-0.12862645089626312,
0.15624703466892242,
0.0811062678694725,
-0.06913470476865768,
-0.090506412088871,
-0.03764181211590767,
-0.03841415420174599,
-0.042179327458143234,
-0.0016469586407765746,
0.001675017992965877,
0.09126315265893936,
-0.06410215049982071,
-0.07968160510063171,
-0.011081584729254246,
-0.11021602898836136,
-0.07639633864164352,
-0.039296314120292664,
0.22242383658885956,
0.027246985584497452,
0.06035972759127617,
-0.0024400907568633556,
0.04411636292934418,
-0.014306767843663692,
-0.07267975062131882,
0.1610579788684845,
0.1524278074502945,
0.005187114235013723,
0.07418059557676315,
-0.04720178246498108,
0.06959165632724762,
-0.12832026183605194,
0.01356277335435152,
0.1916099488735199,
0.26330339908599854,
-0.04096360504627228,
0.1463014930486679,
0.048686496913433075,
-0.06601624190807343,
-0.16603544354438782,
-0.05171683430671692,
0.0059123570099473,
-0.029521986842155457,
0.09761042147874832,
-0.1864408403635025,
0.05035946145653725,
0.024683242663741112,
-0.023524807766079903,
-0.013134962879121304,
-0.2802312672138214,
-0.07811024785041809,
0.04426632076501846,
0.08895062655210495,
-0.057324718683958054,
-0.10998518019914627,
-0.07759759575128555,
0.022736532613635063,
-0.1331912726163864,
0.03872005268931389,
-0.16317467391490936,
0.052949801087379456,
-0.012085053138434887,
0.023780539631843567,
0.04326298087835312,
-0.041974831372499466,
0.12208902835845947,
-0.028391988947987556,
-0.024225272238254547,
-0.057235121726989746,
0.0377795584499836,
0.01695486530661583,
-0.08564901351928711,
0.04818730428814888,
0.0007963031530380249,
-0.017481397837400436,
-0.22004742920398712,
-0.03311251103878021,
-0.02574058622121811,
0.04673467576503754,
-0.014724268577992916,
-0.01945212297141552,
0.004057324957102537,
0.07201184332370758,
0.08810988813638687,
0.04024798795580864,
0.09846864640712738,
0.0056667509488761425,
0.03778274357318878,
0.07108236104249954,
0.0352008081972599,
0.011124270968139172,
-0.1574268490076065,
-0.04465387016534805,
-0.04115448519587517,
0.010830816812813282,
-0.0560990571975708,
-0.0014108909526839852,
0.06646120548248291,
0.032168347388505936,
0.037360891699790955,
0.05918970704078674,
-0.11458787322044373,
-0.01665627211332321,
0.055901166051626205,
-0.10633068531751633,
-0.1824926882982254,
-0.06705227494239807,
-0.0403701551258564,
-0.009934045374393463,
-0.06662723422050476,
0.03136943280696869,
-0.03115922026336193,
-0.015411161817610264,
0.03817339986562729,
0.030744051560759544,
-0.03787907958030701,
0.050979580730199814,
-0.015685224905610085,
0.03389056771993637,
-0.07075011730194092,
0.16228759288787842,
0.07966269552707672,
-0.01934158429503441,
0.013469494879245758,
0.22457793354988098,
-0.07306896150112152,
-0.08565017580986023,
-0.029853971675038338,
0.09698282182216644,
0.1394166797399521,
-0.006689833011478186,
-0.029855618253350258,
-0.0704306960105896,
0.0846976786851883,
-0.13239245116710663,
0.01293746754527092,
-0.13381092250347137,
0.012760466895997524,
0.03461230546236038,
-0.07525881379842758,
0.08697868138551712,
-0.014037908986210823,
-0.037474922835826874,
-0.12956400215625763,
0.04576936736702919,
0.03414515033364296,
0.12588132917881012,
-0.01789475791156292,
-0.0488072969019413,
-0.1239195317029953,
0.04176831990480423,
0.011927084065973759,
-0.03136327117681503,
-0.19746102392673492,
-0.03398497402667999,
-0.010905476287007332,
0.040093567222356796,
-0.003848584135994315,
0.0476221963763237,
-0.04600141569972038,
-0.10652361065149307,
-0.02111162059009075,
0.10238806158304214,
-0.06291566789150238,
-0.025727346539497375,
0.02200753428041935,
-0.07802174240350723,
0.06574889272451401,
0.06397222727537155,
-0.0048566944897174835,
-0.019325818866491318,
-0.06983967870473862,
-0.04407257214188576,
-0.02666447125375271,
0.003868801984935999,
0.05037735402584076,
-0.16299942135810852,
0.035623982548713684,
-0.04238254204392433,
-0.11798032373189926,
0.014606023207306862,
0.07077693939208984,
-0.08078780770301819,
0.032448071986436844,
0.03479675203561783,
-0.048559918999671936,
-0.06771660596132278,
0.028703458607196808,
0.056050051003694534,
0.06227573752403259,
0.05537506565451622,
-0.07340160757303238,
0.17620012164115906,
-0.12864458560943604,
-0.02102583833038807,
0.006947335787117481,
0.0323362834751606,
0.05594322457909584,
-0.07676561921834946,
0.054292041808366776,
-0.032232608646154404,
0.0969405546784401,
0.08435904234647751,
-0.01400623470544815,
0.04333335533738136,
0.02778712473809719,
0.08980933576822281,
0.010861947201192379,
0.059655383229255676,
-0.015993431210517883,
-0.0030120485462248325,
0.10666505247354507,
-0.00822642631828785,
0.053255606442689896,
-0.02760532684624195,
0.12263068556785583,
0.13664743304252625,
0.13671348989009857,
0.02954459935426712,
0.08183624595403671,
-0.09167218208312988,
-0.178754061460495,
-0.055323150008916855,
0.02705586515367031,
0.04913114011287689,
-0.06883297115564346,
0.1375206559896469,
0.08826754242181778,
-0.17564338445663452,
0.06487645208835602,
-0.00459473067894578,
0.015345478430390358,
-0.07123016566038132,
-0.12606461346149445,
0.0012878727866336703,
-0.14751212298870087,
0.0631195455789566,
-0.02999432571232319,
-0.006956109311431646,
-0.0342261902987957,
-0.026966461911797523,
-0.017748774960637093,
0.09112685918807983,
-0.060856424272060394,
-0.0247667096555233,
0.07808879017829895,
-0.03604494780302048,
0.013488342054188251,
-0.05701454356312752,
-0.021958649158477783,
-0.048926886171102524,
-0.08238603919744492,
0.018566064536571503,
0.03947071731090546,
-0.03730925917625427,
0.06779750436544418,
-0.03285401314496994,
-0.08522547036409378,
0.04340542107820511,
-0.027557898312807083,
-0.020558932796120644,
0.14361818134784698,
0.07809129357337952,
-0.08370602130889893,
-0.030429719015955925,
0.20311307907104492,
-0.026636196300387383,
0.02727511338889599,
-0.07551407068967819,
0.1511576771736145,
-0.01819835975766182,
-0.0814286470413208,
-0.010389032773673534,
-0.13016657531261444,
-0.06321583688259125,
0.23060792684555054,
0.13441376388072968,
-0.05296929553151131,
0.024279816076159477,
-0.0377928763628006,
0.008667041547596455,
-0.008751154877245426,
0.09415408968925476,
0.07651394605636597,
0.11091575026512146,
-0.07709671556949615,
0.02875388041138649,
-0.0375838428735733,
-0.07896032184362411,
-0.19464430212974548,
-0.015736637637019157,
0.05567801371216774,
-0.02735324762761593,
-0.024381771683692932,
0.11113220453262329,
-0.1170382872223854,
-0.07107987999916077,
0.0899401381611824,
-0.10994853079319,
-0.09359642118215561,
-0.021627506241202354,
-0.01190157700330019,
0.019769007340073586,
0.08876805752515793,
0.03191718831658363,
0.040773436427116394,
0.05578889325261116,
-0.01265630777925253,
-0.054333169013261795,
-0.03072647750377655,
0.08201185613870621,
-0.08304253220558167,
0.25902724266052246,
-0.034163475036621094,
0.029553091153502464,
0.0744684636592865,
0.026195509359240532,
-0.16875551640987396,
0.029273536056280136,
0.053309619426727295,
-0.13627906143665314,
0.028024297207593918,
0.09564260393381119,
-0.04003889486193657,
-0.000514523999299854,
0.07736046612262726,
-0.015991710126399994,
0.001025190926156938,
0.06916497647762299,
0.05080709233880043,
-0.06356979161500931,
0.06798345595598221,
-0.13805343210697174,
0.11553630977869034,
0.11846182495355606,
-0.06155085563659668,
0.011672045104205608,
-0.02094418741762638,
0.024318164214491844,
0.031186753883957863,
0.08548983186483383,
-0.047430675476789474,
-0.13268961012363434,
0.003437184263020754,
-0.03540469706058502,
0.050898417830467224,
-0.24166327714920044,
-0.11891521513462067,
-0.03441694751381874,
-0.08172145485877991,
-0.04628082737326622,
0.09951373189687729,
0.14294232428073883,
-0.02245357446372509,
-0.014677582308650017,
-0.14198662340641022,
0.022399550303816795,
0.1489674150943756,
-0.0935978889465332,
-0.010670913383364677
] |
null | null | transformers |
# Open-LLM Benchmark Results:
MixtureofMerges-MoE-4x7b-v4 (As of 12/02/24 PB Score) on Open LLM Leaderboard📑
Average: 76.23
ARC: 72.53
HellaSwag: 88.85
MMLU: 64.53
TruthfulQA: 75.3
Winogrande: 84.85
GSM8K: 71.34
# MixtureofMerges-MoE-4x7b-v4
MixtureofMerges-MoE-4x7b-v4 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [flemmingmiguel/MBX-7B-v3](https://huggingface.co/flemmingmiguel/MBX-7B-v3)
* [Kukedlc/NeuTrixOmniBe-7B-model-remix](https://huggingface.co/Kukedlc/NeuTrixOmniBe-7B-model-remix)
* [PetroGPT/WestSeverus-7B-DPO](https://huggingface.co/PetroGPT/WestSeverus-7B-DPO)
* [vanillaOVO/supermario_v4](https://huggingface.co/vanillaOVO/supermario_v4)
## 🧩 Configuration
```yaml
base_model: Kukedlc/NeuTrixOmniBe-7B-model-remix
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: flemmingmiguel/MBX-7B-v3
positive_prompts:
- "Answer this question from the ARC (Argument Reasoning Comprehension)."
- "Use common sense and logical reasoning skills."
- "What assumptions does this argument rely on?"
- "Are these assumptions valid? Explain."
- "Could this be explained in a different way? Provide an alternative explanation."
- "Identify any weaknesses in this argument."
- "Does this argument contain any logical fallacies? If so, which ones?"
negative_prompts:
- "misses key evidence"
- "overly general"
- "focuses on irrelevant details"
- "assumes information not provided"
- "relies on stereotypes"
- source_model: Kukedlc/NeuTrixOmniBe-7B-model-remix
positive_prompts:
- "Answer this question, demonstrating commonsense understanding and using any relevant general knowledge you may have."
- "Provide a concise summary of this passage, then explain why the highlighted section is essential to the main idea."
- "Read these two brief articles presenting different viewpoints on the same topic. List their key arguments and highlight where they disagree."
- "Paraphrase this statement, changing the emotional tone but keeping the core meaning intact. Example: Rephrase a worried statement in a humorous way"
- "Create a short analogy that helps illustrate the main concept of this article."
negative_prompts:
- "sounds too basic"
- "understated"
- "dismisses important details"
- "avoids the question's nuance"
- "takes this statement too literally"
- source_model: PetroGPT/WestSeverus-7B-DPO
positive_prompts:
- "Calculate the answer to this math problem"
- "My mathematical capabilities are strong, allowing me to handle complex mathematical queries"
- "solve for"
- "A store sells apples at $0.50 each. If Emily buys 12 apples, how much does she need to pay?"
- "Isolate x in the following equation: 2x + 5 = 17"
- "Solve this equation and show your working."
- "Explain why you used this formula to solve the problem."
- "Attempt to divide this number by zero. Explain why this cannot be done."
negative_prompts:
- "incorrect"
- "inaccurate"
- "creativity"
- "assumed without proof"
- "rushed calculation"
- "confuses mathematical concepts"
- "draws illogical conclusions"
- "circular reasoning"
- source_model: vanillaOVO/supermario_v4
positive_prompts:
- "Generate a few possible continuations to this scenario."
- "Demonstrate understanding of everyday commonsense in your response."
- "Use contextual clues to determine the most likely outcome."
- "Continue this scenario, but make the writing style sound archaic and overly formal."
- "This narrative is predictable. Can you introduce an unexpected yet plausible twist?"
- "The character is angry. Continue this scenario showcasing a furious outburst."
negative_prompts:
- "repetitive phrases"
- "overuse of the same words"
- "contradicts earlier statements - breaks the internal logic of the scenario"
- "out of character dialogue"
- "awkward phrasing - sounds unnatural"
- "doesn't match the given genre"
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jsfs11/MixtureofMerges-MoE-4x7b-v4"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` | {"license": "apache-2.0", "tags": ["moe", "frankenmoe", "merge", "mergekit", "lazymergekit", "flemmingmiguel/MBX-7B-v3", "Kukedlc/NeuTrixOmniBe-7B-model-remix", "PetroGPT/WestSeverus-7B-DPO", "vanillaOVO/supermario_v4"], "base_model": ["flemmingmiguel/MBX-7B-v3", "Kukedlc/NeuTrixOmniBe-7B-model-remix", "PetroGPT/WestSeverus-7B-DPO", "vanillaOVO/supermario_v4"]} | text-generation | jsfs11/MixtureofMerges-MoE-4x7b-v4 | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"frankenmoe",
"merge",
"mergekit",
"lazymergekit",
"flemmingmiguel/MBX-7B-v3",
"Kukedlc/NeuTrixOmniBe-7B-model-remix",
"PetroGPT/WestSeverus-7B-DPO",
"vanillaOVO/supermario_v4",
"base_model:flemmingmiguel/MBX-7B-v3",
"base_model:Kukedlc/NeuTrixOmniBe-7B-model-remix",
"base_model:PetroGPT/WestSeverus-7B-DPO",
"base_model:vanillaOVO/supermario_v4",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T06:55:36+00:00 | [] | [] | TAGS
#transformers #safetensors #mixtral #text-generation #moe #frankenmoe #merge #mergekit #lazymergekit #flemmingmiguel/MBX-7B-v3 #Kukedlc/NeuTrixOmniBe-7B-model-remix #PetroGPT/WestSeverus-7B-DPO #vanillaOVO/supermario_v4 #base_model-flemmingmiguel/MBX-7B-v3 #base_model-Kukedlc/NeuTrixOmniBe-7B-model-remix #base_model-PetroGPT/WestSeverus-7B-DPO #base_model-vanillaOVO/supermario_v4 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Open-LLM Benchmark Results:
MixtureofMerges-MoE-4x7b-v4 (As of 12/02/24 PB Score) on Open LLM Leaderboard
Average: 76.23
ARC: 72.53
HellaSwag: 88.85
MMLU: 64.53
TruthfulQA: 75.3
Winogrande: 84.85
GSM8K: 71.34
# MixtureofMerges-MoE-4x7b-v4
MixtureofMerges-MoE-4x7b-v4 is a Mixure of Experts (MoE) made with the following models using LazyMergekit:
* flemmingmiguel/MBX-7B-v3
* Kukedlc/NeuTrixOmniBe-7B-model-remix
* PetroGPT/WestSeverus-7B-DPO
* vanillaOVO/supermario_v4
## Configuration
## Usage
| [
"# Open-LLM Benchmark Results:\nMixtureofMerges-MoE-4x7b-v4 (As of 12/02/24 PB Score) on Open LLM Leaderboard\nAverage: 76.23\nARC: 72.53\nHellaSwag: 88.85\nMMLU: 64.53\nTruthfulQA: 75.3\nWinogrande: 84.85\nGSM8K: 71.34",
"# MixtureofMerges-MoE-4x7b-v4\n\nMixtureofMerges-MoE-4x7b-v4 is a Mixure of Experts (MoE) made with the following models using LazyMergekit:\n* flemmingmiguel/MBX-7B-v3\n* Kukedlc/NeuTrixOmniBe-7B-model-remix\n* PetroGPT/WestSeverus-7B-DPO\n* vanillaOVO/supermario_v4",
"## Configuration",
"## Usage"
] | [
"TAGS\n#transformers #safetensors #mixtral #text-generation #moe #frankenmoe #merge #mergekit #lazymergekit #flemmingmiguel/MBX-7B-v3 #Kukedlc/NeuTrixOmniBe-7B-model-remix #PetroGPT/WestSeverus-7B-DPO #vanillaOVO/supermario_v4 #base_model-flemmingmiguel/MBX-7B-v3 #base_model-Kukedlc/NeuTrixOmniBe-7B-model-remix #base_model-PetroGPT/WestSeverus-7B-DPO #base_model-vanillaOVO/supermario_v4 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Open-LLM Benchmark Results:\nMixtureofMerges-MoE-4x7b-v4 (As of 12/02/24 PB Score) on Open LLM Leaderboard\nAverage: 76.23\nARC: 72.53\nHellaSwag: 88.85\nMMLU: 64.53\nTruthfulQA: 75.3\nWinogrande: 84.85\nGSM8K: 71.34",
"# MixtureofMerges-MoE-4x7b-v4\n\nMixtureofMerges-MoE-4x7b-v4 is a Mixure of Experts (MoE) made with the following models using LazyMergekit:\n* flemmingmiguel/MBX-7B-v3\n* Kukedlc/NeuTrixOmniBe-7B-model-remix\n* PetroGPT/WestSeverus-7B-DPO\n* vanillaOVO/supermario_v4",
"## Configuration",
"## Usage"
] | [
208,
88,
111,
4,
3
] | [
"passage: TAGS\n#transformers #safetensors #mixtral #text-generation #moe #frankenmoe #merge #mergekit #lazymergekit #flemmingmiguel/MBX-7B-v3 #Kukedlc/NeuTrixOmniBe-7B-model-remix #PetroGPT/WestSeverus-7B-DPO #vanillaOVO/supermario_v4 #base_model-flemmingmiguel/MBX-7B-v3 #base_model-Kukedlc/NeuTrixOmniBe-7B-model-remix #base_model-PetroGPT/WestSeverus-7B-DPO #base_model-vanillaOVO/supermario_v4 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Open-LLM Benchmark Results:\nMixtureofMerges-MoE-4x7b-v4 (As of 12/02/24 PB Score) on Open LLM Leaderboard\nAverage: 76.23\nARC: 72.53\nHellaSwag: 88.85\nMMLU: 64.53\nTruthfulQA: 75.3\nWinogrande: 84.85\nGSM8K: 71.34# MixtureofMerges-MoE-4x7b-v4\n\nMixtureofMerges-MoE-4x7b-v4 is a Mixure of Experts (MoE) made with the following models using LazyMergekit:\n* flemmingmiguel/MBX-7B-v3\n* Kukedlc/NeuTrixOmniBe-7B-model-remix\n* PetroGPT/WestSeverus-7B-DPO\n* vanillaOVO/supermario_v4## Configuration## Usage"
] | [
-0.08623211830854416,
0.16653816401958466,
-0.007155946455895901,
0.043100882321596146,
0.0602947399020195,
0.04128309711813927,
0.049939051270484924,
0.12460345029830933,
0.03039136342704296,
0.14284957945346832,
0.05085078999400139,
0.1493411362171173,
0.08165758103132248,
0.10516928136348724,
-0.00008195851842174307,
-0.1223832443356514,
0.04003977030515671,
-0.03562799468636513,
-0.006891465280205011,
0.10999973863363266,
0.07165646553039551,
-0.07978464663028717,
0.09159159660339355,
0.005861502606421709,
-0.07398537546396255,
-0.005903397221118212,
-0.02622132934629917,
-0.01519570592790842,
0.009790110401809216,
0.06420908123254776,
-0.02797825075685978,
0.02975054457783699,
-0.00995019730180502,
-0.17334304749965668,
0.02151157520711422,
0.023336123675107956,
-0.048107318580150604,
0.07107966393232346,
0.1289547085762024,
-0.07934189587831497,
0.0929771363735199,
-0.0993553176522255,
0.012941054068505764,
0.0899018868803978,
-0.14379829168319702,
-0.15400677919387817,
-0.17469888925552368,
0.12111735343933105,
0.10795315355062485,
0.06014784798026085,
-0.05285632237792015,
0.0933745801448822,
0.019378116354346275,
0.07810208201408386,
0.29194527864456177,
-0.2550043761730194,
-0.055385638028383255,
0.11712253838777542,
0.04212159663438797,
-0.07693347334861755,
-0.04629356786608696,
0.05624684691429138,
0.023010430857539177,
-0.006380707956850529,
-0.02105262316763401,
-0.0504743717610836,
0.16581948101520538,
-0.013679565861821175,
-0.08004463464021683,
-0.018383638933300972,
0.059175070375204086,
0.09238989651203156,
-0.030057065188884735,
-0.13854335248470306,
-0.00554649019613862,
-0.09089843928813934,
-0.05637884512543678,
-0.005927018355578184,
0.006780583411455154,
-0.04057707637548447,
-0.02849879302084446,
0.054878365248441696,
-0.005257881246507168,
-0.03945189341902733,
-0.023243943229317665,
0.1277221292257309,
-0.010070315562188625,
-0.0074897874146699905,
0.0285808015614748,
0.0770777016878128,
-0.019985852763056755,
-0.16766555607318878,
-0.055914271622896194,
-0.020744310691952705,
-0.10581985116004944,
0.01616794988512993,
0.022422634065151215,
0.015245355665683746,
0.10339616984128952,
0.15893039107322693,
-0.05179508775472641,
0.08587942272424698,
0.0805632472038269,
-0.0003049219667445868,
0.012241111136972904,
0.05081724375486374,
-0.09997360408306122,
-0.1990486979484558,
-0.034015852957963943,
0.01633659191429615,
0.023822853341698647,
-0.004381501581519842,
-0.00011376795009709895,
-0.02142726071178913,
0.025448977947235107,
0.08160573244094849,
0.1157984808087349,
0.032293274998664856,
-0.1214967891573906,
-0.060521360486745834,
0.15636982023715973,
-0.09806197881698608,
0.04534263536334038,
0.02762533351778984,
-0.06690867245197296,
-0.018142657354474068,
0.02406061254441738,
0.0332917682826519,
-0.030453767627477646,
0.09933210164308548,
-0.06941540539264679,
-0.03433816507458687,
-0.01884905993938446,
-0.06881247460842133,
0.07136894762516022,
-0.014632055535912514,
-0.04627105966210365,
-0.09185676276683807,
-0.07165710628032684,
-0.11967042833566666,
0.0019796115811914206,
-0.06980285793542862,
-0.029311344027519226,
-0.023415302857756615,
-0.030570093542337418,
0.03917410597205162,
0.01996639370918274,
0.06702516973018646,
-0.03206819295883179,
0.0322728231549263,
-0.02387620136141777,
0.05216560885310173,
0.08518344163894653,
0.028020726516842842,
-0.03367186337709427,
0.06724539399147034,
-0.17468930780887604,
0.06881926953792572,
-0.14212851226329803,
0.09070061892271042,
-0.19542047381401062,
-0.057836469262838364,
-0.004048206843435764,
-0.0190912913531065,
0.07212084531784058,
0.1485963612794876,
-0.12402352690696716,
-0.08538113534450531,
0.14130772650241852,
-0.06062299758195877,
-0.15434673428535461,
0.03200380876660347,
0.03965695574879646,
-0.017590433359146118,
0.0795239582657814,
0.09388847649097443,
0.10785450786352158,
-0.06578457355499268,
-0.11621211469173431,
-0.11685046553611755,
0.05031423270702362,
0.10716358572244644,
0.08123136311769485,
-0.10926666855812073,
0.0007698751869611442,
0.03773651644587517,
0.005444408394396305,
0.016909616068005562,
-0.05424138531088829,
-0.027699239552021027,
0.005745491944253445,
-0.05333137884736061,
0.04502050206065178,
0.00657515088096261,
-0.028971495106816292,
-0.07827752083539963,
-0.09494401514530182,
-0.02512158825993538,
0.11647431552410126,
0.016239076852798462,
-0.0021996577270329,
-0.11963455379009247,
0.11759846657514572,
0.005911420565098524,
0.024133384227752686,
-0.13905788958072662,
-0.06933286041021347,
0.009797902777791023,
-0.11897313594818115,
-0.004612778313457966,
-0.10599944740533829,
0.07983192056417465,
0.006497775204479694,
-0.046643275767564774,
-0.05314694344997406,
0.02237168326973915,
0.0037656708154827356,
-0.0313369557261467,
-0.17668598890304565,
-0.05319888889789581,
-0.009878307580947876,
0.12018554657697678,
-0.052123282104730606,
-0.005335679277777672,
0.10722276568412781,
0.20085914433002472,
0.03253624215722084,
-0.1065451130270958,
0.057341568171978,
0.01930096745491028,
0.030876899138092995,
-0.03335987403988838,
0.040484555065631866,
-0.01901598833501339,
-0.09023024886846542,
0.055452365428209305,
-0.13339824974536896,
0.0883818194270134,
0.08492147922515869,
0.07302496582269669,
-0.08328066021203995,
-0.02251456491649151,
-0.013674638234078884,
-0.02861926704645157,
0.011535217985510826,
-0.04750484228134155,
0.042520225048065186,
0.05252480134367943,
0.05179614573717117,
-0.05235738307237625,
-0.10234586894512177,
0.021654685959219933,
0.03351666405797005,
-0.03365466371178627,
0.16649121046066284,
0.004717291332781315,
-0.20327624678611755,
0.06988845020532608,
0.09903133660554886,
0.1206204891204834,
0.1310223788022995,
-0.0035746144130825996,
-0.011477558873593807,
-0.11680819094181061,
0.004238734021782875,
0.046126753091812134,
0.01721716858446598,
-0.1046162098646164,
0.03792884573340416,
0.053054891526699066,
0.006151906680315733,
0.020263444632291794,
-0.04317258670926094,
0.008064232766628265,
0.009091377258300781,
-0.027154527604579926,
0.050877645611763,
0.12216201424598694,
-0.026786185801029205,
0.06629516184329987,
0.030355026945471764,
0.046093836426734924,
-0.04303046315908432,
-0.05473800748586655,
-0.10176127403974533,
0.13321559131145477,
-0.13880327343940735,
-0.12316204607486725,
-0.0770793929696083,
-0.0771019235253334,
-0.09713944047689438,
-0.03578510507941246,
0.048513926565647125,
-0.08906514197587967,
-0.06572313606739044,
-0.04779767990112305,
0.05462127551436424,
0.034729063510894775,
-0.013973594643175602,
0.07540619373321533,
-0.012030222453176975,
0.047653306275606155,
-0.1177150085568428,
-0.01667734794318676,
0.009274248965084553,
-0.05622407793998718,
0.01169707253575325,
0.00646569486707449,
0.1198417991399765,
0.09730891138315201,
0.08637140691280365,
0.026121720671653748,
-0.00018624181393533945,
0.3033153712749481,
-0.10027360171079636,
0.031247960403561592,
0.10416071116924286,
0.04286658391356468,
0.05848531424999237,
0.09883511811494827,
0.048265039920806885,
-0.06904107332229614,
0.01180603913962841,
0.0615745447576046,
0.003558867145329714,
-0.23300643265247345,
-0.07810667157173157,
-0.0326463058590889,
0.036403682082891464,
0.040229134261608124,
0.060034796595573425,
0.013693214394152164,
0.0537467785179615,
-0.05915633589029312,
-0.07300318032503128,
0.06161889433860779,
0.05581680312752724,
0.09910686314105988,
0.013109193183481693,
0.08017875999212265,
-0.04649439454078674,
0.020830275490880013,
0.0822213888168335,
-0.04984116926789284,
0.10387835651636124,
0.056999608874320984,
0.15094120800495148,
0.07820142060518265,
0.06313501298427582,
-0.0063060880638659,
0.04006817191839218,
0.024804923683404922,
0.0015359255485236645,
0.03287573903799057,
-0.0874757468700409,
-0.0023634873796254396,
0.021283844485878944,
0.07461122423410416,
0.0183882936835289,
-0.046237628906965256,
-0.0230928435921669,
0.09410053491592407,
0.15571683645248413,
0.07414223253726959,
-0.1634947508573532,
-0.05192667618393898,
0.019233589991927147,
-0.005902840290218592,
-0.03078162856400013,
-0.03440220281481743,
-0.03982498124241829,
-0.12387571483850479,
0.16891099512577057,
0.009257680736482143,
0.10843873023986816,
-0.04255659878253937,
-0.021558070555329323,
0.034621741622686386,
0.04570866376161575,
-0.02178223989903927,
0.026841746643185616,
-0.13028433918952942,
0.15411457419395447,
0.025655392557382584,
0.021014399826526642,
0.013284560292959213,
0.02115117944777012,
0.03266887366771698,
0.0174344964325428,
0.13969677686691284,
0.03617566078901291,
-0.0979844331741333,
-0.11837229877710342,
-0.05829019844532013,
-0.025172065943479538,
0.07191184908151627,
-0.13146641850471497,
0.0982072576880455,
0.03685827553272247,
-0.07137925922870636,
-0.04252238944172859,
0.04534778743982315,
-0.17528726160526276,
-0.06563076376914978,
0.08759249001741409,
-0.03189879283308983,
0.07579430937767029,
-0.08858734369277954,
-0.054101500660181046,
-0.14349457621574402,
0.15688997507095337,
-0.0722028985619545,
-0.05565644055604935,
-0.11549293994903564,
-0.02811376005411148,
0.15370507538318634,
-0.11284893751144409,
0.0524158850312233,
-0.028688417747616768,
0.0847030058503151,
-0.002586985006928444,
-0.039507944136857986,
0.08026856184005737,
-0.0718919187784195,
-0.19124868512153625,
-0.016316231340169907,
0.1572025865316391,
0.031991250813007355,
0.02371092326939106,
-0.0009465241455473006,
0.07784043252468109,
0.032212309539318085,
-0.11976240575313568,
0.11760522425174713,
0.09824295341968536,
0.006657774560153484,
0.07089317589998245,
0.042452432215213776,
-0.06884555518627167,
-0.06863464415073395,
-0.05078481137752533,
0.0775570496916771,
0.33803895115852356,
-0.05577809363603592,
0.07832997292280197,
0.02353525534272194,
-0.06259019672870636,
-0.15857689082622528,
-0.05262969061732292,
0.072333425283432,
-0.01601533405482769,
0.04990142583847046,
-0.1308300495147705,
0.0517963245511055,
0.07380089163780212,
-0.013969541527330875,
0.08314993977546692,
-0.30248406529426575,
-0.14888493716716766,
0.03772618994116783,
0.045483652502298355,
-0.013668090105056763,
-0.1432274430990219,
-0.12018924951553345,
-0.059052154421806335,
-0.30558642745018005,
0.031458720564842224,
0.005493637640029192,
0.07383430004119873,
-0.03428115323185921,
-0.003232038114219904,
0.03169207274913788,
-0.014777137897908688,
0.1868872344493866,
0.05077888071537018,
0.023888055235147476,
-0.07486910372972488,
-0.028829425573349,
0.022353140637278557,
-0.037693608552217484,
0.0047129178419709206,
-0.02853246219456196,
0.04107163846492767,
-0.14269398152828217,
-0.014428974129259586,
-0.06760567426681519,
0.021932411938905716,
-0.07775796204805374,
0.008335708640515804,
-0.04874194785952568,
0.0827658548951149,
0.063360795378685,
-0.0026956922374665737,
0.05188976600766182,
-0.06237835809588432,
0.11068751662969589,
0.14598150551319122,
0.05648623779416084,
0.023486537858843803,
-0.1442103385925293,
-0.015898320823907852,
-0.027767229825258255,
0.009674151428043842,
-0.04507249593734741,
0.035906363278627396,
0.10609973967075348,
0.047994282096624374,
0.09177695959806442,
0.0015732268802821636,
-0.13841870427131653,
-0.01349580381065607,
0.09432841837406158,
-0.11210548877716064,
-0.1305358111858368,
-0.020065734162926674,
-0.03706899285316467,
-0.04506449028849602,
-0.03673982247710228,
0.13194139301776886,
0.05428410321474075,
-0.04529238119721413,
0.03433092311024666,
0.07173332571983337,
-0.032690905034542084,
0.20360085368156433,
-0.01697511598467827,
0.061391428112983704,
-0.1130061000585556,
0.07108518481254578,
0.04317410662770271,
-0.031035950407385826,
0.0011660116724669933,
0.11677177995443344,
-0.055406805127859116,
-0.04272298887372017,
-0.061461593955755234,
0.1447407603263855,
-0.015457745641469955,
-0.007858344353735447,
-0.06135496869683266,
-0.10839550197124481,
0.07635975629091263,
0.05319160223007202,
0.04636275768280029,
0.03297249600291252,
0.0914967730641365,
-0.014059889130294323,
0.051526959985494614,
0.09468633681535721,
0.13398225605487823,
0.042860958725214005,
-0.10757549852132797,
0.02231164649128914,
-0.025598030537366867,
-0.006302374880760908,
0.019853901118040085,
0.010829013772308826,
-0.12520284950733185,
-0.027418803423643112,
-0.14999599754810333,
-0.022682057693600655,
-0.12651647627353668,
-0.01975083537399769,
-0.030608544126152992,
-0.014878727495670319,
-0.045688044279813766,
-0.0022903955541551113,
-0.07589039951562881,
-0.09146296977996826,
-0.020317034795880318,
0.09554186463356018,
-0.09951431304216385,
-0.01024684589356184,
0.06615758687257767,
-0.060136716812849045,
0.08653146773576736,
0.03590774908661842,
0.03478802368044853,
-0.011830754578113556,
-0.14008064568042755,
-0.04292327165603638,
0.01143769919872284,
-0.03153199329972267,
0.0044116429053246975,
-0.23904874920845032,
-0.004042255226522684,
-0.06076045334339142,
-0.04070845991373062,
0.02116943523287773,
0.027720728889107704,
-0.13757085800170898,
-0.05873517692089081,
-0.03438623994588852,
-0.021373029798269272,
-0.05753535032272339,
0.02061495929956436,
0.0952598825097084,
0.04435531049966812,
0.09733022004365921,
-0.034891486167907715,
0.06421501934528351,
-0.19168101251125336,
-0.006004746071994305,
-0.0017580032581463456,
-0.05274668335914612,
0.03550399839878082,
0.019288284704089165,
0.08198610693216324,
-0.010842348448932171,
0.045294806361198425,
-0.03238135203719139,
-0.13077034056186676,
0.03723623603582382,
-0.026101430878043175,
-0.0015573027776554227,
0.012407064437866211,
0.101612888276577,
0.01756959594786167,
0.013126786798238754,
0.026972807943820953,
0.036091819405555725,
-0.037312429398298264,
-0.02111860364675522,
0.10781653970479965,
0.1252381056547165,
0.08100582659244537,
0.020201222971081734,
0.06963946670293808,
-0.10089205205440521,
0.0021650707349181175,
0.061939675360918045,
-0.07920318096876144,
0.10607060045003891,
-0.05088474601507187,
0.0370350182056427,
0.07264283299446106,
-0.17826783657073975,
0.07366461306810379,
-0.029880501329898834,
-0.015132637694478035,
-0.07655839622020721,
-0.11453588306903839,
-0.09027107805013657,
-0.10434717684984207,
0.0343981571495533,
-0.09639602154493332,
0.06930477172136307,
-0.052654046565294266,
0.015777239575982094,
0.01053771935403347,
0.08976485580205917,
-0.09665122628211975,
-0.05487760528922081,
0.09882256388664246,
0.003069484606385231,
-0.08331932872533798,
0.018286913633346558,
0.003929898142814636,
0.03297905623912811,
0.04589634761214256,
0.016246294602751732,
0.03306938335299492,
-0.1054392009973526,
0.04817350581288338,
-0.008496121503412724,
-0.10439051687717438,
-0.007179057225584984,
0.027028683573007584,
0.02677931822836399,
0.1413453370332718,
0.04441721737384796,
0.03964059799909592,
-0.017772473394870758,
0.1548834890127182,
-0.02531972900032997,
-0.03067423589527607,
-0.0916934609413147,
-0.00882258452475071,
-0.0015870924107730389,
0.011715003289282322,
0.042178645730018616,
-0.08364339917898178,
0.02998587302863598,
0.10640744119882584,
0.1544867753982544,
0.02103184349834919,
0.014339308254420757,
0.013374721631407738,
0.015275959856808186,
0.05013818293809891,
0.02346653863787651,
0.04178806021809578,
0.14069880545139313,
-0.03755886107683182,
0.07533174008131027,
-0.02702919952571392,
-0.07697495073080063,
-0.01475305762141943,
0.05135679617524147,
0.03277472034096718,
-0.01862611062824726,
-0.018942633643746376,
0.13451926410198212,
-0.08028047531843185,
-0.1261620819568634,
0.04911774769425392,
-0.1421733945608139,
-0.1573377549648285,
-0.03978079929947853,
0.0442015677690506,
0.10163984447717667,
0.10352686792612076,
0.0278242789208889,
-0.039697274565696716,
0.15487946569919586,
0.01767439767718315,
-0.09694403409957886,
-0.13030526041984558,
0.0280081108212471,
-0.07536756992340088,
0.1724396049976349,
-0.015868009999394417,
0.06099267676472664,
0.13019728660583496,
-0.028514353558421135,
-0.13868510723114014,
0.023225216194987297,
0.04722091928124428,
-0.12172669917345047,
0.04218699038028717,
0.1384573131799698,
0.016304364427924156,
0.04583217576146126,
0.04860127717256546,
-0.03427153453230858,
0.026357805356383324,
0.05534568056464195,
0.01458557415753603,
-0.08402413129806519,
0.1151375025510788,
-0.08162693679332733,
0.12349259853363037,
0.1725354939699173,
-0.08292010426521301,
0.009515553712844849,
-0.020614488050341606,
0.03331718593835831,
0.002638493198901415,
0.05376707762479782,
-0.028729107230901718,
-0.18640434741973877,
0.0697157084941864,
0.006635888479650021,
0.05248786509037018,
-0.1387484073638916,
-0.08675070106983185,
-0.03080429881811142,
-0.0252150259912014,
-0.011070550419390202,
0.1418139636516571,
0.043239448219537735,
-0.008917083963751793,
-0.016291875392198563,
-0.1404813528060913,
0.00209701806306839,
0.1420169472694397,
-0.10998691618442535,
-0.08297421038150787
] |
null | null | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 0.11094751209020615
f1_macro: 0.969943620778024
f1_micro: 0.97
f1_weighted: 0.9699436207780239
precision_macro: 0.9722943722943723
precision_micro: 0.97
precision_weighted: 0.9722943722943722
recall_macro: 0.97
recall_micro: 0.97
recall_weighted: 0.97
accuracy: 0.97
| {"tags": ["autotrain", "image-classification"], "datasets": ["autotrain-wa6y6-kdrt6/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "example_title": "Teapot"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg", "example_title": "Palace"}]} | image-classification | chetinator/autotrain-wa6y6-kdrt6 | [
"transformers",
"safetensors",
"vit",
"image-classification",
"autotrain",
"dataset:autotrain-wa6y6-kdrt6/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T06:57:30+00:00 | [] | [] | TAGS
#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-wa6y6-kdrt6/autotrain-data #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metricsg
loss: 0.11094751209020615
f1_macro: 0.969943620778024
f1_micro: 0.97
f1_weighted: 0.9699436207780239
precision_macro: 0.9722943722943723
precision_micro: 0.97
precision_weighted: 0.9722943722943722
recall_macro: 0.97
recall_micro: 0.97
recall_weighted: 0.97
accuracy: 0.97
| [
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 0.11094751209020615\n\nf1_macro: 0.969943620778024\n\nf1_micro: 0.97\n\nf1_weighted: 0.9699436207780239\n\nprecision_macro: 0.9722943722943723\n\nprecision_micro: 0.97\n\nprecision_weighted: 0.9722943722943722\n\nrecall_macro: 0.97\n\nrecall_micro: 0.97\n\nrecall_weighted: 0.97\n\naccuracy: 0.97"
] | [
"TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-wa6y6-kdrt6/autotrain-data #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\n- Problem type: Image Classification",
"## Validation Metricsg\nloss: 0.11094751209020615\n\nf1_macro: 0.969943620778024\n\nf1_micro: 0.97\n\nf1_weighted: 0.9699436207780239\n\nprecision_macro: 0.9722943722943723\n\nprecision_micro: 0.97\n\nprecision_weighted: 0.9722943722943722\n\nrecall_macro: 0.97\n\nrecall_micro: 0.97\n\nrecall_weighted: 0.97\n\naccuracy: 0.97"
] | [
64,
16,
122
] | [
"passage: TAGS\n#transformers #safetensors #vit #image-classification #autotrain #dataset-autotrain-wa6y6-kdrt6/autotrain-data #autotrain_compatible #endpoints_compatible #region-us \n# Model Trained Using AutoTrain\n\n- Problem type: Image Classification## Validation Metricsg\nloss: 0.11094751209020615\n\nf1_macro: 0.969943620778024\n\nf1_micro: 0.97\n\nf1_weighted: 0.9699436207780239\n\nprecision_macro: 0.9722943722943723\n\nprecision_micro: 0.97\n\nprecision_weighted: 0.9722943722943722\n\nrecall_macro: 0.97\n\nrecall_micro: 0.97\n\nrecall_weighted: 0.97\n\naccuracy: 0.97"
] | [
-0.1211472749710083,
0.10519763082265854,
0.0004807523509953171,
0.1175958663225174,
0.12988434731960297,
0.025831717997789383,
0.08393818140029907,
0.11394453793764114,
-0.06589604914188385,
0.10326825827360153,
0.14223715662956238,
0.10382239520549774,
0.03815102577209473,
0.17573042213916779,
-0.12439786642789841,
-0.1824498027563095,
0.024572672322392464,
0.019933601841330528,
0.06976605951786041,
0.07221613824367523,
0.0753663033246994,
-0.14002440869808197,
0.09591599553823471,
-0.03314156085252762,
-0.2786073684692383,
0.024155838415026665,
0.13703641295433044,
-0.10666622966527939,
0.09674535691738129,
0.0771246999502182,
0.10649053752422333,
-0.0006337405648082495,
0.12281765043735504,
-0.02723284251987934,
-0.008703948929905891,
0.014805274084210396,
0.016477199271321297,
0.058429818600416183,
0.15401649475097656,
0.028599541634321213,
-0.09255151450634003,
-0.05369142070412636,
0.04824301227927208,
0.041382431983947754,
-0.06487586349248886,
-0.08890315890312195,
-0.09327910840511322,
0.0662231594324112,
0.09030843526124954,
0.07070739567279816,
-0.014595073647797108,
0.18376517295837402,
-0.07251839339733124,
0.07804232090711594,
0.06761261075735092,
-0.22613045573234558,
-0.0779152661561966,
0.1766032874584198,
-0.06174121052026749,
-0.052783504128456116,
-0.07874439656734467,
0.08920992165803909,
0.1154850497841835,
-0.007336053065955639,
0.029733119532465935,
-0.027319151908159256,
-0.05803715065121651,
0.016299430280923843,
-0.11303572356700897,
0.012069215066730976,
0.20249438285827637,
0.014244881458580494,
-0.044622309505939484,
-0.11001140624284744,
-0.041993044316768646,
-0.09409860521554947,
-0.07129044830799103,
-0.051983557641506195,
0.004270574543625116,
-0.06187338009476662,
-0.08599095791578293,
0.09901757538318634,
-0.060926761478185654,
-0.10558299720287323,
-0.14762409031391144,
0.07848680764436722,
-0.0006543805939145386,
0.021683963015675545,
-0.0037242097314447165,
0.04549309238791466,
-0.09925127029418945,
-0.08527885377407074,
0.028206443414092064,
-0.014079282060265541,
-0.08865415304899216,
-0.08137644827365875,
0.0003560860932338983,
-0.04951741546392441,
0.014462708495557308,
0.07689838856458664,
0.05043985694646835,
0.042433544993400574,
-0.034392546862363815,
0.010314936749637127,
-0.05094902217388153,
0.19288665056228638,
-0.1259918063879013,
-0.0708673894405365,
0.030346965417265892,
0.02011200226843357,
0.020595349371433258,
0.0056688254699110985,
-0.09190976619720459,
-0.07714620977640152,
0.14718030393123627,
0.03471001237630844,
-0.03295044228434563,
0.0399293377995491,
-0.055926043540239334,
-0.02119150198996067,
-0.04752833768725395,
-0.06996189057826996,
0.0426979623734951,
-0.066403828561306,
-0.09611200541257858,
0.02793663553893566,
0.00461013987660408,
0.018935557454824448,
-0.016876952722668648,
0.13655973970890045,
-0.13568207621574402,
0.015621760860085487,
-0.07086244970560074,
-0.12288475781679153,
0.019068414345383644,
-0.05546499788761139,
-0.007617195602506399,
-0.12174772471189499,
-0.19000843167304993,
-0.02061026729643345,
-0.05589601770043373,
-0.1049264520406723,
-0.0152461351826787,
-0.00996372476220131,
-0.06328163295984268,
0.06327012926340103,
0.030243193730711937,
0.10232127457857132,
-0.013142026960849762,
0.044219721108675,
0.056255850940942764,
0.09220807254314423,
-0.022357769310474396,
0.014650481753051281,
-0.07330190390348434,
-0.0019567108247429132,
-0.20758071541786194,
0.024965696036815643,
-0.053277671337127686,
0.057552922517061234,
-0.08949846774339676,
0.00042735665920190513,
0.06403670459985733,
-0.01272051502019167,
0.03355036675930023,
0.16868823766708374,
-0.154932901263237,
-0.01569628342986107,
0.08660098910331726,
-0.08841074258089066,
-0.09752223640680313,
0.12276749312877655,
-0.004867244977504015,
0.01461052242666483,
0.0476541742682457,
0.1046791598200798,
0.025691013783216476,
-0.09753045439720154,
-0.03345731645822525,
-0.05172267556190491,
-0.05027741566300392,
-0.029278138652443886,
0.08970323204994202,
0.000741859374102205,
-0.1778242439031601,
0.010936915874481201,
0.030360789969563484,
0.013169599696993828,
-0.09095724672079086,
-0.0542251281440258,
-0.0444720983505249,
-0.06139786168932915,
0.06072373315691948,
0.022784799337387085,
0.0611068531870842,
-0.08650518208742142,
-0.03156938776373863,
0.07181884348392487,
0.0852600708603859,
0.01803268864750862,
-0.06396111845970154,
-0.1107201874256134,
0.09082401543855667,
-0.20176203548908234,
-0.027577610686421394,
-0.13806109130382538,
-0.0769270732998848,
0.02165891043841839,
0.017152413725852966,
-0.01350759994238615,
-0.05302149057388306,
0.08008253574371338,
0.05635302886366844,
-0.07014250755310059,
-0.0391261987388134,
0.0793176144361496,
0.015271507203578949,
-0.13544072210788727,
-0.12295706570148468,
0.030222510918974876,
-0.00029882637318223715,
0.18702176213264465,
-0.18231190741062164,
-0.025154924020171165,
0.04193924739956856,
0.07918034493923187,
0.04555647447705269,
0.021771781146526337,
-0.01384943537414074,
0.0321556031703949,
-0.0330883152782917,
-0.059665970504283905,
0.05671754106879234,
-0.02722589299082756,
-0.03942999243736267,
0.03966318443417549,
-0.21739958226680756,
0.2377593070268631,
0.1365489363670349,
-0.02168014831840992,
-0.10422687977552414,
-0.05292395502328873,
0.017380649223923683,
-0.05172759294509888,
-0.1252632737159729,
-0.009316221810877323,
-0.039240751415491104,
-0.03135782107710838,
0.10808917880058289,
-0.06618960201740265,
-0.04162371903657913,
0.046558987349271774,
-0.006607040762901306,
-0.0843304693698883,
0.11932950466871262,
0.021458541974425316,
-0.16003243625164032,
0.14274892210960388,
0.10429015010595322,
-0.1134205162525177,
0.12177355587482452,
0.024573173373937607,
-0.06412961333990097,
-0.0520903654396534,
-0.06804050505161285,
0.040546201169490814,
0.12444878369569778,
0.024209529161453247,
0.015426775440573692,
0.055567797273397446,
-0.017886485904455185,
-0.023411842063069344,
-0.11923976987600327,
-0.012146411463618279,
0.0029806613456457853,
0.02089865319430828,
0.06712716072797775,
0.013818454928696156,
0.0472588986158371,
0.177858367562294,
0.006753723602741957,
-0.056302543729543686,
0.06472637504339218,
-0.004119568970054388,
-0.07478619366884232,
0.1792227327823639,
-0.08545482158660889,
-0.19822372496128082,
-0.15955999493598938,
-0.0462830625474453,
-0.11206768453121185,
0.014620504342019558,
-0.011884280480444431,
-0.09124424308538437,
-0.10771478712558746,
-0.06828274577856064,
0.008043445646762848,
-0.004944664891809225,
0.008613279089331627,
0.002302495064213872,
-0.028403718024492264,
0.04406218230724335,
-0.04106565937399864,
-0.03987756744027138,
-0.0038001365028321743,
-0.04368545114994049,
0.11648615449666977,
0.015870295464992523,
0.14729167520999908,
0.14494387805461884,
-0.06189996004104614,
0.03948545083403587,
-0.046175941824913025,
0.11839890480041504,
-0.0371023528277874,
0.019343441352248192,
0.1732025295495987,
0.06046542152762413,
0.004463443532586098,
0.16033326089382172,
0.003778198966756463,
-0.07981448620557785,
0.04111933708190918,
0.05759505182504654,
-0.021065905690193176,
-0.11061877757310867,
-0.1349058449268341,
0.0008447852451354265,
0.04610394686460495,
0.11194329708814621,
0.021965328603982925,
0.1006261482834816,
0.12748746573925018,
0.030353644862771034,
0.1043652892112732,
-0.035562291741371155,
0.08437233418226242,
0.11162665486335754,
0.030414223670959473,
0.19012506306171417,
-0.059051983058452606,
-0.05395887792110443,
0.09402719140052795,
-0.04460415244102478,
0.06345535069704056,
0.03355076536536217,
-0.026114115491509438,
-0.010068717412650585,
0.10191546380519867,
0.10023735463619232,
0.09129208326339722,
0.05645092949271202,
-0.06401382386684418,
0.01855047047138214,
-0.08842162042856216,
-0.022315455600619316,
0.029701044782996178,
0.025251351296901703,
0.07957574725151062,
-0.11377006769180298,
0.07063911110162735,
0.0627775639295578,
0.11816044896841049,
0.1086934506893158,
-0.43232619762420654,
-0.045990049839019775,
0.04294757544994354,
0.04318614676594734,
-0.10798473656177521,
0.006593784783035517,
0.06757119297981262,
-0.1098339706659317,
0.04958758130669594,
-0.07125068455934525,
0.07763683050870895,
-0.0033070954959839582,
-0.010406444780528545,
-0.02290879189968109,
0.062217358499765396,
-0.03714767098426819,
0.049457747489213943,
-0.24337534606456757,
0.16819757223129272,
0.05824211612343788,
0.026442253962159157,
-0.09559991955757141,
-0.0021720470394939184,
0.08450828492641449,
0.08067729324102402,
0.15413635969161987,
-0.025245876982808113,
-0.10338568687438965,
-0.2862261235713959,
-0.07988505065441132,
-0.02300320193171501,
0.033911336213350296,
0.0003295477363280952,
0.07693693786859512,
-0.07741932570934296,
-0.03321210667490959,
0.02875869907438755,
0.004510019905865192,
-0.13722944259643555,
-0.03332982212305069,
0.0016915802843868732,
0.09846866875886917,
0.007757901214063168,
-0.05945644900202751,
-0.10000284761190414,
-0.1081932932138443,
0.09640763700008392,
-0.0531991682946682,
-0.012782215140759945,
-0.17583248019218445,
0.13049300014972687,
0.07438600808382034,
-0.06525102257728577,
0.05086715519428253,
-0.025449279695749283,
0.15108372271060944,
0.006245874334126711,
-0.10359200835227966,
0.13387605547904968,
-0.09380640834569931,
-0.11516081541776657,
-0.043415557593107224,
0.03681386634707451,
-0.04641767218708992,
0.04070139303803444,
0.03409058228135109,
0.06300903856754303,
0.036769475787878036,
-0.07952434569597244,
0.07538032531738281,
0.021295789629220963,
0.1592349112033844,
0.1095326617360115,
-0.04809204861521721,
-0.17283451557159424,
-0.04361211508512497,
-0.015768414363265038,
0.14105691015720367,
0.24003157019615173,
-0.09115307778120041,
-0.05364172160625458,
0.06516028940677643,
-0.026307007297873497,
-0.33778899908065796,
0.09444401413202286,
-0.040518708527088165,
0.0417332723736763,
-0.024000070989131927,
0.01607045717537403,
0.16054582595825195,
0.1710885763168335,
-0.03850649297237396,
0.03438972681760788,
-0.25395384430885315,
-0.13947173953056335,
0.1886788010597229,
0.1358276754617691,
0.10112963616847992,
-0.13437820971012115,
-0.04015953466296196,
-0.11519792675971985,
-0.04224567115306854,
0.05660839006304741,
-0.05753406137228012,
0.06904298812150955,
-0.04906739294528961,
0.00813088845461607,
0.054586444050073624,
-0.07660531997680664,
0.11400046944618225,
-0.05628545582294464,
0.12173322588205338,
-0.0880119577050209,
-0.06259182095527649,
0.01487935334444046,
-0.08201012015342712,
0.10715737193822861,
0.07073280960321426,
0.07496371120214462,
-0.09217428416013718,
-0.014662455767393112,
-0.013035467825829983,
0.0630238726735115,
-0.023831933736801147,
-0.07395540177822113,
-0.06603976339101791,
0.07036649435758591,
-0.06675544381141663,
-0.07719337940216064,
0.008724112063646317,
-0.02204241417348385,
0.07460319250822067,
0.12521852552890778,
0.06962226331233978,
-0.05808626115322113,
0.01030916441231966,
0.015683945268392563,
-0.06264462321996689,
0.09792666882276535,
-0.02710365690290928,
0.08149956166744232,
0.12253767997026443,
0.006053166463971138,
0.1369839608669281,
0.0798271968960762,
0.00781311932951212,
-0.01998644508421421,
0.07077857851982117,
-0.13691698014736176,
0.0006106014479883015,
-0.042733948677778244,
0.03600515425205231,
-0.015544325113296509,
-0.01297907903790474,
0.10007485002279282,
-0.04825618863105774,
0.009515841491520405,
-0.0077935680747032166,
0.015342751517891884,
0.0333944670855999,
0.2570798695087433,
0.00024592530098743737,
0.04238978773355484,
-0.1025625616312027,
0.13009513914585114,
0.065212182700634,
-0.14394447207450867,
-0.01497277058660984,
0.031694602221250534,
-0.0817105770111084,
-0.042033664882183075,
0.1099586933851242,
0.20278118550777435,
-0.15055814385414124,
-0.0439477376639843,
-0.07415371388196945,
-0.16662386059761047,
0.06212746724486351,
0.24267832934856415,
0.09262014180421829,
-0.005986451171338558,
0.015085744671523571,
-0.07590556889772415,
-0.13410316407680511,
0.12069808691740036,
0.07806459814310074,
0.07538505643606186,
-0.19812852144241333,
0.13342680037021637,
-0.049565259367227554,
0.015889044851064682,
-0.06880945712327957,
0.033521320670843124,
-0.16651464998722076,
-0.014035483822226524,
-0.05436775088310242,
0.06858203560113907,
-0.03009079024195671,
0.0013026687083765864,
-0.003216438228264451,
0.004282386973500252,
-0.041536811739206314,
0.013166925869882107,
-0.052697353065013885,
-0.024462049826979637,
0.029589328914880753,
0.05450547859072685,
-0.04979189857840538,
-0.07459741085767746,
0.02217162400484085,
-0.015654319897294044,
0.05012577772140503,
0.03034350275993347,
0.07531396299600601,
0.005260101053863764,
-0.05112839490175247,
-0.047610241919755936,
0.09071985632181168,
-0.030783139169216156,
0.05913633108139038,
-0.14573611319065094,
0.04122048616409302,
0.01912364549934864,
0.01926163025200367,
0.05146612599492073,
0.07887955754995346,
-0.11114183813333511,
-0.027357526123523712,
-0.09543777257204056,
-0.06899160146713257,
-0.10664694011211395,
0.031764037907123566,
0.16085456311702728,
-0.005329772364348173,
0.11814499646425247,
-0.12313282489776611,
-0.006504556629806757,
-0.16240835189819336,
0.015155292116105556,
-0.05111042782664299,
-0.11310192942619324,
-0.11988744884729385,
0.030638745054602623,
0.0721634030342102,
-0.03202756494283676,
0.07979658991098404,
0.04747549071907997,
0.02113688737154007,
0.061354849487543106,
0.10613387078046799,
0.001179485465399921,
0.0226309671998024,
0.2006167322397232,
0.07838001102209091,
-0.03234419971704483,
0.03161220997571945,
0.11436893045902252,
0.13853371143341064,
0.06533665955066681,
0.07086598128080368,
0.08670368045568466,
-0.09361964464187622,
0.1251394897699356,
0.03509578853845596,
-0.08145152032375336,
-0.05510054528713226,
0.08837341517210007,
-0.1615830510854721,
0.038643695414066315,
-0.04878886789083481,
0.007596911862492561,
0.1679161936044693,
-0.09441438317298889,
-0.00812421552836895,
-0.08273782581090927,
-0.06814104318618774,
-0.1350678950548172,
-0.11802389472723007,
-0.16371271014213562,
-0.05566299334168434,
-0.00362748047336936,
-0.09526649117469788,
0.0303870290517807,
0.16539351642131805,
0.04607786238193512,
-0.01706382818520069,
0.17481473088264465,
-0.22133482992649078,
0.0037041998002678156,
0.0487588569521904,
-0.00030745487310923636,
-0.037782277911901474,
-0.03795483335852623,
-0.04757894203066826,
0.028534162789583206,
0.010498235002160072,
0.02661527320742607,
-0.022472241893410683,
0.005850747227668762,
0.035408418625593185,
0.020746638998389244,
-0.09670387208461761,
-0.017958033829927444,
0.008932599797844887,
0.0281357541680336,
0.025773167610168457,
0.0009060437441803515,
0.04090587794780731,
-0.020469393581151962,
0.19870595633983612,
-0.10439813882112503,
-0.02377662993967533,
-0.10362731665372849,
0.21003250777721405,
-0.005637886933982372,
0.0940324142575264,
0.0009778417879715562,
-0.07613804191350937,
0.057070933282375336,
0.17911235988140106,
0.13086740672588348,
-0.042160019278526306,
-0.051234349608421326,
-0.02010643482208252,
-0.018405241891741753,
-0.07301869988441467,
0.09655433893203735,
0.0224158875644207,
0.03447995334863663,
-0.0629042461514473,
0.07129031419754028,
-0.02168520726263523,
-0.05962403118610382,
-0.01885230466723442,
0.05357099324464798,
0.0217133816331625,
0.01947047933936119,
-0.04971592500805855,
0.06871401518583298,
0.024164529517292976,
0.09538443386554718,
0.12934064865112305,
-0.10229118168354034,
-0.14083103835582733,
0.035983119159936905,
0.020256342366337776,
-0.06060590222477913,
0.06107281893491745,
-0.07883987575769424,
0.0343996100127697,
-0.06874579936265945,
-0.010265326127409935,
-0.15128110349178314,
-0.12311136722564697,
0.004142609424889088,
0.13196788728237152,
0.2778593897819519,
-0.0016358356224372983,
0.06289827823638916,
0.12589453160762787,
-0.04993937537074089,
-0.16468018293380737,
0.10472414642572403,
-0.023483935743570328,
-0.13088610768318176,
0.11089932918548584,
0.1576138734817505,
-0.020655903965234756,
0.16264724731445312,
0.017468297854065895,
-0.1858883798122406,
0.017755862325429916,
-0.07895581424236298,
-0.026308344677090645,
-0.06888404488563538,
0.050562579184770584,
-0.06550431996583939,
0.14337870478630066,
0.11417272686958313,
-0.02103496342897415,
0.006876251194626093,
-0.0629410669207573,
0.04808822274208069,
0.02974454127252102,
0.0595761314034462,
0.03290080651640892,
-0.1264454871416092,
0.06876151263713837,
-0.13826678693294525,
-0.021696461364626884,
-0.2916562855243683,
-0.05575575679540634,
-0.05678873136639595,
-0.06005055829882622,
-0.09664180129766464,
0.1040220782160759,
0.13460466265678406,
0.03689119964838028,
-0.04430272430181503,
-0.27879491448402405,
0.03561382740736008,
0.12294009327888489,
-0.07020079344511032,
-0.10500278323888779
] |
null | null | scvi-tools |
# Description
mmColon_single_cell_85K.mouse.h5ad
# Model properties
Many model properties are in the model tags. Some more are listed below.
**model_init_params**:
```json
{
"n_hidden": 128,
"n_latent": 10,
"n_layers": 1,
"dropout_rate": 0.1,
"dispersion": "gene",
"gene_likelihood": "nb",
"latent_distribution": "normal"
}
```
**model_setup_anndata_args**:
```json
{
"layer": null,
"batch_key": null,
"labels_key": null,
"size_factor_key": "total_counts",
"categorical_covariate_keys": null,
"continuous_covariate_keys": null
}
```
**Training curve**:
**Embedding plots**:
**model_summary_stats**:
|[1m [0m[1m Summary Stat Key [0m[1m [0m|[1m [0m[1mValue[0m[1m [0m|
|--------------------------|-------|
|[94m [0m[94m n_batch [0m[94m [0m|[35m [0m[35m 1 [0m[35m [0m|
|[94m [0m[94m n_cells [0m[94m [0m|[35m [0m[35m84612[0m[35m [0m|
|[94m [0m[94mn_extra_categorical_covs[0m[94m [0m|[35m [0m[35m 0 [0m[35m [0m|
|[94m [0m[94mn_extra_continuous_covs [0m[94m [0m|[35m [0m[35m 0 [0m[35m [0m|
|[94m [0m[94m n_labels [0m[94m [0m|[35m [0m[35m 1 [0m[35m [0m|
|[94m [0m[94m n_latent_qzm [0m[94m [0m|[35m [0m[35m 10 [0m[35m [0m|
|[94m [0m[94m n_latent_qzv [0m[94m [0m|[35m [0m[35m 10 [0m[35m [0m|
|[94m [0m[94m n_vars [0m[94m [0m|[35m [0m[35m18416[0m[35m [0m|
**model_data_registry**:
|[1m [0m[1m Registry Key [0m[1m [0m|[1m [0m[1m scvi-tools Location [0m[1m [0m|
|-------------------|--------------------------------------|
|[94m [0m[94m X [0m[94m [0m|[35m [0m[35m adata.X [0m[35m [0m|
|[94m [0m[94m batch [0m[94m [0m|[35m [0m[35m adata.obs['_scvi_batch'] [0m[35m [0m|
|[94m [0m[94m labels [0m[94m [0m|[35m [0m[35m adata.obs['_scvi_labels'] [0m[35m [0m|
|[94m [0m[94m latent_qzm [0m[94m [0m|[35m [0m[35m adata.obsm['_scvi_latent_qzm'] [0m[35m [0m|
|[94m [0m[94m latent_qzv [0m[94m [0m|[35m [0m[35m adata.obsm['_scvi_latent_qzv'] [0m[35m [0m|
|[94m [0m[94m minify_type [0m[94m [0m|[35m [0m[35madata.uns['_scvi_adata_minify_type'][0m[35m [0m|
|[94m [0m[94mobserved_lib_size[0m[94m [0m|[35m [0m[35madata.obs['_scvi_observed_lib_size'][0m[35m [0m|
|[94m [0m[94m size_factor [0m[94m [0m|[35m [0m[35m adata.obs['total_counts'] [0m[35m [0m|
**model_parent_module**: scvi.model
**data_is_minified**: True
# Training data
This is an optional link to where the training data is stored if it is too large
to host on the huggingface Model hub.
<!-- If your model is not uploaded with any data (e.g., minified data) on the Model Hub, then make
sure to provide this field if you want users to be able to access your training data. See the scvi-tools
documentation for details. -->
Training data url: N/A
# Training code
This is an optional link to the code used to train the model.
Training code url: N/A
# References
10.6084/m9.figshare.24670038.v1 | {"license": "cc-by-4.0", "library_name": "scvi-tools", "tags": ["biology", "genomics", "single-cell", "model_cls_name:SCVI", "scvi_version:1.0.4", "anndata_version:0.9.1", "modality:rna", "annotated:True"]} | null | valsv/mmColon_single_cell_85K.mouse.scvi.model | [
"scvi-tools",
"biology",
"genomics",
"single-cell",
"model_cls_name:SCVI",
"scvi_version:1.0.4",
"anndata_version:0.9.1",
"modality:rna",
"annotated:True",
"license:cc-by-4.0",
"region:us"
] | 2024-02-11T07:27:52+00:00 | [] | [] | TAGS
#scvi-tools #biology #genomics #single-cell #model_cls_name-SCVI #scvi_version-1.0.4 #anndata_version-0.9.1 #modality-rna #annotated-True #license-cc-by-4.0 #region-us
| Description
===========
mmColon\_single\_cell\_85K.mouse.h5ad
Model properties
================
Many model properties are in the model tags. Some more are listed below.
model\_init\_params:
model\_setup\_anndata\_args:
Training curve:
!image/png
Embedding plots:
!image/png
model\_summary\_stats:
model\_data\_registry:
model\_parent\_module: URL
data\_is\_minified: True
Training data
=============
This is an optional link to where the training data is stored if it is too large
to host on the huggingface Model hub.
Training data url: N/A
Training code
=============
This is an optional link to the code used to train the model.
Training code url: N/A
References
==========
10.6084/m9.figshare.24670038.v1
| [] | [
"TAGS\n#scvi-tools #biology #genomics #single-cell #model_cls_name-SCVI #scvi_version-1.0.4 #anndata_version-0.9.1 #modality-rna #annotated-True #license-cc-by-4.0 #region-us \n"
] | [
72
] | [
"passage: TAGS\n#scvi-tools #biology #genomics #single-cell #model_cls_name-SCVI #scvi_version-1.0.4 #anndata_version-0.9.1 #modality-rna #annotated-True #license-cc-by-4.0 #region-us \n"
] | [
-0.03717820346355438,
0.048367489129304886,
-0.0032548203598707914,
-0.10777990520000458,
0.09014134854078293,
0.048945169895887375,
0.1474742740392685,
0.12890633940696716,
0.1292525976896286,
0.10540828108787537,
0.16159898042678833,
0.06415301561355591,
0.04024170711636543,
0.025117384269833565,
-0.03480347618460655,
-0.039684802293777466,
0.06635556370019913,
-0.0015555188292637467,
-0.029105929657816887,
-0.00014467007713392377,
0.0731179490685463,
-0.031621500849723816,
0.1203550174832344,
-0.02538258023560047,
-0.09034018218517303,
-0.03772876784205437,
0.12438716739416122,
-0.00878115650266409,
0.12989777326583862,
-0.0016922723734751344,
0.026932748034596443,
0.11967597156763077,
0.0839378610253334,
-0.17554761469364166,
0.031912826001644135,
-0.06311935186386108,
0.007702632807195187,
0.10436256229877472,
0.02935227006673813,
0.0756908729672432,
0.07636093348264694,
0.04652821272611618,
-0.0606672465801239,
0.06653036177158356,
-0.07628536224365234,
-0.028608061373233795,
-0.03912549093365669,
0.01128661260008812,
-0.0386715792119503,
-0.027399301528930664,
0.027332976460456848,
0.044555727392435074,
0.04115305840969086,
-0.012804550118744373,
0.1346425861120224,
-0.22690489888191223,
0.04681319743394852,
0.29405155777931213,
0.08567965030670166,
0.09296362102031708,
0.08328573405742645,
0.16073428094387054,
0.06512953341007233,
-0.08642444759607315,
0.00426439568400383,
-0.11524836719036102,
-0.09437102824449539,
0.04793244227766991,
-0.046726617962121964,
-0.059490568935871124,
0.30403250455856323,
-0.0832914337515831,
0.030002539977431297,
0.043592166155576706,
-0.027846312150359154,
-0.008079089224338531,
-0.00254014297388494,
-0.07135909795761108,
0.025672152638435364,
0.014044234529137611,
0.12196803092956543,
-0.11875585466623306,
-0.06194375082850456,
-0.12587575614452362,
-0.050259947776794434,
0.057662732899188995,
-0.026905275881290436,
0.0459870770573616,
-0.08967335522174835,
-0.000956283591222018,
-0.18391531705856323,
-0.06826692074537277,
-0.027391597628593445,
0.004407411441206932,
-0.015970176085829735,
-0.045902978628873825,
-0.0064391824416816235,
-0.03575792908668518,
0.21800744533538818,
0.008271507918834686,
0.022347815334796906,
-0.022581279277801514,
-0.08763813227415085,
0.10452587157487869,
0.021662253886461258,
-0.11920307576656342,
-0.04757244884967804,
0.2203933298587799,
0.06441284716129303,
-0.008708218112587929,
-0.002009013667702675,
-0.025728020817041397,
-0.1252494603395462,
-0.01644330658018589,
-0.12172677367925644,
0.1261504888534546,
-0.020792098715901375,
-0.062460873275995255,
-0.005266936961561441,
0.0018670425051823258,
0.0893847718834877,
-0.011441481299698353,
-0.06297613680362701,
0.10168081521987915,
0.11166314035654068,
-0.005777057260274887,
-0.10534680634737015,
-0.047964345663785934,
-0.019100889563560486,
-0.12045231461524963,
-0.15749967098236084,
-0.0218613613396883,
-0.02641431614756584,
-0.000584747176617384,
0.024068456143140793,
-0.05122191831469536,
0.01919291913509369,
-0.1062609925866127,
-0.030113665387034416,
-0.04740949347615242,
-0.12041877210140228,
-0.077341228723526,
-0.018133725970983505,
0.07515467703342438,
-0.00459774024784565,
0.023317495360970497,
-0.0839773640036583,
-0.042113807052373886,
-0.04992055892944336,
0.00972006842494011,
-0.021907009184360504,
0.01617124117910862,
-0.13072113692760468,
0.01700066775083542,
-0.11747902631759644,
0.0875212624669075,
0.039640940725803375,
-0.10818023234605789,
-0.1585683375597,
0.00009174390288535506,
-0.07297811657190323,
-0.040381621569395065,
-0.023473069071769714,
-0.034167978912591934,
0.05332673341035843,
0.09790635108947754,
-0.06725595891475677,
-0.0157252699136734,
0.15843188762664795,
-0.10504855960607529,
-0.14529336988925934,
0.017161129042506218,
0.04917292669415474,
-0.021067997440695763,
-0.009014097042381763,
0.2647988796234131,
0.02416137419641018,
0.021951541304588318,
-0.0005442656693048775,
0.05641485005617142,
0.09890958666801453,
-0.08811930567026138,
0.19687801599502563,
-0.10441891849040985,
-0.15286575257778168,
0.06724748760461807,
-0.21748344600200653,
-0.04397999495267868,
-0.07218555361032486,
-0.047192882746458054,
-0.06749721616506577,
-0.03511841222643852,
-0.0971648097038269,
-0.026588086038827896,
0.03174930438399315,
-0.01939062401652336,
0.15882079303264618,
-0.039113786071538925,
0.149544358253479,
-0.056921832263469696,
-0.003669395577162504,
-0.030740296468138695,
0.18925955891609192,
-0.059895727783441544,
0.0018948334036394954,
-0.12699954211711884,
-0.08683470636606216,
0.083787702023983,
-0.06960637867450714,
0.08075898885726929,
0.04763676971197128,
-0.04592600092291832,
0.002839133143424988,
0.0325237438082695,
0.08376218378543854,
-0.01428158301860094,
0.04075458273291588,
0.016657261177897453,
-0.15620216727256775,
-0.02126632258296013,
-0.05072632431983948,
0.03311500698328018,
-0.20755620300769806,
-0.003594708628952503,
0.08471856266260147,
0.060271766036748886,
-0.03588252142071724,
-0.02513483352959156,
0.05370389297604561,
0.026183659210801125,
-0.13050739467144012,
0.01568653993308544,
0.06466148048639297,
-0.06441722065210342,
-0.08907473832368851,
0.11472354084253311,
-0.0059733521193265915,
0.09713693708181381,
0.02804221585392952,
-0.092342808842659,
0.06706755608320236,
-0.03396868333220482,
0.03597206994891167,
0.0728815570473671,
-0.11260149627923965,
-0.0354185476899147,
-0.03623519092798233,
-0.04485974833369255,
0.07997027039527893,
-0.08015631139278412,
0.10239910334348679,
0.021358277648687363,
-0.025095731019973755,
-0.011053838767111301,
0.11660239845514297,
0.32306957244873047,
-0.24074304103851318,
0.11021384596824646,
0.16222138702869415,
0.09528506547212601,
0.06948166340589523,
-0.010217352770268917,
-0.08750873059034348,
-0.05275897681713104,
-0.006292928941547871,
0.009707972407341003,
0.13843034207820892,
-0.04040634259581566,
-0.060018107295036316,
0.08613472431898117,
0.0002351317962165922,
-0.04383070394396782,
-0.10122619569301605,
-0.04804942011833191,
-0.014697783626616001,
-0.10090576857328415,
-0.07944594323635101,
0.019610658288002014,
-0.05062748119235039,
0.17609751224517822,
-0.07431954145431519,
-0.051910191774368286,
-0.004467283375561237,
-0.015354307368397713,
-0.13080410659313202,
0.21682776510715485,
-0.08042555302381516,
-0.09872780740261078,
-0.17434807121753693,
0.08910436183214188,
-0.08823706209659576,
0.10021565854549408,
0.004507980775088072,
0.0020514067728072405,
-0.0521513931453228,
0.0009852590737864375,
-0.022006819024682045,
-0.06706943362951279,
-0.03180180862545967,
-0.05696187540888786,
0.06879191845655441,
0.010616804473102093,
-0.05100548639893532,
-0.009948065504431725,
-0.0012389280600473285,
-0.019396796822547913,
0.03425944969058037,
-0.0018252512672916055,
0.13859781622886658,
0.10608531534671783,
0.015613081865012646,
-0.07823539525270462,
-0.036076515913009644,
0.059655409306287766,
0.023660903796553612,
-0.0982181653380394,
0.26123321056365967,
0.015748534351587296,
-0.01738271303474903,
0.08453629165887833,
0.08280952274799347,
-0.03849698230624199,
-0.04166426882147789,
-0.11548929661512375,
-0.12874552607536316,
-0.26915743947029114,
-0.08317379653453827,
-0.00827858503907919,
0.07198391109704971,
-0.0007609987515024841,
0.06307617574930191,
0.12236197292804718,
0.12410054355859756,
0.02654188498854637,
-0.06959495693445206,
-0.07943123579025269,
0.04281270131468773,
0.23069466650485992,
-0.03979496657848358,
0.054227352142333984,
-0.014609359204769135,
0.07662516087293625,
0.12442352622747421,
0.12181795388460159,
0.1293344646692276,
0.16304059326648712,
0.2735593616962433,
0.019986165687441826,
0.06738303601741791,
0.0956047996878624,
0.026703592389822006,
0.0724925622344017,
-0.017491627484560013,
-0.01039622351527214,
-0.04170367121696472,
-0.04127347841858864,
0.039610300213098526,
-0.04464314132928848,
-0.0837966650724411,
0.0014979494735598564,
0.04376537725329399,
0.04747679457068443,
-0.03167087584733963,
0.1372731626033783,
-0.11555183678865433,
0.0315779373049736,
0.07500595599412918,
0.08933857828378677,
-0.10706956684589386,
0.09593776613473892,
0.1571439802646637,
-0.0399504229426384,
-0.02381528727710247,
0.032891351729631424,
0.09200217574834824,
0.002593262353911996,
0.06922466307878494,
-0.0049570221453905106,
-0.09355366230010986,
0.0064314245246350765,
0.15008467435836792,
-0.200627401471138,
0.22828862071037292,
0.004068987909704447,
-0.1529998481273651,
-0.02477174624800682,
-0.04318045452237129,
-0.027306681498885155,
0.27688637375831604,
0.18600614368915558,
0.04130462557077408,
-0.38074013590812683,
-0.0714571475982666,
-0.10904175043106079,
-0.04820723831653595,
0.07119084894657135,
-0.11271874606609344,
0.03599924221634865,
-0.02996183931827545,
0.04843791574239731,
-0.08614926040172577,
-0.034979481250047684,
-0.03219589591026306,
0.014210822060704231,
0.14127814769744873,
0.041119106113910675,
0.029994625598192215,
-0.014556348323822021,
0.05287596955895424,
-0.045941852033138275,
0.1379767805337906,
-0.16754460334777832,
-0.0388944111764431,
-0.13743968307971954,
0.031225785613059998,
0.08968938142061234,
-0.06832370162010193,
-0.04928645119071007,
0.008567335084080696,
0.030962062999606133,
0.03769909590482712,
-0.2192801982164383,
0.05366692319512367,
-0.08335870504379272,
-0.16864652931690216,
-0.058255113661289215,
0.1548537164926529,
-0.17878401279449463,
0.11050213128328323,
0.08200986683368683,
0.05330803617835045,
-0.006003227550536394,
-0.11548478901386261,
0.15354758501052856,
-0.03181404247879982,
-0.03018527664244175,
0.10147137939929962,
-0.18691840767860413,
-0.03918888419866562,
0.0139359375461936,
-0.09765845537185669,
0.15081746876239777,
0.3267248868942261,
-0.029759306460618973,
0.08538348227739334,
0.1630551815032959,
-0.19762994349002838,
-0.23883292078971863,
-0.0327017568051815,
-0.12281539291143417,
0.04593982920050621,
0.14723575115203857,
-0.28836727142333984,
0.14083744585514069,
0.19646620750427246,
-0.04141027107834816,
0.11526559293270111,
-0.20681391656398773,
-0.12443342059850693,
0.046661127358675,
0.006613034289330244,
0.17453281581401825,
-0.19038067758083344,
-0.13045434653759003,
-0.0458894744515419,
-0.11372417211532593,
0.08194590359926224,
-0.06016422435641289,
-0.002671763300895691,
-0.021879728883504868,
0.005535283591598272,
0.027319086715579033,
-0.0031778959091752768,
0.2335970252752304,
0.028217943385243416,
0.02461167611181736,
0.0038701381999999285,
-0.051140423864126205,
0.2112741470336914,
0.0886678621172905,
0.029433488845825195,
0.025447005406022072,
0.0650361105799675,
-0.1802893877029419,
0.03428630530834198,
-0.009498325176537037,
0.02673490345478058,
-0.012356502003967762,
-0.027953853830695152,
-0.15459023416042328,
-0.06619004905223846,
-0.003947248216718435,
-0.029765263199806213,
0.27879929542541504,
-0.10572853684425354,
0.08351068198680878,
0.09962563961744308,
0.1055765375494957,
0.042684245854616165,
0.02471204102039337,
-0.01419724803417921,
-0.08156869560480118,
0.02922292985022068,
-0.04182646423578262,
0.028045877814292908,
0.0949549451470375,
0.030104145407676697,
0.004702763631939888,
0.04774218052625656,
0.03401534631848335,
0.052161142230033875,
0.0519694983959198,
-0.18528525531291962,
-0.053067032247781754,
-0.0280283372849226,
0.12332180887460709,
0.008278768509626389,
0.05966613069176674,
0.14264705777168274,
0.02325918711721897,
-0.05926842987537384,
-0.03628210723400116,
0.07103922963142395,
-0.010665896348655224,
0.12880834937095642,
0.017928192391991615,
0.056107815355062485,
-0.1165582537651062,
0.009026125073432922,
0.06481998413801193,
-0.009429745376110077,
-0.01608964055776596,
-0.019235704094171524,
-0.13531111180782318,
-0.08379606902599335,
-0.09018934518098831,
-0.010355999693274498,
-0.23301219940185547,
-0.06338763236999512,
-0.10648368299007416,
-0.17541223764419556,
-0.024260401725769043,
0.1599208414554596,
0.07278668135404587,
0.0076120528392493725,
0.043314605951309204,
-0.12089822441339493,
-0.022822018712759018,
0.03853505477309227,
-0.24618224799633026,
0.11312207579612732,
-0.09022030979394913,
0.03273885324597359,
-0.12332221120595932,
0.07923241704702377,
-0.08252228051424026,
0.06874272972345352,
-0.13815750181674957,
-0.008386916480958462,
-0.03435564786195755,
0.011666211299598217,
-0.08734884858131409,
-0.11028938740491867,
0.1172744631767273,
-0.041776929050683975,
-0.029348423704504967,
0.015955382958054543,
-0.06443258374929428,
-0.005769329611212015,
-0.04594815894961357,
0.12498030811548233,
-0.06555821001529694,
0.03555331379175186,
0.03510585054755211,
-0.001855496084317565,
0.0737607404589653,
0.0568833090364933,
0.017651066184043884,
0.07572189718484879,
-0.04365013912320137,
0.006157220806926489,
0.05260105058550835,
0.10641789436340332,
-0.07758092880249023,
-0.1475268006324768,
-0.017598912119865417,
0.0909482017159462,
-0.09529438614845276,
0.024896347895264626,
-0.05464421957731247,
-0.0009070466039702296,
-0.1519305557012558,
-0.07952330261468887,
-0.02260151319205761,
0.05253719910979271,
-0.007167467847466469,
0.1100599393248558,
0.03046027012169361,
0.018820608034729958,
0.004965678323060274,
-0.01892794482409954,
-0.0662902370095253,
0.0581316314637661,
-0.03678898140788078,
-0.15291018784046173,
-0.20982222259044647,
-0.08113597333431244,
0.03386407345533371,
-0.008378036320209503,
0.2368892878293991,
-0.010027339681982994,
-0.018208393827080727,
0.03365739807486534,
0.11312297731637955,
0.15774253010749817,
0.08194543421268463,
0.2939380705356598,
0.11732257157564163,
-0.025059586390852928,
-0.05238393694162369,
0.0049947090446949005,
-0.02544749714434147,
0.051439374685287476,
0.13195431232452393,
0.0740174651145935,
0.007329396437853575,
0.004357407335191965,
0.06321261078119278,
-0.12639398872852325,
-0.015120002441108227,
-0.0436699315905571,
0.0233237836509943,
0.02389347553253174,
0.019206756725907326,
0.12153289467096329,
0.11780289560556412,
-0.09808407723903656,
0.04234294593334198,
-0.09404442459344864,
-0.029809383675456047,
-0.17850926518440247,
-0.17069119215011597,
-0.1208350881934166,
-0.13896842300891876,
-0.04439670965075493,
-0.18143042922019958,
0.02707391045987606,
0.20023447275161743,
0.010167740285396576,
-0.0008054273785091937,
-0.0028651466127485037,
-0.09843752533197403,
-0.0010893107391893864,
-0.0022338542621582747,
0.0017463965341448784,
0.05246821418404579,
-0.13043852150440216,
-0.07848507165908813,
0.10642892122268677,
-0.09186719357967377,
0.014221273362636566,
-0.05469244346022606,
0.10601157695055008,
-0.0367436483502388,
-0.12983320653438568,
-0.024454785510897636,
-0.0414891354739666,
-0.06742563098669052,
-0.10038407146930695,
0.06957617402076721,
0.026074634864926338,
-0.04409366473555565,
0.012741985730826855,
0.11622318625450134,
0.011671068146824837,
0.1302783042192459,
-0.05970963090658188,
0.0969904437661171,
0.02183559164404869,
0.08167793601751328,
0.012950178235769272,
0.021151458844542503,
0.057138342410326004,
0.14685319364070892,
0.11696892976760864,
-0.07861218601465225,
-0.05770283564925194,
-0.010135600343346596,
-0.0012901138979941607,
0.046617716550827026,
0.06346622109413147,
-0.04060547426342964,
0.029730036854743958,
-0.012622074224054813,
-0.0868799090385437,
-0.005829666741192341,
0.029614480212330818,
-0.1880515217781067,
-0.07298482954502106,
0.03641470521688461,
-0.06637785583734512,
-0.06529072672128677,
0.0011678104056045413,
-0.03826340287923813,
0.07440432161092758,
0.07862153649330139,
-0.03304743021726608,
-0.006185423582792282,
-0.04817850887775421,
-0.054100945591926575,
0.014113920740783215,
-0.044699471443891525,
-0.10930801928043365,
0.0194650087505579,
0.04788127541542053,
0.03432142734527588,
-0.11262739449739456,
-0.07463284581899643,
0.09946542233228683,
-0.04500053822994232,
0.13740096986293793,
-0.02672678232192993,
0.10608610510826111,
0.021301619708538055,
-0.10164166986942291,
-0.15035681426525116,
0.035032968968153,
0.06380641460418701,
-0.038127366453409195,
0.06314121186733246,
0.06693177670240402,
0.01958433911204338,
0.117020383477211,
0.042869698256254196,
-0.027399564161896706,
-0.04077436029911041,
0.07418772578239441,
-0.02259649708867073,
0.049790333956480026,
0.011974900960922241,
-0.10184499621391296,
0.10153784602880478,
0.05826124548912048,
-0.031052350997924805,
-0.06343922019004822,
-0.05387332662940025,
0.07347976416349411,
-0.01306233648210764,
0.07112031430006027,
0.008790952153503895,
-0.06363250315189362,
-0.03545299172401428,
-0.047240979969501495,
0.007022805046290159,
-0.12925861775875092,
-0.057397495955228806,
-0.00869471300393343,
0.07154231518507004,
-0.08818438649177551,
0.035050131380558014,
0.20222949981689453,
-0.04865468293428421,
-0.054842520505189896,
-0.11291328072547913,
0.063493512570858,
0.057819172739982605,
-0.030449792742729187,
-0.1038956418633461
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# random25eof_find_passage_train1000_eval1000_rare_gpt2_1e-4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the tyzhu/random25eof_find_passage_train1000_eval1000_rare dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1972
- Accuracy: 0.8639
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.5646 | 1.0 | 24 | 3.2606 | 0.2888 |
| 3.552 | 2.0 | 48 | 3.1522 | 0.2871 |
| 3.445 | 3.0 | 72 | 3.1167 | 0.2958 |
| 3.3948 | 4.0 | 96 | 3.0464 | 0.2922 |
| 3.3547 | 5.0 | 120 | 3.0126 | 0.3030 |
| 3.3224 | 6.0 | 144 | 2.9746 | 0.3110 |
| 3.2849 | 7.0 | 168 | 2.9594 | 0.3141 |
| 3.2723 | 8.0 | 192 | 2.9486 | 0.3137 |
| 3.256 | 9.0 | 216 | 2.9403 | 0.3139 |
| 3.2393 | 10.0 | 240 | 2.9232 | 0.3153 |
| 3.2252 | 11.0 | 264 | 2.9119 | 0.3163 |
| 3.2046 | 12.0 | 288 | 2.9008 | 0.3159 |
| 3.1802 | 13.0 | 312 | 2.8827 | 0.3176 |
| 3.1496 | 14.0 | 336 | 2.8624 | 0.3187 |
| 3.111 | 15.0 | 360 | 2.8387 | 0.3204 |
| 3.0708 | 16.0 | 384 | 2.8089 | 0.3229 |
| 3.0226 | 17.0 | 408 | 2.7664 | 0.3276 |
| 2.9838 | 18.0 | 432 | 2.7339 | 0.3336 |
| 2.948 | 19.0 | 456 | 2.6899 | 0.3397 |
| 2.918 | 20.0 | 480 | 2.6595 | 0.3434 |
| 2.8864 | 21.0 | 504 | 2.6326 | 0.3487 |
| 2.8551 | 22.0 | 528 | 2.6110 | 0.3526 |
| 2.8232 | 23.0 | 552 | 2.5833 | 0.3561 |
| 2.7845 | 24.0 | 576 | 2.5721 | 0.3592 |
| 2.7379 | 25.0 | 600 | 2.5352 | 0.3656 |
| 2.6811 | 26.0 | 624 | 2.4909 | 0.371 |
| 2.6209 | 27.0 | 648 | 2.4621 | 0.376 |
| 2.5492 | 28.0 | 672 | 2.3919 | 0.3845 |
| 2.4682 | 29.0 | 696 | 2.3452 | 0.3940 |
| 2.3825 | 30.0 | 720 | 2.2898 | 0.4027 |
| 2.2957 | 31.0 | 744 | 2.2151 | 0.4132 |
| 2.1944 | 32.0 | 768 | 2.1349 | 0.4266 |
| 2.1023 | 33.0 | 792 | 2.0710 | 0.4398 |
| 2.0019 | 34.0 | 816 | 1.9923 | 0.4533 |
| 1.9029 | 35.0 | 840 | 1.9018 | 0.4683 |
| 1.8028 | 36.0 | 864 | 1.7989 | 0.4870 |
| 1.7173 | 37.0 | 888 | 1.7220 | 0.5030 |
| 1.6271 | 38.0 | 912 | 1.6370 | 0.5199 |
| 1.539 | 39.0 | 936 | 1.5533 | 0.5377 |
| 1.4512 | 40.0 | 960 | 1.4590 | 0.5561 |
| 1.3791 | 41.0 | 984 | 1.3630 | 0.5799 |
| 1.3 | 42.0 | 1008 | 1.2793 | 0.5974 |
| 1.2317 | 43.0 | 1032 | 1.1758 | 0.6231 |
| 1.1678 | 44.0 | 1056 | 1.0967 | 0.6428 |
| 1.0959 | 45.0 | 1080 | 1.0061 | 0.6644 |
| 1.0454 | 46.0 | 1104 | 0.9222 | 0.6871 |
| 0.9887 | 47.0 | 1128 | 0.8718 | 0.7039 |
| 0.943 | 48.0 | 1152 | 0.7828 | 0.7246 |
| 0.8835 | 49.0 | 1176 | 0.7087 | 0.7436 |
| 0.843 | 50.0 | 1200 | 0.6448 | 0.7588 |
| 0.8008 | 51.0 | 1224 | 0.5864 | 0.7747 |
| 0.7583 | 52.0 | 1248 | 0.5219 | 0.7918 |
| 0.7233 | 53.0 | 1272 | 0.4775 | 0.8036 |
| 0.6883 | 54.0 | 1296 | 0.4376 | 0.8145 |
| 0.6553 | 55.0 | 1320 | 0.3992 | 0.8218 |
| 0.6297 | 56.0 | 1344 | 0.3716 | 0.8312 |
| 0.6019 | 57.0 | 1368 | 0.3455 | 0.8362 |
| 0.5669 | 58.0 | 1392 | 0.3179 | 0.8417 |
| 0.5487 | 59.0 | 1416 | 0.2978 | 0.8459 |
| 0.5235 | 60.0 | 1440 | 0.2741 | 0.8508 |
| 0.5029 | 61.0 | 1464 | 0.2668 | 0.8531 |
| 0.4811 | 62.0 | 1488 | 0.2545 | 0.8546 |
| 0.4593 | 63.0 | 1512 | 0.2449 | 0.8554 |
| 0.4465 | 64.0 | 1536 | 0.2386 | 0.857 |
| 0.4329 | 65.0 | 1560 | 0.2346 | 0.8571 |
| 0.4167 | 66.0 | 1584 | 0.2307 | 0.8580 |
| 0.4031 | 67.0 | 1608 | 0.2281 | 0.8583 |
| 0.389 | 68.0 | 1632 | 0.2275 | 0.8585 |
| 0.3802 | 69.0 | 1656 | 0.2204 | 0.8593 |
| 0.3678 | 70.0 | 1680 | 0.2157 | 0.8595 |
| 0.3568 | 71.0 | 1704 | 0.2131 | 0.8604 |
| 0.3487 | 72.0 | 1728 | 0.2164 | 0.8601 |
| 0.3411 | 73.0 | 1752 | 0.2103 | 0.8612 |
| 0.3322 | 74.0 | 1776 | 0.2116 | 0.8603 |
| 0.3257 | 75.0 | 1800 | 0.2061 | 0.8619 |
| 0.3184 | 76.0 | 1824 | 0.2064 | 0.8615 |
| 0.3157 | 77.0 | 1848 | 0.2077 | 0.8608 |
| 0.3071 | 78.0 | 1872 | 0.2077 | 0.8609 |
| 0.3026 | 79.0 | 1896 | 0.2027 | 0.8621 |
| 0.297 | 80.0 | 1920 | 0.2029 | 0.8621 |
| 0.2914 | 81.0 | 1944 | 0.2067 | 0.8610 |
| 0.2902 | 82.0 | 1968 | 0.2039 | 0.8619 |
| 0.2847 | 83.0 | 1992 | 0.2033 | 0.8620 |
| 0.2805 | 84.0 | 2016 | 0.2024 | 0.8619 |
| 0.2775 | 85.0 | 2040 | 0.2009 | 0.8625 |
| 0.2753 | 86.0 | 2064 | 0.2024 | 0.8621 |
| 0.2692 | 87.0 | 2088 | 0.2009 | 0.8624 |
| 0.2702 | 88.0 | 2112 | 0.2012 | 0.8626 |
| 0.2671 | 89.0 | 2136 | 0.1979 | 0.8636 |
| 0.266 | 90.0 | 2160 | 0.1990 | 0.8628 |
| 0.2629 | 91.0 | 2184 | 0.2023 | 0.8626 |
| 0.2612 | 92.0 | 2208 | 0.2011 | 0.8623 |
| 0.2585 | 93.0 | 2232 | 0.1988 | 0.8631 |
| 0.2554 | 94.0 | 2256 | 0.2008 | 0.8628 |
| 0.2538 | 95.0 | 2280 | 0.1994 | 0.8629 |
| 0.2525 | 96.0 | 2304 | 0.1983 | 0.8634 |
| 0.2497 | 97.0 | 2328 | 0.1969 | 0.8635 |
| 0.2479 | 98.0 | 2352 | 0.1968 | 0.864 |
| 0.2469 | 99.0 | 2376 | 0.1986 | 0.8633 |
| 0.2454 | 100.0 | 2400 | 0.1972 | 0.8639 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/random25eof_find_passage_train1000_eval1000_rare"], "metrics": ["accuracy"], "base_model": "gpt2", "model-index": [{"name": "random25eof_find_passage_train1000_eval1000_rare_gpt2_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/random25eof_find_passage_train1000_eval1000_rare", "type": "tyzhu/random25eof_find_passage_train1000_eval1000_rare"}, "metrics": [{"type": "accuracy", "value": 0.8639148936170212, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/random25eof_find_passage_train1000_eval1000_rare_gpt2_1e-4 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/random25eof_find_passage_train1000_eval1000_rare",
"base_model:gpt2",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:31:57+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train1000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| random25eof\_find\_passage\_train1000\_eval1000\_rare\_gpt2\_1e-4
=================================================================
This model is a fine-tuned version of gpt2 on the tyzhu/random25eof\_find\_passage\_train1000\_eval1000\_rare dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1972
* Accuracy: 0.8639
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 100.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train1000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
99,
98,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train1000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.132711261510849,
0.18299701809883118,
-0.0027603881899267435,
0.13038545846939087,
0.11882490664720535,
0.03712734207510948,
0.12150157243013382,
0.16003379225730896,
-0.10562140494585037,
0.08971128612756729,
0.1567237228155136,
0.09295488148927689,
0.05250368267297745,
0.18003401160240173,
-0.038157641887664795,
-0.22404807806015015,
0.016124190762639046,
0.02820366434752941,
-0.016270698979496956,
0.13902610540390015,
0.07687424123287201,
-0.11654624342918396,
0.09155091643333435,
0.00594562292098999,
-0.1920783966779709,
-0.019083378836512566,
-0.009473959915339947,
-0.05431479215621948,
0.11672753840684891,
0.018710914999246597,
0.0801234096288681,
0.024493565782904625,
0.07571408897638321,
-0.1372804492712021,
0.0004121552046854049,
0.05280454829335213,
0.0020118679385632277,
0.10528799146413803,
0.06370899081230164,
-0.027607904747128487,
0.08935105800628662,
-0.042614106088876724,
0.0294436514377594,
0.01653568632900715,
-0.13809770345687866,
-0.18020741641521454,
-0.09534330666065216,
0.08180372416973114,
0.021989187225699425,
0.08354531973600388,
-0.016757957637310028,
0.12840025126934052,
-0.04765991494059563,
0.07412426173686981,
0.27557986974716187,
-0.2901821434497833,
-0.06125552952289581,
0.041700467467308044,
0.015937067568302155,
0.05760302394628525,
-0.0928913950920105,
-0.04450232535600662,
0.05879415199160576,
0.031682755798101425,
0.12021605670452118,
0.0008540543494746089,
-0.03194393962621689,
0.014937839470803738,
-0.13908754289150238,
-0.06224185973405838,
0.14587010443210602,
0.030575869604945183,
-0.039326075464487076,
-0.05356897786259651,
-0.07627693563699722,
-0.20219838619232178,
-0.014547598548233509,
0.024340588599443436,
0.021653667092323303,
-0.030691375955939293,
-0.08726179599761963,
0.018363073468208313,
-0.05784665048122406,
-0.06987342238426208,
-0.013841954991221428,
0.06984931230545044,
0.05010317265987396,
0.020021537318825722,
-0.00403955765068531,
0.12722700834274292,
-0.04254559427499771,
-0.15368050336837769,
-0.0008776903850957751,
-0.0002911449992097914,
-0.0009095714194700122,
-0.028809618204832077,
-0.03849227726459503,
-0.0010474983137100935,
0.02500869333744049,
0.16490522027015686,
-0.05456749349832535,
0.048132579773664474,
0.008092583157122135,
0.026945706456899643,
-0.06477590650320053,
0.11982803046703339,
-0.08987072855234146,
-0.03466351330280304,
0.021278705447912216,
0.09875418245792389,
0.029715148732066154,
-0.011572481133043766,
-0.09160652756690979,
-0.012372407130897045,
0.12524010241031647,
0.025699196383357048,
-0.027524827048182487,
0.058977339416742325,
-0.04658474028110504,
-0.03198143094778061,
0.049696072936058044,
-0.0947158932685852,
0.014399086125195026,
0.020376475527882576,
-0.10992302000522614,
-0.06270001828670502,
-0.023751741275191307,
-0.013680427335202694,
-0.042822688817977905,
0.07627519220113754,
-0.11756051331758499,
0.002528778975829482,
-0.07274240255355835,
-0.11422980576753616,
0.0007905520615167916,
-0.10626248270273209,
-0.011848940514028072,
-0.06957827508449554,
-0.22345727682113647,
-0.03215015307068825,
0.02155185490846634,
-0.06984437257051468,
-0.08357220888137817,
-0.07840891182422638,
-0.10100682824850082,
0.03450874984264374,
-0.019159875810146332,
0.07835724204778671,
-0.06782799959182739,
0.10242832452058792,
0.034331753849983215,
0.056036923080682755,
0.013113911263644695,
0.0408535860478878,
-0.09085077047348022,
0.04624553024768829,
-0.15406927466392517,
0.08134996145963669,
-0.05055386200547218,
0.03304454684257507,
-0.09353607147932053,
-0.11522261798381805,
0.04272479936480522,
-0.03536207973957062,
0.10306701809167862,
0.139328733086586,
-0.15432193875312805,
-0.06505785882472992,
0.19293460249900818,
-0.06437288969755173,
-0.10757865011692047,
0.12132056057453156,
-0.06265375018119812,
-0.021213769912719727,
0.05514952912926674,
0.1810745745897293,
0.06401357799768448,
-0.041182439774274826,
-0.04249195381999016,
-0.03896622359752655,
0.054471928626298904,
-0.04187594726681709,
0.08481918275356293,
0.011261232197284698,
0.016207346692681313,
0.016507305204868317,
-0.028533749282360077,
0.045149002224206924,
-0.10984403640031815,
-0.08677461743354797,
-0.03793629631400108,
-0.09960542619228363,
0.06319648772478104,
0.04517175257205963,
0.07376594841480255,
-0.10239794105291367,
-0.09347019344568253,
0.016517164185643196,
0.10633660852909088,
-0.08239413797855377,
0.0027986380737274885,
-0.07036267966032028,
0.14818327128887177,
-0.07172621041536331,
-0.018429866060614586,
-0.16277790069580078,
-0.016185620799660683,
0.04608234390616417,
0.02543775364756584,
-0.010584909468889236,
-0.02592361532151699,
0.06939388811588287,
0.08859771490097046,
-0.05631929636001587,
-0.05884096026420593,
-0.032857246696949005,
-0.026393648236989975,
-0.11063861846923828,
-0.19194148480892181,
-0.05162109062075615,
-0.004537258762866259,
0.13096533715724945,
-0.20536749064922333,
0.03587831184267998,
0.004210035782307386,
0.11687809228897095,
0.004483212251216173,
-0.05426797270774841,
-0.00735946511849761,
0.051545821130275726,
-0.061658747494220734,
-0.08506011962890625,
0.05566447228193283,
0.018238766118884087,
-0.06589715927839279,
-0.014901299960911274,
-0.11827543377876282,
0.12098294496536255,
0.11443266272544861,
-0.004549853503704071,
-0.10977965593338013,
0.010596038773655891,
-0.073625847697258,
-0.024712607264518738,
-0.04468058794736862,
-0.0005043706041760743,
0.1404876410961151,
-0.0035692518576979637,
0.15103495121002197,
-0.09832940995693207,
-0.05540589615702629,
0.04010006785392761,
0.011112643405795097,
0.023088350892066956,
0.1370357722043991,
0.05597373843193054,
-0.053885024040937424,
0.15728074312210083,
0.03348207101225853,
-0.05562267452478409,
0.11130562424659729,
-0.05267291143536568,
-0.08089765906333923,
-0.039459437131881714,
0.016778163611888885,
0.022139092907309532,
0.1059436947107315,
-0.08760193735361099,
-0.01655871607363224,
0.03208073973655701,
0.021294955164194107,
0.013015280477702618,
-0.18026158213615417,
-0.031500671058893204,
0.02407144010066986,
-0.062249839305877686,
-0.02039874531328678,
-0.021454202011227608,
0.004351709503680468,
0.11440401524305344,
0.0027564920019358397,
-0.07711450010538101,
0.030990777537226677,
0.010045437142252922,
-0.07775638997554779,
0.20230916142463684,
-0.07953201234340668,
-0.12259382754564285,
-0.11472225934267044,
-0.030563196167349815,
-0.06370188295841217,
0.017340583726763725,
0.0440373457968235,
-0.06531322002410889,
-0.011999242007732391,
-0.0996541827917099,
-0.0008991195354610682,
-0.03391337767243385,
0.02796686626970768,
0.025523189455270767,
-0.02869688719511032,
0.06346610188484192,
-0.10963838547468185,
0.0011954020010307431,
-0.023142274469137192,
-0.03707197308540344,
0.06012417748570442,
0.016123153269290924,
0.08949925005435944,
0.1230572909116745,
-0.016234273090958595,
0.030968084931373596,
-0.030019689351320267,
0.2660991847515106,
-0.038116857409477234,
-0.026594500988721848,
0.09919856488704681,
0.025950979441404343,
0.07585924118757248,
0.1189211830496788,
0.04394151270389557,
-0.08246786892414093,
-0.002084980718791485,
0.019105728715658188,
-0.027282122522592545,
-0.2277841567993164,
-0.02939889393746853,
-0.038830772042274475,
0.027196791023015976,
0.12126997113227844,
0.029732242226600647,
0.0099883321672678,
0.08304647356271744,
-0.006753815338015556,
0.08925078809261322,
-0.03800372779369354,
0.08124437928199768,
0.07017841190099716,
0.06302696466445923,
0.12200601398944855,
-0.010443693958222866,
-0.042353030294179916,
0.0519317090511322,
-0.03908989951014519,
0.22965727746486664,
-0.07194539904594421,
0.18250447511672974,
0.01651238277554512,
0.18629461526870728,
0.017961151897907257,
0.07523477077484131,
-0.019956033676862717,
0.008272949606180191,
-0.0040745860897004604,
-0.05323426052927971,
-0.03924369439482689,
0.013526038266718388,
-0.036609947681427,
0.07307662069797516,
-0.10942882299423218,
0.0054342434741556644,
0.046276576817035675,
0.24498461186885834,
0.0764351412653923,
-0.37140339612960815,
-0.09002078324556351,
-0.010658809915184975,
0.0024736260529607534,
-0.048404961824417114,
0.01542285643517971,
0.10945413261651993,
-0.10156761109828949,
0.03417745605111122,
-0.07298247516155243,
0.0935702845454216,
-0.06796396523714066,
0.016626926138997078,
0.03863188996911049,
0.09296425431966782,
-0.024122094735503197,
0.06842005252838135,
-0.24736925959587097,
0.23334281146526337,
0.013625549152493477,
0.07304833829402924,
-0.0643250122666359,
0.007468635682016611,
0.023633090779185295,
0.0033105877228081226,
0.07755769789218903,
0.0031444865744560957,
-0.017245536670088768,
-0.1941770613193512,
-0.11988072842359543,
0.00435853423550725,
0.06974409520626068,
-0.0417129211127758,
0.11667674779891968,
-0.001138392137363553,
0.00010594813647912815,
0.027819205075502396,
-0.00500250281766057,
-0.061467334628105164,
-0.08493047207593918,
0.018261602148413658,
0.01970808580517769,
0.00929340161383152,
-0.062215693295001984,
-0.11452537775039673,
-0.08088437467813492,
0.15774427354335785,
-0.04252200201153755,
-0.07084804773330688,
-0.10879868268966675,
0.108272485435009,
0.13021647930145264,
-0.08285678178071976,
0.024387242272496223,
0.009070618078112602,
0.09436598420143127,
0.016560548916459084,
-0.06546397507190704,
0.08713347464799881,
-0.04359850287437439,
-0.21138440072536469,
-0.06866275519132614,
0.12213531136512756,
0.044310443103313446,
0.06439480930566788,
-0.02650378830730915,
0.047819092869758606,
-0.03089502826333046,
-0.08614160120487213,
0.04564762860536575,
-0.006676217075437307,
0.09703189134597778,
0.03619542717933655,
-0.01670049875974655,
0.042245130985975266,
-0.056200865656137466,
-0.025452852249145508,
0.1512298583984375,
0.2793392539024353,
-0.09424488991498947,
0.04161899536848068,
0.02624066174030304,
-0.06937318295240402,
-0.1516890972852707,
0.025695232674479485,
0.07981716841459274,
0.025218604132533073,
-0.016837209463119507,
-0.21332745254039764,
0.057753413915634155,
0.1154838427901268,
-0.012726136483252048,
0.1203160285949707,
-0.3443779945373535,
-0.12151870131492615,
0.06954959779977798,
0.10012900829315186,
0.10924151539802551,
-0.1542571783065796,
-0.0576125830411911,
-0.016772368922829628,
-0.14378179609775543,
0.09617449343204498,
-0.04982465133070946,
0.12455671280622482,
-0.063652403652668,
0.0701434537768364,
0.019633539021015167,
-0.068684421479702,
0.13098610937595367,
0.024979954585433006,
0.07692324370145798,
-0.05406118556857109,
-0.013941372744739056,
0.09863107651472092,
-0.06375057250261307,
0.032797202467918396,
-0.09261688590049744,
0.07286043465137482,
-0.13815627992153168,
-0.01926528848707676,
-0.07682539522647858,
0.024718640372157097,
-0.0314786359667778,
-0.049581922590732574,
-0.055345792323350906,
0.03354877606034279,
0.07077671587467194,
-0.009580645710229874,
0.0994873046875,
0.04898744449019432,
0.14848124980926514,
0.0970865786075592,
0.035479433834552765,
-0.0414617583155632,
-0.07684250921010971,
-0.002187119098380208,
-0.0061007309705019,
0.04840238764882088,
-0.1257917732000351,
0.010778887197375298,
0.16425617039203644,
0.04060613736510277,
0.13228139281272888,
0.08295345306396484,
-0.06600870937108994,
0.032907936722040176,
0.04089101031422615,
-0.17879998683929443,
-0.07625751942396164,
-0.017058080062270164,
-0.040077291429042816,
-0.12638869881629944,
0.020369963720440865,
0.09479551762342453,
-0.07748275250196457,
-0.0366143174469471,
-0.009065487422049046,
0.02369622141122818,
-0.0032437918707728386,
0.22419531643390656,
0.0376257598400116,
0.0649355798959732,
-0.11890007555484772,
0.0714620053768158,
0.06406687200069427,
-0.04679055139422417,
0.04329545050859451,
0.07545945048332214,
-0.09339341521263123,
-0.005212060175836086,
0.08046349883079529,
0.16721385717391968,
-0.06573306024074554,
-0.014253652654588223,
-0.15113118290901184,
-0.08749701827764511,
0.09811920672655106,
0.12507224082946777,
0.07822010666131973,
0.04662887379527092,
-0.013683049939572811,
-0.020446650683879852,
-0.117658831179142,
0.09862902760505676,
0.08829349279403687,
0.08202031999826431,
-0.12529553472995758,
0.15485598146915436,
-0.022397715598344803,
0.01719280704855919,
-0.010989158414304256,
0.026396850124001503,
-0.12398483604192734,
-0.00834255013614893,
-0.1282096952199936,
0.03384837135672569,
-0.07285795360803604,
-0.008568176999688148,
-0.022783836349844933,
-0.026335474103689194,
-0.051359858363866806,
0.02493341825902462,
-0.10121971368789673,
-0.052392687648534775,
0.003799459431320429,
0.033480796962976456,
-0.12850911915302277,
-0.013987329788506031,
0.005316291935741901,
-0.08330968022346497,
0.10348173975944519,
0.07345529645681381,
0.0120795713737607,
0.008347047492861748,
-0.06116890534758568,
-0.006254130974411964,
0.005469089839607477,
0.000012669523130171001,
0.05460861325263977,
-0.10275647044181824,
0.01818256452679634,
-0.016994986683130264,
-0.0014843690441921353,
0.02761777490377426,
0.06913241744041443,
-0.1346871256828308,
-0.01808151975274086,
-0.0036884930450469255,
-0.019649766385555267,
-0.07840543985366821,
0.06191202253103256,
0.10017593204975128,
0.006944639142602682,
0.16070058941841125,
-0.07776086032390594,
0.03915507346391678,
-0.22263982892036438,
-0.01513199508190155,
0.001497661811299622,
-0.10852711647748947,
-0.09655626118183136,
-0.007351701147854328,
0.08903486281633377,
-0.058135975152254105,
0.1313658058643341,
-0.01364570390433073,
-0.01842772401869297,
0.009885677136480808,
-0.018184153363108635,
0.03427823260426521,
0.022513924166560173,
0.2071741670370102,
0.03717857599258423,
-0.05882759392261505,
0.05424097180366516,
0.034063003957271576,
0.09339431673288345,
0.13184276223182678,
0.15937770903110504,
0.08696288615465164,
0.03898628056049347,
0.07435556501150131,
0.03393625468015671,
-0.09111085534095764,
-0.12264776229858398,
0.06049388274550438,
-0.05246290564537048,
0.11590388417243958,
0.00121450109872967,
0.20912767946720123,
0.08697081357240677,
-0.15074904263019562,
0.045669667422771454,
-0.055731818079948425,
-0.09708916395902634,
-0.09767037630081177,
-0.08520232886075974,
-0.08607710152864456,
-0.14740431308746338,
0.01957499422132969,
-0.1365552395582199,
0.032506633549928665,
0.10943461954593658,
0.024167032912373543,
-0.006020720582455397,
0.09106616675853729,
0.07444506883621216,
0.010723615065217018,
0.05579943209886551,
0.014306692406535149,
-0.021051451563835144,
-0.041236892342567444,
-0.08943666517734528,
0.042269811034202576,
-0.027757326140999794,
0.06398533284664154,
-0.03263901546597481,
0.007957285270094872,
0.04555479437112808,
-0.0003941720933653414,
-0.09016387909650803,
0.01753246784210205,
-0.0015449984930455685,
0.06233734264969826,
0.05637897923588753,
0.01660199835896492,
0.01611645333468914,
-0.02739911712706089,
0.20468024909496307,
-0.057217665016651154,
-0.022325612604618073,
-0.11745156347751617,
0.22327859699726105,
0.029165441170334816,
-0.03941255807876587,
0.06132989004254341,
-0.09367130696773529,
0.004673515446484089,
0.1883416771888733,
0.20227299630641937,
-0.049363911151885986,
-0.033168792724609375,
0.014073632657527924,
-0.025335902348160744,
0.011442285031080246,
0.08468732237815857,
0.09700755029916763,
0.0316343829035759,
-0.09479761868715286,
-0.025025183334946632,
-0.05970337986946106,
-0.018068673089146614,
-0.03511862829327583,
0.07529532164335251,
0.014236409217119217,
0.0019220947287976742,
-0.05051723122596741,
0.03048798255622387,
-0.08109484612941742,
-0.07601068913936615,
0.04270869493484497,
-0.20044799149036407,
-0.1799193173646927,
-0.013265132904052734,
0.03118525631725788,
0.026984838768839836,
0.055934540927410126,
-0.008216158486902714,
0.021505147218704224,
0.05614060163497925,
-0.028948601335287094,
-0.10642160475254059,
-0.10480435192584991,
0.07316826283931732,
-0.08899247646331787,
0.19556482136249542,
-0.03993329405784607,
0.06394561380147934,
0.1336897313594818,
0.044094234704971313,
-0.13152895867824554,
0.032850418239831924,
0.06328070908784866,
-0.05603024363517761,
0.019925083965063095,
0.12817968428134918,
-0.01848357729613781,
0.06661644577980042,
0.036030277609825134,
-0.05631617456674576,
-0.02069196105003357,
-0.010561581701040268,
-0.0040601626969873905,
-0.07068509608507156,
-0.054091066122055054,
-0.032429441809654236,
0.14123640954494476,
0.20134679973125458,
-0.06625548005104065,
-0.004324994515627623,
-0.062178533524274826,
0.0003807551693171263,
0.05466626212000847,
0.039149560034275055,
-0.030594151467084885,
-0.2753762900829315,
0.007523633539676666,
0.08314462751150131,
0.015385639853775501,
-0.2448648065328598,
-0.0683530867099762,
-0.001207647379487753,
-0.06148980185389519,
-0.0858556479215622,
0.11263749748468399,
0.05191616341471672,
0.07096648961305618,
-0.05401968955993652,
0.014461357146501541,
-0.08561325073242188,
0.1509171575307846,
-0.1328412890434265,
-0.10476207733154297
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# random25eof_find_passage_train10000_eval1000_rare_gpt2_1e-4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the tyzhu/random25eof_find_passage_train10000_eval1000_rare dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2278
- Accuracy: 0.8610
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.5086 | 1.0 | 165 | 2.9782 | 0.3140 |
| 3.2057 | 2.0 | 330 | 2.9331 | 0.3146 |
| 3.1678 | 3.0 | 495 | 2.9121 | 0.3152 |
| 3.1454 | 4.0 | 660 | 2.9026 | 0.3153 |
| 3.1269 | 5.0 | 825 | 2.8901 | 0.3172 |
| 3.1088 | 6.0 | 990 | 2.8721 | 0.3173 |
| 3.0734 | 7.0 | 1155 | 2.8520 | 0.3191 |
| 3.0366 | 8.0 | 1320 | 2.8343 | 0.3206 |
| 3.0023 | 9.0 | 1485 | 2.8128 | 0.3232 |
| 2.9704 | 10.0 | 1650 | 2.7913 | 0.3263 |
| 2.9421 | 11.0 | 1815 | 2.7679 | 0.3282 |
| 2.9177 | 12.0 | 1980 | 2.7425 | 0.3329 |
| 2.8949 | 13.0 | 2145 | 2.7205 | 0.3359 |
| 2.8764 | 14.0 | 2310 | 2.7017 | 0.3386 |
| 2.8587 | 15.0 | 2475 | 2.6847 | 0.3425 |
| 2.8427 | 16.0 | 2640 | 2.6690 | 0.3447 |
| 2.8226 | 17.0 | 2805 | 2.6541 | 0.3487 |
| 2.7993 | 18.0 | 2970 | 2.6359 | 0.3500 |
| 2.7726 | 19.0 | 3135 | 2.6166 | 0.3534 |
| 2.7399 | 20.0 | 3300 | 2.5878 | 0.3587 |
| 2.7006 | 21.0 | 3465 | 2.5625 | 0.3614 |
| 2.6539 | 22.0 | 3630 | 2.5281 | 0.3667 |
| 2.5997 | 23.0 | 3795 | 2.4841 | 0.3731 |
| 2.5386 | 24.0 | 3960 | 2.4382 | 0.3805 |
| 2.4669 | 25.0 | 4125 | 2.3756 | 0.3914 |
| 2.3899 | 26.0 | 4290 | 2.3211 | 0.4006 |
| 2.3063 | 27.0 | 4455 | 2.2600 | 0.4083 |
| 2.2176 | 28.0 | 4620 | 2.1880 | 0.4204 |
| 2.1246 | 29.0 | 4785 | 2.1169 | 0.4347 |
| 2.0341 | 30.0 | 4950 | 2.0373 | 0.4496 |
| 1.9442 | 31.0 | 5115 | 1.9606 | 0.4619 |
| 1.8549 | 32.0 | 5280 | 1.8919 | 0.4749 |
| 1.765 | 33.0 | 5445 | 1.8054 | 0.4924 |
| 1.6795 | 34.0 | 5610 | 1.7215 | 0.5088 |
| 1.6534 | 35.0 | 5775 | 1.6681 | 0.5180 |
| 1.5318 | 36.0 | 5940 | 1.5879 | 0.5358 |
| 1.4528 | 37.0 | 6105 | 1.5126 | 0.5533 |
| 1.3757 | 38.0 | 6270 | 1.4242 | 0.5695 |
| 1.3052 | 39.0 | 6435 | 1.3589 | 0.5851 |
| 1.2374 | 40.0 | 6600 | 1.2803 | 0.6036 |
| 1.175 | 41.0 | 6765 | 1.1866 | 0.6230 |
| 1.1147 | 42.0 | 6930 | 1.1151 | 0.6409 |
| 1.0578 | 43.0 | 7095 | 1.0400 | 0.6575 |
| 1.0034 | 44.0 | 7260 | 0.9695 | 0.6742 |
| 0.9548 | 45.0 | 7425 | 0.9055 | 0.6917 |
| 0.9072 | 46.0 | 7590 | 0.8384 | 0.7085 |
| 0.8639 | 47.0 | 7755 | 0.7790 | 0.7231 |
| 0.8207 | 48.0 | 7920 | 0.7089 | 0.7407 |
| 0.7826 | 49.0 | 8085 | 0.6634 | 0.7547 |
| 0.7482 | 50.0 | 8250 | 0.6017 | 0.7703 |
| 0.7146 | 51.0 | 8415 | 0.5553 | 0.7826 |
| 0.6829 | 52.0 | 8580 | 0.5182 | 0.7910 |
| 0.6589 | 53.0 | 8745 | 0.4788 | 0.8014 |
| 0.6292 | 54.0 | 8910 | 0.4378 | 0.8123 |
| 0.6057 | 55.0 | 9075 | 0.4105 | 0.8200 |
| 0.583 | 56.0 | 9240 | 0.3822 | 0.8277 |
| 0.5629 | 57.0 | 9405 | 0.3589 | 0.8337 |
| 0.544 | 58.0 | 9570 | 0.3414 | 0.8371 |
| 0.5248 | 59.0 | 9735 | 0.3218 | 0.8429 |
| 0.5091 | 60.0 | 9900 | 0.3045 | 0.8467 |
| 0.4931 | 61.0 | 10065 | 0.2969 | 0.8478 |
| 0.4804 | 62.0 | 10230 | 0.2850 | 0.8500 |
| 0.4653 | 63.0 | 10395 | 0.2748 | 0.8524 |
| 0.4534 | 64.0 | 10560 | 0.2677 | 0.8542 |
| 0.4421 | 65.0 | 10725 | 0.2636 | 0.8549 |
| 0.4308 | 66.0 | 10890 | 0.2586 | 0.8558 |
| 0.4204 | 67.0 | 11055 | 0.2537 | 0.8564 |
| 0.4122 | 68.0 | 11220 | 0.2505 | 0.8572 |
| 0.4028 | 69.0 | 11385 | 0.2475 | 0.8579 |
| 0.3944 | 70.0 | 11550 | 0.2451 | 0.8580 |
| 0.3874 | 71.0 | 11715 | 0.2429 | 0.8583 |
| 0.3805 | 72.0 | 11880 | 0.2420 | 0.8584 |
| 0.3755 | 73.0 | 12045 | 0.2400 | 0.8586 |
| 0.3693 | 74.0 | 12210 | 0.2403 | 0.8582 |
| 0.3623 | 75.0 | 12375 | 0.2393 | 0.8583 |
| 0.3582 | 76.0 | 12540 | 0.2382 | 0.8591 |
| 0.3534 | 77.0 | 12705 | 0.2362 | 0.8593 |
| 0.3491 | 78.0 | 12870 | 0.2366 | 0.8589 |
| 0.3455 | 79.0 | 13035 | 0.2349 | 0.8591 |
| 0.3401 | 80.0 | 13200 | 0.2338 | 0.8598 |
| 0.3382 | 81.0 | 13365 | 0.2332 | 0.8596 |
| 0.3327 | 82.0 | 13530 | 0.2331 | 0.8602 |
| 0.3301 | 83.0 | 13695 | 0.2333 | 0.8596 |
| 0.3268 | 84.0 | 13860 | 0.2328 | 0.8599 |
| 0.3241 | 85.0 | 14025 | 0.2315 | 0.8603 |
| 0.3211 | 86.0 | 14190 | 0.2311 | 0.8603 |
| 0.3185 | 87.0 | 14355 | 0.2315 | 0.8601 |
| 0.3149 | 88.0 | 14520 | 0.2318 | 0.8598 |
| 0.314 | 89.0 | 14685 | 0.2303 | 0.8607 |
| 0.3111 | 90.0 | 14850 | 0.2315 | 0.8599 |
| 0.3071 | 91.0 | 15015 | 0.2303 | 0.8606 |
| 0.3057 | 92.0 | 15180 | 0.2313 | 0.8603 |
| 0.3043 | 93.0 | 15345 | 0.2301 | 0.8603 |
| 0.3018 | 94.0 | 15510 | 0.2300 | 0.8606 |
| 0.2997 | 95.0 | 15675 | 0.2294 | 0.8607 |
| 0.2979 | 96.0 | 15840 | 0.2284 | 0.861 |
| 0.2963 | 97.0 | 16005 | 0.2282 | 0.8610 |
| 0.2932 | 98.0 | 16170 | 0.2281 | 0.8612 |
| 0.2923 | 99.0 | 16335 | 0.2279 | 0.8610 |
| 0.2901 | 100.0 | 16500 | 0.2278 | 0.8610 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/random25eof_find_passage_train10000_eval1000_rare"], "metrics": ["accuracy"], "base_model": "gpt2", "model-index": [{"name": "random25eof_find_passage_train10000_eval1000_rare_gpt2_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/random25eof_find_passage_train10000_eval1000_rare", "type": "tyzhu/random25eof_find_passage_train10000_eval1000_rare"}, "metrics": [{"type": "accuracy", "value": 0.8609574468085106, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/random25eof_find_passage_train10000_eval1000_rare_gpt2_1e-4 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/random25eof_find_passage_train10000_eval1000_rare",
"base_model:gpt2",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:32:22+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train10000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| random25eof\_find\_passage\_train10000\_eval1000\_rare\_gpt2\_1e-4
==================================================================
This model is a fine-tuned version of gpt2 on the tyzhu/random25eof\_find\_passage\_train10000\_eval1000\_rare dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2278
* Accuracy: 0.8610
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 100.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train10000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
99,
98,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train10000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.13255129754543304,
0.18134805560112,
-0.002762680873274803,
0.13009855151176453,
0.11814473569393158,
0.03690415248274803,
0.12216871231794357,
0.16045701503753662,
-0.10393892228603363,
0.090070441365242,
0.15657499432563782,
0.09315971285104752,
0.053406182676553726,
0.17955978214740753,
-0.03849228471517563,
-0.2237834334373474,
0.016354814171791077,
0.029259636998176575,
-0.014546320773661137,
0.1389671117067337,
0.07659625262022018,
-0.11705128103494644,
0.09193126857280731,
0.005723774898797274,
-0.19114720821380615,
-0.020591935142874718,
-0.008797027170658112,
-0.054417528212070465,
0.11691948026418686,
0.018560228869318962,
0.07992632687091827,
0.024448681622743607,
0.07564348727464676,
-0.13754971325397491,
0.00033804780105128884,
0.05262867361307144,
0.0021372793707996607,
0.10547181963920593,
0.06290096044540405,
-0.026565510779619217,
0.08962009847164154,
-0.04395691677927971,
0.028545256704092026,
0.016552824527025223,
-0.13851585984230042,
-0.18078427016735077,
-0.09537287801504135,
0.08211848884820938,
0.02281222492456436,
0.08293989300727844,
-0.016970349475741386,
0.12870341539382935,
-0.04668364301323891,
0.07379701733589172,
0.2764723598957062,
-0.290751188993454,
-0.06107722967863083,
0.04140469431877136,
0.015878571197390556,
0.057126257568597794,
-0.09232398122549057,
-0.04369375482201576,
0.05836619809269905,
0.03247031942009926,
0.12062615156173706,
0.00045572620001621544,
-0.031745873391628265,
0.014398934319615364,
-0.1389613300561905,
-0.06360973417758942,
0.14652028679847717,
0.03188595548272133,
-0.040273312479257584,
-0.05361328274011612,
-0.07643529027700424,
-0.20153585076332092,
-0.014895448461174965,
0.02513839304447174,
0.02161128632724285,
-0.030994748696684837,
-0.08774959295988083,
0.01844874769449234,
-0.05807871371507645,
-0.07034745812416077,
-0.014719586819410324,
0.06968937069177628,
0.04983840137720108,
0.02030075155198574,
-0.00399765744805336,
0.12741178274154663,
-0.043105095624923706,
-0.15378816425800323,
-0.0013272016076371074,
0.00019799867004621774,
-0.0000050466951506678015,
-0.028533294796943665,
-0.038671258836984634,
-0.00025444666971452534,
0.0251979511231184,
0.1650048792362213,
-0.05459929257631302,
0.04783036932349205,
0.00843080598860979,
0.026910170912742615,
-0.06540175527334213,
0.11915749311447144,
-0.09020019322633743,
-0.034191738814115524,
0.021177805960178375,
0.09847161918878555,
0.0306007731705904,
-0.011465259827673435,
-0.09140636026859283,
-0.01315637119114399,
0.12611190974712372,
0.025110725313425064,
-0.027289794757962227,
0.05982831493020058,
-0.04644008353352547,
-0.031967032700777054,
0.05023734271526337,
-0.094278983771801,
0.01357177272439003,
0.020413406193256378,
-0.11050987243652344,
-0.06336622685194016,
-0.02324126847088337,
-0.013511097989976406,
-0.04315061494708061,
0.07455482333898544,
-0.11672624945640564,
0.002354053780436516,
-0.0723729357123375,
-0.11469053477048874,
0.0014742466155439615,
-0.10556349158287048,
-0.011128773912787437,
-0.06952378153800964,
-0.22277256846427917,
-0.0319884717464447,
0.02168145589530468,
-0.06923803687095642,
-0.08294489234685898,
-0.07837986201047897,
-0.10113561153411865,
0.03413777053356171,
-0.019768955186009407,
0.07854802906513214,
-0.06784279644489288,
0.10281652957201004,
0.035092078149318695,
0.056876178830862045,
0.011808618903160095,
0.04055720940232277,
-0.0904952809214592,
0.04675321653485298,
-0.15455061197280884,
0.08079749345779419,
-0.049076784402132034,
0.03289922699332237,
-0.09464528411626816,
-0.11516562849283218,
0.04284016415476799,
-0.035307157784700394,
0.10339370369911194,
0.1394490748643875,
-0.15414443612098694,
-0.06467514485120773,
0.19360625743865967,
-0.06334926187992096,
-0.10879364609718323,
0.12150264531373978,
-0.06225091591477394,
-0.020933156833052635,
0.05589498206973076,
0.18141838908195496,
0.062219250947237015,
-0.041643593460321426,
-0.04354702681303024,
-0.03827877715229988,
0.05467524752020836,
-0.04241670295596123,
0.08501127362251282,
0.011126179248094559,
0.017065811902284622,
0.016370592638850212,
-0.030096175149083138,
0.045509811490774155,
-0.1101624146103859,
-0.08688433468341827,
-0.03784346580505371,
-0.09994366765022278,
0.06301537156105042,
0.045177046209573746,
0.07360732555389404,
-0.10219068080186844,
-0.09340748190879822,
0.016086196526885033,
0.10634387284517288,
-0.08326137810945511,
0.0029734813142567873,
-0.07104615867137909,
0.1480572521686554,
-0.07206631451845169,
-0.01831348054111004,
-0.16274145245552063,
-0.015299760736525059,
0.0457485057413578,
0.024555999785661697,
-0.010569379664957523,
-0.027626950293779373,
0.06950178742408752,
0.08832681179046631,
-0.05601906403899193,
-0.058383386582136154,
-0.03260979428887367,
-0.026313913986086845,
-0.11066481471061707,
-0.19129891693592072,
-0.05285397917032242,
-0.003913517110049725,
0.1313462257385254,
-0.20487168431282043,
0.03589358180761337,
0.004741202108561993,
0.11678460985422134,
0.0038904279936105013,
-0.05430585891008377,
-0.007138385903090239,
0.050990406423807144,
-0.06119478866457939,
-0.08508468419313431,
0.05610049515962601,
0.017885282635688782,
-0.06675785779953003,
-0.01612688973546028,
-0.11893829703330994,
0.11875077337026596,
0.11513078212738037,
-0.005745444446802139,
-0.10892336070537567,
0.010714365169405937,
-0.07318885624408722,
-0.02456183172762394,
-0.04399795085191727,
-0.0007477686158381402,
0.1401911824941635,
-0.003006700659170747,
0.15034323930740356,
-0.09865172952413559,
-0.0548616461455822,
0.04088965430855751,
0.010351037606596947,
0.023636071011424065,
0.1364547461271286,
0.056257180869579315,
-0.05469852685928345,
0.15651437640190125,
0.03429161757230759,
-0.05445357784628868,
0.1104477122426033,
-0.05327476188540459,
-0.08066423237323761,
-0.03938843309879303,
0.017105109989643097,
0.02213296853005886,
0.10633570700883865,
-0.08798311650753021,
-0.016477109864354134,
0.03248361870646477,
0.021088331937789917,
0.012417134828865528,
-0.1807330846786499,
-0.030881477519869804,
0.02372925542294979,
-0.0630701407790184,
-0.021738892421126366,
-0.02168840914964676,
0.0037812041118741035,
0.11416100710630417,
0.0033663948997855186,
-0.07712449133396149,
0.031362246721982956,
0.009752378799021244,
-0.07799322158098221,
0.20232932269573212,
-0.07867109775543213,
-0.1218118965625763,
-0.11408292502164841,
-0.03041897900402546,
-0.06396545469760895,
0.0176868736743927,
0.043531376868486404,
-0.06434400379657745,
-0.011490163393318653,
-0.09947925060987473,
0.00009137420420302078,
-0.03237081319093704,
0.02842172607779503,
0.025844428688287735,
-0.02892916463315487,
0.06401429325342178,
-0.10915640741586685,
0.0004339498409535736,
-0.02369707264006138,
-0.036957982927560806,
0.060056839138269424,
0.015021384693682194,
0.08958801627159119,
0.12269417196512222,
-0.016212014481425285,
0.030844518914818764,
-0.03012881428003311,
0.2668917179107666,
-0.03873763233423233,
-0.025946810841560364,
0.10014639049768448,
0.025979161262512207,
0.07573104649782181,
0.11922439187765121,
0.044053152203559875,
-0.0826290175318718,
-0.002385118743404746,
0.018644768744707108,
-0.02730451710522175,
-0.22665761411190033,
-0.029691772535443306,
-0.03898013010621071,
0.02674994431436062,
0.12156514823436737,
0.028592612594366074,
0.010223126038908958,
0.08316031843423843,
-0.00710713118314743,
0.0888378769159317,
-0.038309402763843536,
0.08132092654705048,
0.07134419679641724,
0.06328892707824707,
0.1215406283736229,
-0.010514164343476295,
-0.04190904274582863,
0.05127844959497452,
-0.038446247577667236,
0.2296937108039856,
-0.07180550694465637,
0.18343502283096313,
0.01690928265452385,
0.1867276430130005,
0.01753537729382515,
0.0761842355132103,
-0.019943589344620705,
0.008371850475668907,
-0.004538135137408972,
-0.05331334471702576,
-0.04011352360248566,
0.013100259006023407,
-0.0377960205078125,
0.0727463811635971,
-0.10986892133951187,
0.004657285287976265,
0.045979924499988556,
0.24559509754180908,
0.07724760472774506,
-0.37248316407203674,
-0.09148187190294266,
-0.010544931516051292,
0.0024006993044167757,
-0.048645298928022385,
0.014690336771309376,
0.10979454219341278,
-0.10141457617282867,
0.03443172574043274,
-0.07324646413326263,
0.09357679635286331,
-0.06862615048885345,
0.017367342486977577,
0.03789608180522919,
0.0927334651350975,
-0.02375359833240509,
0.06816592812538147,
-0.24757955968379974,
0.23384380340576172,
0.013935767114162445,
0.07361830025911331,
-0.06522605568170547,
0.00693148747086525,
0.023284174501895905,
0.0026517370715737343,
0.07828254252672195,
0.0033628230448812246,
-0.017927834764122963,
-0.19444765150547028,
-0.11911574751138687,
0.004740437027066946,
0.06960655003786087,
-0.040789972990751266,
0.11764524132013321,
-0.000402899575419724,
0.0005376682383939624,
0.02841760776937008,
-0.0055557796731591225,
-0.061172306537628174,
-0.08348732441663742,
0.017967648804187775,
0.019977092742919922,
0.009575450792908669,
-0.0621902272105217,
-0.11389701068401337,
-0.08033380657434464,
0.15523535013198853,
-0.043129004538059235,
-0.07121331989765167,
-0.1079857274889946,
0.10816337913274765,
0.13047966361045837,
-0.08339101821184158,
0.02413271926343441,
0.008823230862617493,
0.09390081465244293,
0.016601422801613808,
-0.06529022753238678,
0.08734705299139023,
-0.043374836444854736,
-0.21134431660175323,
-0.06759040802717209,
0.12221305072307587,
0.0445844791829586,
0.06458986550569534,
-0.025971831753849983,
0.04764052852988243,
-0.030870672315359116,
-0.08613842725753784,
0.04594574123620987,
-0.006824590265750885,
0.09729825705289841,
0.03480713069438934,
-0.015297180972993374,
0.04290062561631203,
-0.05668562650680542,
-0.024913832545280457,
0.15070001780986786,
0.2795550525188446,
-0.09391129016876221,
0.04037230461835861,
0.026133816689252853,
-0.06874161213636398,
-0.15090930461883545,
0.02446773275732994,
0.07906505465507507,
0.025454562157392502,
-0.016803957521915436,
-0.2131035327911377,
0.057036809623241425,
0.11422412842512131,
-0.012736435979604721,
0.11943943798542023,
-0.34333276748657227,
-0.12089025974273682,
0.0705626904964447,
0.10041831433773041,
0.10890272259712219,
-0.1542477011680603,
-0.05764191597700119,
-0.01654096692800522,
-0.14476802945137024,
0.09772999584674835,
-0.0504133403301239,
0.12497179210186005,
-0.06345368176698685,
0.07106824964284897,
0.019624607637524605,
-0.06892002373933792,
0.13094265758991241,
0.025686876848340034,
0.07654739171266556,
-0.05425719544291496,
-0.015098596923053265,
0.09910020232200623,
-0.06328018754720688,
0.03331839665770531,
-0.09240128099918365,
0.07213912904262543,
-0.138262540102005,
-0.019092030823230743,
-0.07744619250297546,
0.02454851008951664,
-0.031205754727125168,
-0.04947371408343315,
-0.055153872817754745,
0.03379285708069801,
0.07053444534540176,
-0.008592796511948109,
0.09963780641555786,
0.048347726464271545,
0.14741098880767822,
0.09814957529306412,
0.03606060892343521,
-0.04122578352689743,
-0.07568180561065674,
-0.0017354924930259585,
-0.006180005148053169,
0.04818419739603996,
-0.12697742879390717,
0.010795870795845985,
0.1642695516347885,
0.04046941548585892,
0.13211917877197266,
0.08261173218488693,
-0.06647622585296631,
0.03321970999240875,
0.04061591997742653,
-0.17906321585178375,
-0.07691037654876709,
-0.0162018034607172,
-0.04119301214814186,
-0.1269945353269577,
0.021005364134907722,
0.09507062286138535,
-0.07725631445646286,
-0.036450233310461044,
-0.009454341605305672,
0.023934409022331238,
-0.004685156513005495,
0.22392524778842926,
0.03815904259681702,
0.06486760824918747,
-0.11903267353773117,
0.07124073058366776,
0.06347054243087769,
-0.04623526334762573,
0.043633315712213516,
0.07434263080358505,
-0.09379661828279495,
-0.005129210185259581,
0.07949668914079666,
0.16622234880924225,
-0.06633938103914261,
-0.015076776035130024,
-0.1518922746181488,
-0.08775818347930908,
0.09768947958946228,
0.12449553608894348,
0.07840518653392792,
0.04680750146508217,
-0.013315512798726559,
-0.020488863810896873,
-0.11765453964471817,
0.09756072610616684,
0.08780431747436523,
0.08136564493179321,
-0.12465345114469528,
0.15555834770202637,
-0.022556977346539497,
0.017742173746228218,
-0.010968036018311977,
0.026556365191936493,
-0.12343838065862656,
-0.00788974016904831,
-0.12884575128555298,
0.03347327932715416,
-0.07333528250455856,
-0.008616622537374496,
-0.022856922820210457,
-0.026349220424890518,
-0.05162426829338074,
0.024780282750725746,
-0.10129333287477493,
-0.05248701944947243,
0.004204209428280592,
0.03332582861185074,
-0.12854941189289093,
-0.014476521871984005,
0.005521814804524183,
-0.08299041539430618,
0.10349569469690323,
0.07320650666952133,
0.012649452313780785,
0.008491067215800285,
-0.060068484395742416,
-0.006348734255880117,
0.0055180019699037075,
0.0004649759503081441,
0.05406318977475166,
-0.10219457745552063,
0.017762135714292526,
-0.01678565703332424,
-0.0011238311417400837,
0.02765647880733013,
0.06946739554405212,
-0.13430866599082947,
-0.018396640196442604,
-0.0038692515809088945,
-0.01803792081773281,
-0.07893118262290955,
0.0624576210975647,
0.09964365512132645,
0.0076488470658659935,
0.1599119007587433,
-0.07708368450403214,
0.03877827152609825,
-0.22320251166820526,
-0.015182781964540482,
0.001082078437320888,
-0.10931548476219177,
-0.09590760618448257,
-0.007823321036994457,
0.08946491777896881,
-0.05762432888150215,
0.1309252232313156,
-0.014253155328333378,
-0.01781371980905533,
0.009528140537440777,
-0.017465025186538696,
0.03402482345700264,
0.02187173441052437,
0.2084057331085205,
0.03673616051673889,
-0.05906473472714424,
0.05463198572397232,
0.03434363380074501,
0.09261373430490494,
0.1329190731048584,
0.15949390828609467,
0.08793891966342926,
0.03951293230056763,
0.07449132204055786,
0.03432557359337807,
-0.09029228240251541,
-0.12312399595975876,
0.0607440322637558,
-0.05114998295903206,
0.11561916023492813,
0.001279792282730341,
0.2085968255996704,
0.08638012409210205,
-0.15175029635429382,
0.04533158242702484,
-0.05573655664920807,
-0.09709123522043228,
-0.09737864881753922,
-0.08598144352436066,
-0.0855943113565445,
-0.14736391603946686,
0.01921849139034748,
-0.1363663375377655,
0.0317164771258831,
0.11061706393957138,
0.02310705929994583,
-0.006266491487622261,
0.09158502519130707,
0.0740506574511528,
0.010779737494885921,
0.05598525330424309,
0.013958994299173355,
-0.0212105605751276,
-0.04126691445708275,
-0.08982057869434357,
0.04293552041053772,
-0.02784811519086361,
0.06460323184728622,
-0.0327586755156517,
0.008030385710299015,
0.04578736796975136,
-0.00025539484340697527,
-0.09078933298587799,
0.016746768727898598,
-0.0010912981815636158,
0.06267150491476059,
0.05658234655857086,
0.016711827367544174,
0.01621232181787491,
-0.02713238261640072,
0.2039516717195511,
-0.05748367682099342,
-0.022810591384768486,
-0.1172310933470726,
0.22315667569637299,
0.028427107259631157,
-0.03998709097504616,
0.06125783175230026,
-0.09312280267477036,
0.004635713063180447,
0.18948419392108917,
0.20183761417865753,
-0.049505457282066345,
-0.03308867663145065,
0.013822078704833984,
-0.025245826691389084,
0.01139632984995842,
0.08498990535736084,
0.09706450998783112,
0.03129896894097328,
-0.09521642327308655,
-0.024488229304552078,
-0.059531401842832565,
-0.01760021597146988,
-0.03481500968337059,
0.07485735416412354,
0.01466488465666771,
0.002255024155601859,
-0.05041222274303436,
0.030831923708319664,
-0.08093944191932678,
-0.07641085237264633,
0.04257674142718315,
-0.20083151757717133,
-0.179533913731575,
-0.013175399042665958,
0.029660243541002274,
0.028707679361104965,
0.05617281422019005,
-0.00921943224966526,
0.022497668862342834,
0.057076595723629,
-0.028388066217303276,
-0.10670238733291626,
-0.10404576361179352,
0.07346487045288086,
-0.08891883492469788,
0.19513551890850067,
-0.03981902077794075,
0.06481141597032547,
0.13412605226039886,
0.04334999620914459,
-0.13164368271827698,
0.03336741030216217,
0.06326092034578323,
-0.054730065166950226,
0.020345529541373253,
0.12771160900592804,
-0.01843418926000595,
0.06623686105012894,
0.036168746650218964,
-0.057095181196928024,
-0.0210709348320961,
-0.009410597383975983,
-0.00394293200224638,
-0.07091385126113892,
-0.05468344688415527,
-0.032505348324775696,
0.1413963884115219,
0.20063970983028412,
-0.06701245903968811,
-0.004338755272328854,
-0.06168753653764725,
0.0006666528061032295,
0.05573560670018196,
0.038340013474226,
-0.031021183356642723,
-0.27416011691093445,
0.007501290179789066,
0.08298736810684204,
0.014691369608044624,
-0.24449002742767334,
-0.06806263327598572,
-0.001132605946622789,
-0.06204366311430931,
-0.08558852970600128,
0.11223945766687393,
0.05214931070804596,
0.07073410600423813,
-0.05450304597616196,
0.016139330342411995,
-0.08620522171258926,
0.15131354331970215,
-0.13271556794643402,
-0.10557450354099274
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# random25eof_find_passage_train50000_eval1000_rare_gpt2_1e-4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the tyzhu/random25eof_find_passage_train50000_eval1000_rare dataset.
It achieves the following results on the evaluation set:
- Loss: 8.0949
- Accuracy: 0.0169
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.2388 | 1.0 | 790 | 2.9030 | 0.3157 |
| 3.1188 | 2.0 | 1580 | 2.8873 | 0.3166 |
| 3.1052 | 3.0 | 2370 | 2.8811 | 0.3174 |
| 3.1 | 4.0 | 3160 | 2.8791 | 0.3177 |
| 3.0872 | 5.0 | 3950 | 2.8697 | 0.3169 |
| 3.0696 | 6.0 | 4740 | 2.8580 | 0.3194 |
| 3.6024 | 7.0 | 5530 | 3.4806 | 0.2323 |
| 3.0601 | 8.0 | 6320 | 2.8489 | 0.3201 |
| 3.0245 | 9.0 | 7110 | 2.8315 | 0.3209 |
| 3.003 | 10.0 | 7900 | 2.8208 | 0.3236 |
| 2.9808 | 11.0 | 8690 | 2.7987 | 0.3258 |
| 2.9592 | 12.0 | 9480 | 2.7816 | 0.3283 |
| 2.9388 | 13.0 | 10270 | 2.7593 | 0.3326 |
| 2.9213 | 14.0 | 11060 | 2.7403 | 0.3351 |
| 2.9383 | 15.0 | 11850 | 2.7829 | 0.3305 |
| 4.3435 | 16.0 | 12640 | 3.8353 | 0.2479 |
| 4.2322 | 17.0 | 13430 | 3.6782 | 0.2623 |
| 4.6505 | 18.0 | 14220 | 4.8186 | 0.2034 |
| 3.8905 | 19.0 | 15010 | 3.4753 | 0.2475 |
| 3.7183 | 20.0 | 15800 | 3.0024 | 0.3127 |
| 3.5937 | 21.0 | 16590 | 3.1250 | 0.3059 |
| 5.6916 | 22.0 | 17380 | 3.5780 | 0.2303 |
| 5.3999 | 23.0 | 18170 | 4.2021 | 0.1463 |
| 4.591 | 24.0 | 18960 | 3.8260 | 0.1754 |
| 4.4151 | 25.0 | 19750 | 3.8398 | 0.1717 |
| 5.2757 | 26.0 | 20540 | 6.3746 | 0.1125 |
| 9.7884 | 27.0 | 21330 | 6.7146 | 0.1568 |
| 6.1396 | 28.0 | 22120 | 5.2031 | 0.1461 |
| 6.0073 | 29.0 | 22910 | 5.5025 | 0.1099 |
| 5.9667 | 30.0 | 23700 | 5.6595 | 0.0809 |
| 6.1704 | 31.0 | 24490 | 6.2647 | 0.0596 |
| 6.4117 | 32.0 | 25280 | 6.7793 | 0.0704 |
| 6.7125 | 33.0 | 26070 | 8.0069 | 0.0687 |
| 5.2982 | 34.0 | 26860 | 3.9177 | 0.1559 |
| 3.9204 | 35.0 | 27650 | 3.5765 | 0.2526 |
| 4.6918 | 36.0 | 28440 | 5.2898 | 0.0757 |
| 5.2076 | 37.0 | 29230 | 5.6341 | 0.0866 |
| 5.4105 | 38.0 | 30020 | 5.8781 | 0.0854 |
| 5.9246 | 39.0 | 30810 | 6.8365 | 0.0641 |
| 6.2495 | 40.0 | 31600 | 6.8572 | 0.0639 |
| 5.5856 | 41.0 | 32390 | 6.4182 | 0.0820 |
| 5.805 | 42.0 | 33180 | 6.2804 | 0.0701 |
| 5.772 | 43.0 | 33970 | 6.5162 | 0.0672 |
| 6.1005 | 44.0 | 34760 | 6.6292 | 0.0661 |
| 5.9056 | 45.0 | 35550 | 6.6549 | 0.0641 |
| 5.9554 | 46.0 | 36340 | 6.8468 | 0.0583 |
| 6.1045 | 47.0 | 37130 | 7.2076 | 0.0480 |
| 6.2245 | 48.0 | 37920 | 7.2001 | 0.0440 |
| 6.3846 | 49.0 | 38710 | 7.5064 | 0.0429 |
| 6.4392 | 50.0 | 39500 | 7.0399 | 0.0485 |
| 6.6399 | 51.0 | 40290 | 7.7912 | 0.0431 |
| 6.7447 | 52.0 | 41080 | 7.6136 | 0.0609 |
| 6.6511 | 53.0 | 41870 | 7.2568 | 0.0622 |
| 5.4705 | 54.0 | 42660 | 4.2823 | 0.0887 |
| 4.5982 | 55.0 | 43450 | 4.1356 | 0.0764 |
| 4.3264 | 56.0 | 44240 | 4.0260 | 0.0904 |
| 4.3061 | 57.0 | 45030 | 4.0866 | 0.0893 |
| 4.4114 | 58.0 | 45820 | 4.1726 | 0.0841 |
| 4.4357 | 59.0 | 46610 | 4.2065 | 0.0851 |
| 4.6297 | 60.0 | 47400 | 4.2080 | 0.0681 |
| 4.615 | 61.0 | 48190 | 4.3039 | 0.0824 |
| 4.6879 | 62.0 | 48980 | 4.3113 | 0.1058 |
| 4.5669 | 63.0 | 49770 | 4.3563 | 0.1069 |
| 4.6161 | 64.0 | 50560 | 4.2010 | 0.1093 |
| 4.5767 | 65.0 | 51350 | 4.4816 | 0.0853 |
| 4.6556 | 66.0 | 52140 | 4.5231 | 0.0684 |
| 4.7147 | 67.0 | 52930 | 4.5471 | 0.0682 |
| 4.7333 | 68.0 | 53720 | 4.5433 | 0.0779 |
| 4.7297 | 69.0 | 54510 | 4.7392 | 0.0686 |
| 4.802 | 70.0 | 55300 | 4.5169 | 0.0690 |
| 4.6399 | 71.0 | 56090 | 4.4978 | 0.0691 |
| 4.6481 | 72.0 | 56880 | 4.5414 | 0.0693 |
| 4.6695 | 73.0 | 57670 | 4.5581 | 0.0690 |
| 4.7096 | 74.0 | 58460 | 4.6022 | 0.0696 |
| 4.7361 | 75.0 | 59250 | 4.6220 | 0.069 |
| 4.7371 | 76.0 | 60040 | 4.6045 | 0.0693 |
| 4.7257 | 77.0 | 60830 | 4.5894 | 0.0698 |
| 4.7535 | 78.0 | 61620 | 4.6369 | 0.0694 |
| 4.7742 | 79.0 | 62410 | 4.6312 | 0.0637 |
| 4.7726 | 80.0 | 63200 | 4.6392 | 0.0619 |
| 4.7963 | 81.0 | 63990 | 4.6895 | 0.0499 |
| 4.8915 | 82.0 | 64780 | 4.7156 | 0.0463 |
| 8.7667 | 83.0 | 65570 | 10.8358 | 0.0236 |
| 9.9203 | 84.0 | 66360 | 10.8358 | 0.0236 |
| 9.9425 | 85.0 | 67150 | 10.8358 | 0.0236 |
| 9.9182 | 86.0 | 67940 | 10.8358 | 0.0236 |
| 9.9425 | 87.0 | 68730 | 10.8358 | 0.0236 |
| 9.9378 | 88.0 | 69520 | 10.8178 | 0.0230 |
| 9.9304 | 89.0 | 70310 | 10.5802 | 0.0187 |
| 9.9379 | 90.0 | 71100 | 10.3706 | 0.0197 |
| 11.321 | 91.0 | 71890 | 13.1686 | 0.0074 |
| 10.8639 | 92.0 | 72680 | 7.8597 | 0.0358 |
| 8.9673 | 93.0 | 73470 | 8.0068 | 0.0351 |
| 8.9745 | 94.0 | 74260 | 8.0603 | 0.0361 |
| 9.3914 | 95.0 | 75050 | 8.1805 | 0.0155 |
| 10.4284 | 96.0 | 75840 | 10.7251 | 0.0166 |
| 10.2511 | 97.0 | 76630 | 9.4927 | 0.0177 |
| 9.9685 | 98.0 | 77420 | 9.4927 | 0.0177 |
| 9.9626 | 99.0 | 78210 | 9.4927 | 0.0177 |
| 9.9793 | 100.0 | 79000 | 8.0949 | 0.0169 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/random25eof_find_passage_train50000_eval1000_rare"], "metrics": ["accuracy"], "base_model": "gpt2", "model-index": [{"name": "random25eof_find_passage_train50000_eval1000_rare_gpt2_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/random25eof_find_passage_train50000_eval1000_rare", "type": "tyzhu/random25eof_find_passage_train50000_eval1000_rare"}, "metrics": [{"type": "accuracy", "value": 0.016936170212765958, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/random25eof_find_passage_train50000_eval1000_rare_gpt2_1e-4 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/random25eof_find_passage_train50000_eval1000_rare",
"base_model:gpt2",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:32:28+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train50000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| random25eof\_find\_passage\_train50000\_eval1000\_rare\_gpt2\_1e-4
==================================================================
This model is a fine-tuned version of gpt2 on the tyzhu/random25eof\_find\_passage\_train50000\_eval1000\_rare dataset.
It achieves the following results on the evaluation set:
* Loss: 8.0949
* Accuracy: 0.0169
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 100.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train50000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
100,
98,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train50000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.1356978714466095,
0.17601539194583893,
-0.002908194437623024,
0.1278006136417389,
0.12731392681598663,
0.04007171839475632,
0.11887001991271973,
0.16189149022102356,
-0.09778767824172974,
0.0858951210975647,
0.15126706659793854,
0.09757358580827713,
0.054812781512737274,
0.16989512741565704,
-0.03549358621239662,
-0.2270077019929886,
0.014316929504275322,
0.026278752833604813,
-0.016859624534845352,
0.14478886127471924,
0.07331924885511398,
-0.1161651611328125,
0.08989417552947998,
0.003642057301476598,
-0.18278761208057404,
-0.021292710676789284,
-0.008281741291284561,
-0.05216292291879654,
0.11903050541877747,
0.020150404423475266,
0.08461981266736984,
0.02766464278101921,
0.07604924589395523,
-0.1480630487203598,
0.0015651358989998698,
0.05272709205746651,
0.0008940853294916451,
0.10324063897132874,
0.0700521171092987,
-0.0329049713909626,
0.09049412608146667,
-0.04784785956144333,
0.024574199691414833,
0.01625949516892433,
-0.134182408452034,
-0.17641028761863708,
-0.0929441899061203,
0.08294537663459778,
0.017512768507003784,
0.09218290448188782,
-0.013872731477022171,
0.11932002007961273,
-0.05457165092229843,
0.07668205350637436,
0.27708688378334045,
-0.2848174273967743,
-0.05864867940545082,
0.03783440217375755,
0.015644507482647896,
0.06344024091959,
-0.09310916811227798,
-0.0484258271753788,
0.05175716057419777,
0.029693977907299995,
0.11417517811059952,
0.0017138600815087557,
-0.03437891975045204,
0.016571227461099625,
-0.14252839982509613,
-0.06498929858207703,
0.136387899518013,
0.030883897095918655,
-0.03579141944646835,
-0.04746897891163826,
-0.07750077545642853,
-0.20100514590740204,
-0.015270533040165901,
0.02744857780635357,
0.019073188304901123,
-0.030757203698158264,
-0.08269218355417252,
0.01648486778140068,
-0.06293359398841858,
-0.07074002921581268,
-0.01800195872783661,
0.0690387636423111,
0.04840034246444702,
0.020243516191840172,
-0.0020903823897242546,
0.1286906599998474,
-0.031422246247529984,
-0.15098103880882263,
0.0011844986584037542,
0.0012471507070586085,
-0.00540617061778903,
-0.022858845070004463,
-0.041119955480098724,
-0.002243892289698124,
0.0228244811296463,
0.16001535952091217,
-0.042661380022764206,
0.04369043558835983,
0.011968499980866909,
0.027185380458831787,
-0.07036633789539337,
0.12237018346786499,
-0.09794676303863525,
-0.04166313633322716,
0.019192906096577644,
0.10262089967727661,
0.02741387113928795,
-0.011638791300356388,
-0.09084086120128632,
-0.020472053438425064,
0.12880279123783112,
0.026548733934760094,
-0.017619799822568893,
0.05802697688341141,
-0.04903655871748924,
-0.03643900528550148,
0.04932834580540657,
-0.09573689848184586,
0.007972612977027893,
0.028885014355182648,
-0.11261314153671265,
-0.053834039717912674,
-0.012686533853411674,
-0.01894095353782177,
-0.044929634779691696,
0.081668421626091,
-0.11737631261348724,
0.006943870801478624,
-0.07063588500022888,
-0.11936264485120773,
0.0034193829633295536,
-0.10046520084142685,
-0.013386979699134827,
-0.07079511880874634,
-0.2212713211774826,
-0.03402362018823624,
0.018626559525728226,
-0.06672314554452896,
-0.08088574558496475,
-0.07884829491376877,
-0.10251135379076004,
0.034692950546741486,
-0.021410072222352028,
0.07976425439119339,
-0.06876537948846817,
0.11031032353639603,
0.03105282597243786,
0.05203823000192642,
0.020423367619514465,
0.047735776752233505,
-0.08988393843173981,
0.04222618788480759,
-0.14019842445850372,
0.08557598292827606,
-0.05561227723956108,
0.028438901528716087,
-0.09405827522277832,
-0.12045690417289734,
0.04059179127216339,
-0.035762157291173935,
0.10372471809387207,
0.1446559876203537,
-0.1453000009059906,
-0.06906259804964066,
0.18807032704353333,
-0.06671417504549026,
-0.10205229371786118,
0.1216762363910675,
-0.059536755084991455,
-0.02594650164246559,
0.05074864625930786,
0.17299363017082214,
0.07514463365077972,
-0.046784013509750366,
-0.03874146193265915,
-0.02553490921854973,
0.055824581533670425,
-0.04877603054046631,
0.09036030620336533,
0.00939764454960823,
0.01288197748363018,
0.015346376225352287,
-0.04158778861165047,
0.054703228175640106,
-0.11485930532217026,
-0.08865156024694443,
-0.03352655470371246,
-0.09671606123447418,
0.07100554555654526,
0.050645433366298676,
0.07075423747301102,
-0.09310341626405716,
-0.09437111765146255,
0.024322187528014183,
0.11113810539245605,
-0.0840834453701973,
0.0023523306008428335,
-0.06758588552474976,
0.1454630047082901,
-0.0750540941953659,
-0.022717954590916634,
-0.16757109761238098,
-0.02442159131169319,
0.0401282012462616,
0.022112248465418816,
-0.01019507460296154,
-0.018351418897509575,
0.06949947774410248,
0.08715987205505371,
-0.05379479378461838,
-0.06223040446639061,
-0.03709644451737404,
-0.02736017480492592,
-0.11067915707826614,
-0.18939124047756195,
-0.06016111001372337,
-0.002060812897980213,
0.1419268697500229,
-0.2018345147371292,
0.034719061106443405,
0.0017308404203504324,
0.10875604301691055,
0.0028323987498879433,
-0.05119701474905014,
-0.006337473168969154,
0.05761931464076042,
-0.05674661323428154,
-0.08014571666717529,
0.062333863228559494,
0.016035014763474464,
-0.06653361022472382,
-0.011082924902439117,
-0.11729026585817337,
0.11918746680021286,
0.11526799201965332,
-0.018485644832253456,
-0.10223766416311264,
0.014470396563410759,
-0.07406140863895416,
-0.02975340746343136,
-0.038192205131053925,
-0.0023767738603055477,
0.13454359769821167,
0.0031930364202708006,
0.1511184424161911,
-0.09376268833875656,
-0.048639096319675446,
0.03731294721364975,
0.014295603148639202,
0.022249864414334297,
0.14378978312015533,
0.061542220413684845,
-0.03983185812830925,
0.15509769320487976,
0.02905428037047386,
-0.05736587569117546,
0.10703625530004501,
-0.04868428409099579,
-0.0880933403968811,
-0.03841445595026016,
0.018361665308475494,
0.020555095747113228,
0.09863244742155075,
-0.0980498343706131,
-0.01699005253612995,
0.035549264401197433,
0.018303755670785904,
0.01873454637825489,
-0.1835165023803711,
-0.033648811280727386,
0.025952491909265518,
-0.0673721507191658,
-0.02036961540579796,
-0.016831552609801292,
0.007369477767497301,
0.11251527070999146,
0.003307880135253072,
-0.08158962428569794,
0.029695376753807068,
0.0030935010872781277,
-0.08064982295036316,
0.20593304932117462,
-0.07860599458217621,
-0.131826713681221,
-0.1234191358089447,
-0.029180100187659264,
-0.06047769635915756,
0.013681589625775814,
0.04304235428571701,
-0.058212168514728546,
-0.010131695307791233,
-0.09319224208593369,
0.006548124365508556,
-0.03399842604994774,
0.025917898863554,
0.013630875386297703,
-0.03127044811844826,
0.06187906116247177,
-0.111960768699646,
0.004070024937391281,
-0.026429856196045876,
-0.043777357786893845,
0.060646723955869675,
0.016159597784280777,
0.09525603801012039,
0.12746113538742065,
-0.011937259696424007,
0.027307262644171715,
-0.02837497927248478,
0.263754665851593,
-0.03597003221511841,
-0.031762611120939255,
0.10993746668100357,
0.02654135972261429,
0.07716206461191177,
0.12034399807453156,
0.04448845610022545,
-0.07436676323413849,
-0.005644634831696749,
0.022631749510765076,
-0.02255024015903473,
-0.23325183987617493,
-0.03416988626122475,
-0.04045668616890907,
0.027617665007710457,
0.11310970038175583,
0.026228394359350204,
0.010587462224066257,
0.0802621990442276,
-0.008177406154572964,
0.0782575011253357,
-0.040182970464229584,
0.07433968782424927,
0.08232159167528152,
0.06131032109260559,
0.12482421100139618,
-0.0073966109193861485,
-0.03825167194008827,
0.0513605922460556,
-0.044889748096466064,
0.23245981335639954,
-0.07537148147821426,
0.18582949042320251,
0.018786324188113213,
0.19400209188461304,
0.013733966276049614,
0.07484497129917145,
-0.019082320854067802,
0.012491782195866108,
-0.0020013784524053335,
-0.05234568938612938,
-0.04955195263028145,
0.01050489954650402,
-0.03322315216064453,
0.07599364221096039,
-0.11633580923080444,
0.0012105683563277125,
0.04175359010696411,
0.24164414405822754,
0.07535194605588913,
-0.36492103338241577,
-0.09754545986652374,
-0.016004571691155434,
0.0005056518712081015,
-0.041729167103767395,
0.012772879563272,
0.10993308573961258,
-0.1061854287981987,
0.02265295945107937,
-0.07797519862651825,
0.09243956208229065,
-0.0729847252368927,
0.015113062225282192,
0.04238208010792732,
0.09122715145349503,
-0.020106878131628036,
0.0731431245803833,
-0.24522504210472107,
0.23916861414909363,
0.009788891300559044,
0.06474552303552628,
-0.06208806484937668,
0.005512611474841833,
0.028114715591073036,
0.006912223994731903,
0.0800514966249466,
0.002801810624077916,
0.001602126401849091,
-0.2026359736919403,
-0.12396431714296341,
0.0012381612323224545,
0.07171297818422318,
-0.04624801129102707,
0.11688454449176788,
-0.0055467113852500916,
-0.003877498907968402,
0.029233651235699654,
0.006305424030870199,
-0.05377786234021187,
-0.08134835958480835,
0.024833861738443375,
0.012699073180556297,
0.01586875505745411,
-0.06287696957588196,
-0.12194182723760605,
-0.08087150752544403,
0.15241174399852753,
-0.054082565009593964,
-0.07241444289684296,
-0.10871527343988419,
0.11241740733385086,
0.1347343474626541,
-0.0915725827217102,
0.024339184165000916,
0.010336777195334435,
0.08377118408679962,
0.021356819197535515,
-0.0722309872508049,
0.08385777473449707,
-0.04458354413509369,
-0.20991474390029907,
-0.06466422975063324,
0.12448521703481674,
0.04439806565642357,
0.0669010803103447,
-0.033985622227191925,
0.04172806069254875,
-0.03196434676647186,
-0.08663176745176315,
0.035837989300489426,
-0.00045337097253650427,
0.08894498646259308,
0.04915923252701759,
-0.01998276263475418,
0.0314052514731884,
-0.060429975390434265,
-0.017624786123633385,
0.15152853727340698,
0.2721569240093231,
-0.09441407024860382,
0.04238772392272949,
0.025395603850483894,
-0.06804928183555603,
-0.15893709659576416,
0.021791961044073105,
0.08322314918041229,
0.025510387495160103,
-0.015334495343267918,
-0.21350330114364624,
0.058544691652059555,
0.11681858450174332,
-0.011110256426036358,
0.11628425121307373,
-0.35977116227149963,
-0.1192089095711708,
0.0679224357008934,
0.10092150419950485,
0.1138242557644844,
-0.1559440642595291,
-0.06216975674033165,
-0.004364760592579842,
-0.14749892055988312,
0.0983569547533989,
-0.0387362465262413,
0.12614206969738007,
-0.06451614201068878,
0.06919556856155396,
0.022051533684134483,
-0.06891343742609024,
0.1299382448196411,
0.028581246733665466,
0.07214096188545227,
-0.05178247019648552,
-0.017287196591496468,
0.09781001508235931,
-0.05689301714301109,
0.030807361006736755,
-0.08616671711206436,
0.07282387465238571,
-0.14684127271175385,
-0.018584897741675377,
-0.08836697787046432,
0.026960797607898712,
-0.0334249846637249,
-0.04810722917318344,
-0.046594876796007156,
0.037219006568193436,
0.07389532774686813,
-0.0050217704847455025,
0.09765947610139847,
0.04300091415643692,
0.1456999033689499,
0.09799914807081223,
0.033064015209674835,
-0.03322083503007889,
-0.08633484691381454,
-0.01105793658643961,
-0.004958901088684797,
0.047617796808481216,
-0.11926758289337158,
0.007750766817480326,
0.16789765655994415,
0.04377119988203049,
0.1351950317621231,
0.0815812274813652,
-0.06639949232339859,
0.030587099492549896,
0.04031507670879364,
-0.17762480676174164,
-0.07554478198289871,
-0.022111617028713226,
-0.053823765367269516,
-0.12948961555957794,
0.01527068205177784,
0.09791342914104462,
-0.07479656487703323,
-0.03430739417672157,
-0.00987815298140049,
0.023748591542243958,
-0.0019865273497998714,
0.2264605164527893,
0.04357079789042473,
0.06585396826267242,
-0.11826185882091522,
0.06769383698701859,
0.06646767258644104,
-0.05759622901678085,
0.031781502068042755,
0.07994344085454941,
-0.09300383180379868,
-0.009628464467823505,
0.07333335280418396,
0.15334104001522064,
-0.07431335002183914,
-0.011075442656874657,
-0.14624324440956116,
-0.08310748636722565,
0.09673221409320831,
0.12761922180652618,
0.08170197159051895,
0.04955095797777176,
-0.014304716140031815,
-0.02204599604010582,
-0.11395835131406784,
0.1034262403845787,
0.09091746807098389,
0.07544755935668945,
-0.12311454862356186,
0.16856303811073303,
-0.022878337651491165,
0.024249710142612457,
-0.010531429201364517,
0.02500762604176998,
-0.11528385430574417,
-0.00889492966234684,
-0.1307901293039322,
0.03712519630789757,
-0.07159306108951569,
-0.0070758056826889515,
-0.023365933448076248,
-0.032287679612636566,
-0.04996180534362793,
0.02466130629181862,
-0.10136143863201141,
-0.05472564324736595,
0.0015512616373598576,
0.035613905638456345,
-0.1321103274822235,
-0.019644608721137047,
0.007307255640625954,
-0.08338523656129837,
0.10510950535535812,
0.08204622566699982,
0.016623780131340027,
0.011918486095964909,
-0.06406591832637787,
-0.00946089532226324,
0.0034056291915476322,
0.005613464396446943,
0.05137676000595093,
-0.09749969094991684,
0.0230691060423851,
-0.019075145944952965,
-0.006157413125038147,
0.0258843582123518,
0.07199238240718842,
-0.14005324244499207,
-0.019105883315205574,
-0.005266076419502497,
-0.01526978611946106,
-0.07993073761463165,
0.060617949813604355,
0.09335769712924957,
0.0098340455442667,
0.1602010875940323,
-0.07894132286310196,
0.048466071486473083,
-0.22764194011688232,
-0.014986858703196049,
-0.00380896357819438,
-0.10362561047077179,
-0.09830305725336075,
-0.012724836356937885,
0.09166984260082245,
-0.05674408748745918,
0.11869604885578156,
-0.017190923914313316,
-0.0040280758403241634,
0.006368598435074091,
-0.01577885076403618,
0.045155119150877,
0.02013389952480793,
0.20617789030075073,
0.042355917394161224,
-0.05568651482462883,
0.058048050850629807,
0.033983148634433746,
0.08746375888586044,
0.12955832481384277,
0.16484731435775757,
0.09411739557981491,
0.039871472865343094,
0.07473046332597733,
0.03823466598987579,
-0.09303498268127441,
-0.12445489317178726,
0.04747220128774643,
-0.05513468757271767,
0.11305132508277893,
0.0014518508687615395,
0.21563105285167694,
0.08233297616243362,
-0.15208932757377625,
0.05029914900660515,
-0.05145635828375816,
-0.09576403349637985,
-0.09667856991291046,
-0.08190646767616272,
-0.08196724951267242,
-0.1464664340019226,
0.017590725794434547,
-0.13704325258731842,
0.029273169115185738,
0.11666565388441086,
0.022967498749494553,
-0.008171760477125645,
0.0911722332239151,
0.0727636069059372,
0.0036698575131595135,
0.05555137246847153,
0.01500279363244772,
-0.01700616255402565,
-0.04403277114033699,
-0.09102782607078552,
0.04588492587208748,
-0.02544386498630047,
0.06161422282457352,
-0.03430167958140373,
0.008240426890552044,
0.048248041421175,
-0.004612855613231659,
-0.09653522819280624,
0.015742836520075798,
0.0001605480065336451,
0.06546161323785782,
0.06573626399040222,
0.01648298278450966,
0.019719665870070457,
-0.027707533910870552,
0.21075275540351868,
-0.0576808862388134,
-0.024863464757800102,
-0.11176010221242905,
0.22730502486228943,
0.031507112085819244,
-0.03757508471608162,
0.060510776937007904,
-0.0939159169793129,
0.003397406078875065,
0.19578367471694946,
0.2024313360452652,
-0.05570220947265625,
-0.030664652585983276,
0.025312375277280807,
-0.024412401020526886,
0.01671496033668518,
0.08146136999130249,
0.09909210354089737,
0.044973041862249374,
-0.09865084290504456,
-0.02862831950187683,
-0.05704496055841446,
-0.015678690746426582,
-0.03212003782391548,
0.07076169550418854,
0.009753274731338024,
-0.00028710326296277344,
-0.05014165863394737,
0.03342800587415695,
-0.08469012379646301,
-0.08394935727119446,
0.050868477672338486,
-0.20567354559898376,
-0.18095971643924713,
-0.020178813487291336,
0.03412790223956108,
0.03580677881836891,
0.056479498744010925,
-0.008662472479045391,
0.02059517800807953,
0.06478527188301086,
-0.025406489148736,
-0.11369773745536804,
-0.10344570130109787,
0.07174400985240936,
-0.08069208264350891,
0.18691402673721313,
-0.038404472172260284,
0.06503546237945557,
0.1321403831243515,
0.05263413488864899,
-0.1308334320783615,
0.033888619393110275,
0.06605979055166245,
-0.061804451048374176,
0.024494586512446404,
0.12588436901569366,
-0.01679137721657753,
0.06971379369497299,
0.033323515206575394,
-0.06238183006644249,
-0.018386153504252434,
-0.011483985930681229,
-0.009565345011651516,
-0.06573424488306046,
-0.05640411376953125,
-0.030471321195364,
0.13844022154808044,
0.20663206279277802,
-0.06453821063041687,
-0.007901925593614578,
-0.06287066638469696,
-0.009296257048845291,
0.0509188286960125,
0.04722285643219948,
-0.03249647095799446,
-0.26514744758605957,
0.009111781604588032,
0.06262422353029251,
0.021558811888098717,
-0.23940253257751465,
-0.06823740899562836,
0.004288178868591785,
-0.06384270638227463,
-0.08778027445077896,
0.113871730864048,
0.04334356263279915,
0.06649186462163925,
-0.048133060336112976,
0.019174447283148766,
-0.08312270045280457,
0.15495586395263672,
-0.14342044293880463,
-0.10745573043823242
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# random25eof_find_passage_train5000_eval1000_rare_gpt2_1e-4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the tyzhu/random25eof_find_passage_train5000_eval1000_rare dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2137
- Accuracy: 0.8615
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.732 | 1.0 | 86 | 3.0607 | 0.3101 |
| 3.2943 | 2.0 | 172 | 2.9724 | 0.3130 |
| 3.2215 | 3.0 | 258 | 2.9441 | 0.3150 |
| 3.1844 | 4.0 | 344 | 2.9137 | 0.3150 |
| 3.1533 | 5.0 | 430 | 2.8964 | 0.3170 |
| 3.1215 | 6.0 | 516 | 2.8791 | 0.3166 |
| 3.0819 | 7.0 | 602 | 2.8529 | 0.3188 |
| 3.0365 | 8.0 | 688 | 2.8275 | 0.3218 |
| 2.9901 | 9.0 | 774 | 2.7925 | 0.3242 |
| 2.9496 | 10.0 | 860 | 2.7557 | 0.3299 |
| 2.9226 | 11.0 | 946 | 2.7238 | 0.3330 |
| 2.8958 | 12.0 | 1032 | 2.6933 | 0.3383 |
| 2.8689 | 13.0 | 1118 | 2.6698 | 0.3430 |
| 2.8448 | 14.0 | 1204 | 2.6496 | 0.3460 |
| 2.8181 | 15.0 | 1290 | 2.6313 | 0.3493 |
| 2.7868 | 16.0 | 1376 | 2.6125 | 0.3527 |
| 2.7474 | 17.0 | 1462 | 2.5802 | 0.3567 |
| 2.6983 | 18.0 | 1548 | 2.5438 | 0.3627 |
| 2.6388 | 19.0 | 1634 | 2.5006 | 0.3696 |
| 2.5679 | 20.0 | 1720 | 2.4438 | 0.3776 |
| 2.4869 | 21.0 | 1806 | 2.3926 | 0.3852 |
| 2.4006 | 22.0 | 1892 | 2.3235 | 0.3971 |
| 2.3065 | 23.0 | 1978 | 2.2513 | 0.4094 |
| 2.2127 | 24.0 | 2064 | 2.1724 | 0.422 |
| 2.1144 | 25.0 | 2150 | 2.0957 | 0.4358 |
| 2.0214 | 26.0 | 2236 | 2.0211 | 0.4492 |
| 1.9232 | 27.0 | 2322 | 1.9406 | 0.4649 |
| 1.8304 | 28.0 | 2408 | 1.8519 | 0.4811 |
| 1.7377 | 29.0 | 2494 | 1.7617 | 0.4971 |
| 1.6455 | 30.0 | 2580 | 1.6824 | 0.5150 |
| 1.5605 | 31.0 | 2666 | 1.5949 | 0.5325 |
| 1.4816 | 32.0 | 2752 | 1.5060 | 0.5501 |
| 1.4033 | 33.0 | 2838 | 1.4264 | 0.5698 |
| 1.541 | 34.0 | 2924 | 2.0068 | 0.4731 |
| 1.3891 | 35.0 | 3010 | 1.2975 | 0.5977 |
| 1.2288 | 36.0 | 3096 | 1.2059 | 0.6171 |
| 1.1547 | 37.0 | 3182 | 1.1224 | 0.6384 |
| 1.092 | 38.0 | 3268 | 1.0348 | 0.6599 |
| 1.0286 | 39.0 | 3354 | 0.9516 | 0.6806 |
| 0.9689 | 40.0 | 3440 | 0.8732 | 0.6993 |
| 0.9206 | 41.0 | 3526 | 0.8068 | 0.7168 |
| 0.8681 | 42.0 | 3612 | 0.7309 | 0.7378 |
| 0.823 | 43.0 | 3698 | 0.6805 | 0.7477 |
| 0.7827 | 44.0 | 3784 | 0.6308 | 0.7616 |
| 0.7431 | 45.0 | 3870 | 0.5659 | 0.7812 |
| 0.71 | 46.0 | 3956 | 0.5182 | 0.7914 |
| 0.6755 | 47.0 | 4042 | 0.4704 | 0.8052 |
| 0.6454 | 48.0 | 4128 | 0.4378 | 0.8135 |
| 0.6165 | 49.0 | 4214 | 0.4049 | 0.8217 |
| 0.5928 | 50.0 | 4300 | 0.3709 | 0.8301 |
| 0.5692 | 51.0 | 4386 | 0.3482 | 0.8348 |
| 0.5503 | 52.0 | 4472 | 0.3283 | 0.8396 |
| 0.5277 | 53.0 | 4558 | 0.3103 | 0.8446 |
| 0.5102 | 54.0 | 4644 | 0.2936 | 0.8476 |
| 0.4917 | 55.0 | 4730 | 0.2815 | 0.8504 |
| 0.4782 | 56.0 | 4816 | 0.2701 | 0.8523 |
| 0.4623 | 57.0 | 4902 | 0.2640 | 0.8531 |
| 0.4495 | 58.0 | 4988 | 0.2559 | 0.8550 |
| 0.4361 | 59.0 | 5074 | 0.2504 | 0.8558 |
| 0.4236 | 60.0 | 5160 | 0.2453 | 0.8563 |
| 0.4131 | 61.0 | 5246 | 0.2402 | 0.8568 |
| 0.4026 | 62.0 | 5332 | 0.2388 | 0.8569 |
| 0.3925 | 63.0 | 5418 | 0.2366 | 0.8577 |
| 0.3831 | 64.0 | 5504 | 0.2351 | 0.8580 |
| 0.3783 | 65.0 | 5590 | 0.2314 | 0.8583 |
| 0.3692 | 66.0 | 5676 | 0.2297 | 0.8583 |
| 0.3623 | 67.0 | 5762 | 0.2287 | 0.8586 |
| 0.3553 | 68.0 | 5848 | 0.2274 | 0.8584 |
| 0.3497 | 69.0 | 5934 | 0.2256 | 0.8593 |
| 0.3426 | 70.0 | 6020 | 0.2263 | 0.8590 |
| 0.3383 | 71.0 | 6106 | 0.2245 | 0.8591 |
| 0.3337 | 72.0 | 6192 | 0.2226 | 0.8592 |
| 0.3291 | 73.0 | 6278 | 0.2217 | 0.8594 |
| 0.3266 | 74.0 | 6364 | 0.2223 | 0.8595 |
| 0.3211 | 75.0 | 6450 | 0.2229 | 0.8599 |
| 0.3174 | 76.0 | 6536 | 0.2219 | 0.8598 |
| 0.3137 | 77.0 | 6622 | 0.2214 | 0.8596 |
| 0.3105 | 78.0 | 6708 | 0.2200 | 0.8601 |
| 0.3061 | 79.0 | 6794 | 0.2213 | 0.8599 |
| 0.3045 | 80.0 | 6880 | 0.2200 | 0.8597 |
| 0.3029 | 81.0 | 6966 | 0.2210 | 0.8595 |
| 0.2986 | 82.0 | 7052 | 0.2192 | 0.8599 |
| 0.296 | 83.0 | 7138 | 0.2178 | 0.8604 |
| 0.2933 | 84.0 | 7224 | 0.2198 | 0.8599 |
| 0.2918 | 85.0 | 7310 | 0.2188 | 0.8599 |
| 0.2884 | 86.0 | 7396 | 0.2181 | 0.8607 |
| 0.2881 | 87.0 | 7482 | 0.2189 | 0.8606 |
| 0.2842 | 88.0 | 7568 | 0.2168 | 0.8603 |
| 0.2829 | 89.0 | 7654 | 0.2150 | 0.8611 |
| 0.2817 | 90.0 | 7740 | 0.2165 | 0.8609 |
| 0.2797 | 91.0 | 7826 | 0.2170 | 0.8606 |
| 0.2778 | 92.0 | 7912 | 0.2168 | 0.8611 |
| 0.277 | 93.0 | 7998 | 0.2143 | 0.8614 |
| 0.2755 | 94.0 | 8084 | 0.2146 | 0.8611 |
| 0.2733 | 95.0 | 8170 | 0.2151 | 0.8613 |
| 0.271 | 96.0 | 8256 | 0.2139 | 0.8616 |
| 0.2698 | 97.0 | 8342 | 0.2155 | 0.8614 |
| 0.2688 | 98.0 | 8428 | 0.2143 | 0.8610 |
| 0.2675 | 99.0 | 8514 | 0.2135 | 0.8613 |
| 0.2652 | 100.0 | 8600 | 0.2137 | 0.8615 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/random25eof_find_passage_train5000_eval1000_rare"], "metrics": ["accuracy"], "base_model": "gpt2", "model-index": [{"name": "random25eof_find_passage_train5000_eval1000_rare_gpt2_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/random25eof_find_passage_train5000_eval1000_rare", "type": "tyzhu/random25eof_find_passage_train5000_eval1000_rare"}, "metrics": [{"type": "accuracy", "value": 0.861531914893617, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/random25eof_find_passage_train5000_eval1000_rare_gpt2_1e-4 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/random25eof_find_passage_train5000_eval1000_rare",
"base_model:gpt2",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:32:32+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train5000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| random25eof\_find\_passage\_train5000\_eval1000\_rare\_gpt2\_1e-4
=================================================================
This model is a fine-tuned version of gpt2 on the tyzhu/random25eof\_find\_passage\_train5000\_eval1000\_rare dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2137
* Accuracy: 0.8615
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 100.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train5000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
99,
98,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train5000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.1336292177438736,
0.18204835057258606,
-0.0027533103711903095,
0.13055828213691711,
0.11841419339179993,
0.03786597400903702,
0.12170353531837463,
0.15940366685390472,
-0.10614615678787231,
0.08975331485271454,
0.1565653532743454,
0.09219258278608322,
0.05339285358786583,
0.18134690821170807,
-0.03861072659492493,
-0.22422198951244354,
0.015454948879778385,
0.0280140470713377,
-0.01696029119193554,
0.13928082585334778,
0.07640170305967331,
-0.11764872819185257,
0.09197747707366943,
0.005319032818078995,
-0.19308562576770782,
-0.018345220014452934,
-0.008966324850916862,
-0.05421072617173195,
0.11596167087554932,
0.019584661349654198,
0.0797383189201355,
0.024689747020602226,
0.0767950490117073,
-0.1362975835800171,
0.0002789519203361124,
0.0524480827152729,
0.002237248234450817,
0.1057557538151741,
0.06440252810716629,
-0.027128251269459724,
0.09060604125261307,
-0.042746592313051224,
0.029401378706097603,
0.016283035278320312,
-0.13749556243419647,
-0.17826656997203827,
-0.0944032147526741,
0.08299405872821808,
0.02295750565826893,
0.08328435570001602,
-0.016597405076026917,
0.12782493233680725,
-0.04769422113895416,
0.07430414110422134,
0.2740672826766968,
-0.2913320064544678,
-0.06209350377321243,
0.04338393360376358,
0.014583582989871502,
0.05882025510072708,
-0.09288875013589859,
-0.04373404011130333,
0.05926132947206497,
0.031066086143255234,
0.12063945084810257,
0.0008500309195369482,
-0.029977256432175636,
0.015277864411473274,
-0.13899311423301697,
-0.06177833303809166,
0.14652763307094574,
0.03143506869673729,
-0.03883420303463936,
-0.05378948897123337,
-0.07623682916164398,
-0.2026999145746231,
-0.01519895438104868,
0.023948580026626587,
0.022250017151236534,
-0.03100109100341797,
-0.0884408950805664,
0.018683962523937225,
-0.0571133978664875,
-0.07037953287363052,
-0.014197333715856075,
0.0699252113699913,
0.049972277134656906,
0.02035960741341114,
-0.004378501791507006,
0.12648609280586243,
-0.043252523988485336,
-0.15298734605312347,
-0.0008321864297613502,
-0.0007510381983593106,
-0.001829172600992024,
-0.028857428580522537,
-0.038127318024635315,
-0.0025067843962460756,
0.02407226338982582,
0.16443565487861633,
-0.0544029176235199,
0.0485537052154541,
0.00822495948523283,
0.026860808953642845,
-0.06541486084461212,
0.12031710892915726,
-0.09043926745653152,
-0.03650996461510658,
0.021084420382976532,
0.09914398938417435,
0.02980879880487919,
-0.010659947991371155,
-0.09113261848688126,
-0.013127247802913189,
0.12354452162981033,
0.025068476796150208,
-0.028392532840371132,
0.05843192711472511,
-0.04665827378630638,
-0.0316913016140461,
0.04723046347498894,
-0.09427837282419205,
0.014793994836509228,
0.020259253680706024,
-0.11022157967090607,
-0.06264644861221313,
-0.024649210274219513,
-0.013766189105808735,
-0.04228488355875015,
0.07680319249629974,
-0.11774630099534988,
0.0023968247696757317,
-0.07415998727083206,
-0.11461734771728516,
-0.00046684371773153543,
-0.10460952669382095,
-0.01193088386207819,
-0.06950569152832031,
-0.22361890971660614,
-0.0322200246155262,
0.02179102785885334,
-0.07073887437582016,
-0.08347050100564957,
-0.0788312777876854,
-0.10021539777517319,
0.03448139503598213,
-0.018766658380627632,
0.07945948094129562,
-0.06713549047708511,
0.1023695096373558,
0.03551730141043663,
0.05703150853514671,
0.013751978985965252,
0.04056807979941368,
-0.08979126811027527,
0.045868322253227234,
-0.15382973849773407,
0.08127433061599731,
-0.049681421369314194,
0.03313954547047615,
-0.09367424994707108,
-0.11549986898899078,
0.04135308042168617,
-0.035673774778842926,
0.10393735766410828,
0.13975563645362854,
-0.15407003462314606,
-0.06505374610424042,
0.1921670138835907,
-0.06427577883005142,
-0.10742563754320145,
0.11999184638261795,
-0.061780501157045364,
-0.021961189806461334,
0.05493351072072983,
0.18083591759204865,
0.0633171796798706,
-0.04103080928325653,
-0.04205530509352684,
-0.038038384169340134,
0.05477026104927063,
-0.044256582856178284,
0.08488865941762924,
0.01164997834712267,
0.01389987114816904,
0.0165390744805336,
-0.028332853689789772,
0.045447345823049545,
-0.11085488647222519,
-0.08688872307538986,
-0.03798261657357216,
-0.10061494261026382,
0.06278413534164429,
0.045443613082170486,
0.07447481900453568,
-0.10212264955043793,
-0.09241943061351776,
0.01490932609885931,
0.10654108226299286,
-0.08157234638929367,
0.0021433555521070957,
-0.07068178802728653,
0.1472618728876114,
-0.07183589041233063,
-0.018300101161003113,
-0.1629667580127716,
-0.014448187313973904,
0.04628530889749527,
0.02578420378267765,
-0.010887695476412773,
-0.025792928412556648,
0.06992572546005249,
0.08881376683712006,
-0.05721301585435867,
-0.05879494547843933,
-0.03356069326400757,
-0.026853924617171288,
-0.11137410998344421,
-0.19222629070281982,
-0.05164787545800209,
-0.003956276457756758,
0.12903393805027008,
-0.20491260290145874,
0.03575459122657776,
0.0027984711341559887,
0.1168937161564827,
0.0049304114654660225,
-0.05433923006057739,
-0.007399602793157101,
0.0518256276845932,
-0.06071621552109718,
-0.08504806458950043,
0.055404458194971085,
0.017938463017344475,
-0.0652126595377922,
-0.017338180914521217,
-0.11666664481163025,
0.12272439897060394,
0.11393310874700546,
-0.004387798253446817,
-0.10974530130624771,
0.010690607130527496,
-0.07328547537326813,
-0.024614153429865837,
-0.04529572278261185,
0.0005297718453221023,
0.1394856870174408,
-0.0038018329069018364,
0.15086062252521515,
-0.09832563251256943,
-0.055085767060518265,
0.04019096493721008,
0.012036958709359169,
0.022848457098007202,
0.13744030892848969,
0.057532086968421936,
-0.05352405831217766,
0.15703549981117249,
0.03290090337395668,
-0.055638637393713,
0.11075876653194427,
-0.05252843722701073,
-0.08151184022426605,
-0.03923993930220604,
0.01634586974978447,
0.021462228149175644,
0.1066572368144989,
-0.08647972345352173,
-0.016235901042819023,
0.031962595880031586,
0.020711440593004227,
0.012966594658792019,
-0.1798488199710846,
-0.0314096137881279,
0.023776568472385406,
-0.06212014704942703,
-0.02175023965537548,
-0.021459689363837242,
0.003809861373156309,
0.11440667510032654,
0.0023638675920665264,
-0.07630620896816254,
0.03043665550649166,
0.010439349338412285,
-0.07745597511529922,
0.20227935910224915,
-0.07861483097076416,
-0.12343285232782364,
-0.11352986842393875,
-0.02840385213494301,
-0.06386080384254456,
0.01627766340970993,
0.04329059645533562,
-0.06618239730596542,
-0.012513513676822186,
-0.09944400191307068,
-0.00032345455838367343,
-0.03469851613044739,
0.029081707820296288,
0.02638467215001583,
-0.028382353484630585,
0.06328070163726807,
-0.10882934182882309,
0.001986093819141388,
-0.024145618081092834,
-0.03586354851722717,
0.06017881631851196,
0.016949208453297615,
0.0896858423948288,
0.12167145311832428,
-0.017226601019501686,
0.03204967454075813,
-0.03023705445230007,
0.26666054129600525,
-0.03762531280517578,
-0.02741716057062149,
0.09839186072349548,
0.02797950990498066,
0.07490714639425278,
0.12044449895620346,
0.04436291754245758,
-0.08309665322303772,
-0.0021846196614205837,
0.018894672393798828,
-0.0262749046087265,
-0.22762195765972137,
-0.029266033321619034,
-0.039583440870046616,
0.026946621015667915,
0.12140892446041107,
0.02887764759361744,
0.00757177546620369,
0.0826510414481163,
-0.005765274632722139,
0.08987399935722351,
-0.0386984758079052,
0.08081334829330444,
0.06947622448205948,
0.06347361952066422,
0.12255614995956421,
-0.01040790043771267,
-0.0420270636677742,
0.05218016728758812,
-0.040883615612983704,
0.2297351062297821,
-0.07114827632904053,
0.18053092062473297,
0.015209965407848358,
0.18706576526165009,
0.01869952119886875,
0.07604477554559708,
-0.019532393664121628,
0.007637714967131615,
-0.003519527381286025,
-0.05276254191994667,
-0.039616167545318604,
0.013603723607957363,
-0.035011082887649536,
0.07398233562707901,
-0.1100483313202858,
0.0068199909292161465,
0.045935407280921936,
0.24559460580348969,
0.07539017498493195,
-0.37158268690109253,
-0.08913995325565338,
-0.010972368530929089,
0.0024208950344473124,
-0.04821274057030678,
0.015675105154514313,
0.11017388850450516,
-0.10071784257888794,
0.034104254096746445,
-0.0733424499630928,
0.09378840774297714,
-0.06745434552431107,
0.016324538737535477,
0.038439758121967316,
0.09392978996038437,
-0.024067502468824387,
0.06731484085321426,
-0.24923226237297058,
0.23429246246814728,
0.014188860543072224,
0.07365734130144119,
-0.06350921839475632,
0.0068480330519378185,
0.02255157381296158,
0.004130522720515728,
0.07740770280361176,
0.002983215032145381,
-0.01920093037188053,
-0.19371332228183746,
-0.1195947602391243,
0.004678059834986925,
0.07043691724538803,
-0.04138464108109474,
0.11574655771255493,
-0.000979066826403141,
-0.0004708777123596519,
0.027699237689375877,
-0.00679726991802454,
-0.06356276571750641,
-0.0848563089966774,
0.017854100093245506,
0.019862789660692215,
0.009948528371751308,
-0.062110867351293564,
-0.1146523579955101,
-0.0795706957578659,
0.15765774250030518,
-0.04417429491877556,
-0.07040603458881378,
-0.10939563065767288,
0.11124422401189804,
0.12986570596694946,
-0.0824013352394104,
0.024807646870613098,
0.009411796927452087,
0.0942450612783432,
0.017309337854385376,
-0.06566274911165237,
0.08725018054246902,
-0.04384036362171173,
-0.20980143547058105,
-0.06822767108678818,
0.12154138088226318,
0.04366142302751541,
0.0647830218076706,
-0.026887930929660797,
0.04733487218618393,
-0.030425094068050385,
-0.08596563339233398,
0.04575110599398613,
-0.006476962007582188,
0.09680623561143875,
0.036471132189035416,
-0.017168225720524788,
0.04012769088149071,
-0.05499395355582237,
-0.025646308436989784,
0.15096957981586456,
0.27895304560661316,
-0.09434663504362106,
0.04073038697242737,
0.02598746493458748,
-0.06915140897035599,
-0.15119683742523193,
0.026852279901504517,
0.07953932136297226,
0.026424817740917206,
-0.016911396756768227,
-0.2138221710920334,
0.05649532005190849,
0.11424944549798965,
-0.012400360777974129,
0.11829297989606857,
-0.3454560935497284,
-0.12110309302806854,
0.06863082945346832,
0.10071508586406708,
0.11072371900081635,
-0.1534772664308548,
-0.05792245641350746,
-0.016390584409236908,
-0.14263534545898438,
0.09512349218130112,
-0.04929814115166664,
0.1241626888513565,
-0.06455109268426895,
0.06973791122436523,
0.019986173138022423,
-0.06882163882255554,
0.1297566294670105,
0.024122927337884903,
0.07737808674573898,
-0.052673161029815674,
-0.012217674404382706,
0.09748446196317673,
-0.06328757852315903,
0.032800860702991486,
-0.09280048310756683,
0.07351312041282654,
-0.1367015391588211,
-0.01951284147799015,
-0.07584924250841141,
0.024123141542077065,
-0.031250469386577606,
-0.04961194470524788,
-0.05511409044265747,
0.033651262521743774,
0.07016213983297348,
-0.009916897863149643,
0.09871652722358704,
0.049131542444229126,
0.1476573348045349,
0.09616473317146301,
0.03669896349310875,
-0.04052915796637535,
-0.07674208283424377,
-0.001752662705257535,
-0.005799784790724516,
0.048694223165512085,
-0.12593168020248413,
0.01035232562571764,
0.16527478396892548,
0.040959205478429794,
0.13191495835781097,
0.08282490074634552,
-0.0644608736038208,
0.03208620846271515,
0.041700780391693115,
-0.1785416454076767,
-0.0782703161239624,
-0.016517730429768562,
-0.03986407816410065,
-0.12730109691619873,
0.019842246547341347,
0.09415966272354126,
-0.07811248302459717,
-0.03651631623506546,
-0.009238934144377708,
0.023439975455403328,
-0.003068127203732729,
0.22500883042812347,
0.03699189051985741,
0.06494012475013733,
-0.11894284188747406,
0.07182517647743225,
0.06304598599672318,
-0.0466591939330101,
0.042669542133808136,
0.07587527483701706,
-0.09370622783899307,
-0.004953207913786173,
0.08169808983802795,
0.16770605742931366,
-0.06566052883863449,
-0.013812588527798653,
-0.15099748969078064,
-0.08802149444818497,
0.09839259088039398,
0.1231464296579361,
0.07760537415742874,
0.04478360712528229,
-0.014007024466991425,
-0.020650191232562065,
-0.1169118583202362,
0.09870488941669464,
0.08850375562906265,
0.08191461861133575,
-0.12531985342502594,
0.15435223281383514,
-0.022454796358942986,
0.01578744500875473,
-0.011067657731473446,
0.027726370841264725,
-0.12460153549909592,
-0.008039877749979496,
-0.12598976492881775,
0.033298324793577194,
-0.07224797457456589,
-0.008794608525931835,
-0.022910788655281067,
-0.026710184291005135,
-0.05253845825791359,
0.0251313466578722,
-0.10126056522130966,
-0.05229740962386131,
0.0040963818319141865,
0.03348424285650253,
-0.12755034863948822,
-0.013548926450312138,
0.005215268116444349,
-0.08278349786996841,
0.10252290219068527,
0.07334442436695099,
0.012550964020192623,
0.008268674835562706,
-0.05987563729286194,
-0.005919439718127251,
0.004921391140669584,
0.0004448149411473423,
0.05477796867489815,
-0.10204508155584335,
0.018972760066390038,
-0.016437912359833717,
-0.0006241641822271049,
0.027675004675984383,
0.06887727975845337,
-0.1349257379770279,
-0.018073633313179016,
-0.00485503114759922,
-0.019078388810157776,
-0.078313447535038,
0.06233273074030876,
0.10009855777025223,
0.007173351012170315,
0.1608196496963501,
-0.0777750089764595,
0.03761730343103409,
-0.22278741002082825,
-0.01458072755485773,
0.0016678038518875837,
-0.10860761255025864,
-0.09797868132591248,
-0.008072488009929657,
0.08973512053489685,
-0.058095112442970276,
0.13058999180793762,
-0.012435141019523144,
-0.018475351855158806,
0.010138683021068573,
-0.01828903891146183,
0.03553352504968643,
0.02238578163087368,
0.20835089683532715,
0.03785381093621254,
-0.0583803616464138,
0.055370282381772995,
0.0347091481089592,
0.09403035789728165,
0.13308152556419373,
0.16056770086288452,
0.08767382800579071,
0.037605270743370056,
0.07507491856813431,
0.033213671296834946,
-0.09174932539463043,
-0.12260398268699646,
0.06164492294192314,
-0.05349814146757126,
0.11644149571657181,
0.0009355240617878735,
0.20967911183834076,
0.08703139424324036,
-0.15071432292461395,
0.045687925070524216,
-0.05533226579427719,
-0.09717021882534027,
-0.09774673730134964,
-0.08368837833404541,
-0.0866205096244812,
-0.1489294022321701,
0.019819792360067368,
-0.13670426607131958,
0.032391250133514404,
0.10804346948862076,
0.023816734552383423,
-0.00549320038408041,
0.09030047804117203,
0.07505864650011063,
0.011389469727873802,
0.05602554231882095,
0.014420666731894016,
-0.02125369943678379,
-0.041766729205846786,
-0.08982833474874496,
0.0416281595826149,
-0.029605792835354805,
0.06391198188066483,
-0.03304964676499367,
0.0061821057461202145,
0.045501552522182465,
0.0010525209363549948,
-0.08932750672101974,
0.017175253480672836,
-0.0023116415832191706,
0.061794329434633255,
0.05640092492103577,
0.0164005346596241,
0.015575798228383064,
-0.02771713025867939,
0.20478366315364838,
-0.0580834299325943,
-0.02152647264301777,
-0.11783592402935028,
0.2233978807926178,
0.029757648706436157,
-0.038725465536117554,
0.06174558028578758,
-0.09331919252872467,
0.0038522882387042046,
0.18883873522281647,
0.20121866464614868,
-0.04905805364251137,
-0.03387447074055672,
0.014083133079111576,
-0.025548802688717842,
0.011031740345060825,
0.08499816060066223,
0.0970633402466774,
0.029814166948199272,
-0.09471357613801956,
-0.024008706212043762,
-0.060256775468587875,
-0.01906760409474373,
-0.033724308013916016,
0.0758647695183754,
0.014987916685640812,
0.0014189573703333735,
-0.05007738992571831,
0.030935922637581825,
-0.08047188818454742,
-0.07341212034225464,
0.043578848242759705,
-0.19993413984775543,
-0.18046042323112488,
-0.013693241402506828,
0.03076401725411415,
0.026578083634376526,
0.05583915859460831,
-0.008490527980029583,
0.02171969972550869,
0.055486857891082764,
-0.029283087700605392,
-0.10729391872882843,
-0.10698341578245163,
0.07301166653633118,
-0.08929487317800522,
0.1947677880525589,
-0.0396505668759346,
0.06351225823163986,
0.13371841609477997,
0.04389093816280365,
-0.13152794539928436,
0.03245365247130394,
0.06284182518720627,
-0.05611056089401245,
0.02047945000231266,
0.12909527122974396,
-0.019056376069784164,
0.06854679435491562,
0.034979432821273804,
-0.05501890182495117,
-0.02129671350121498,
-0.012574421241879463,
-0.0038832647260278463,
-0.07050551474094391,
-0.05287889391183853,
-0.031448766589164734,
0.14110751450061798,
0.20109672844409943,
-0.06592248380184174,
-0.003942842595279217,
-0.061687979847192764,
0.001510713598690927,
0.054522741585969925,
0.04124332591891289,
-0.029889291152358055,
-0.2760632336139679,
0.007095553446561098,
0.08405911177396774,
0.015405670739710331,
-0.24431291222572327,
-0.06823933869600296,
-0.0022151065059006214,
-0.06109064444899559,
-0.08662071824073792,
0.11315171420574188,
0.05348348990082741,
0.07037048786878586,
-0.05368751659989357,
0.011596119962632656,
-0.08531462401151657,
0.1506786197423935,
-0.13269008696079254,
-0.10435488075017929
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# random25eof_find_passage_train100000_eval1000_rare_gpt2_1e-4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the tyzhu/random25eof_find_passage_train100000_eval1000_rare dataset.
It achieves the following results on the evaluation set:
- Loss: 6.5510
- Accuracy: 0.0182
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.1793 | 1.0 | 1571 | 2.8883 | 0.3158 |
| 3.11 | 2.0 | 3142 | 2.8865 | 0.3154 |
| 5.5348 | 3.0 | 4713 | 6.1317 | 0.0109 |
| 5.2497 | 4.0 | 6284 | 4.6489 | 0.0762 |
| 5.142 | 5.0 | 7855 | 5.4396 | 0.0213 |
| 5.4095 | 6.0 | 9426 | 5.5736 | 0.0213 |
| 5.5829 | 7.0 | 10997 | 5.8924 | 0.0213 |
| 5.7278 | 8.0 | 12568 | 5.8697 | 0.0213 |
| 5.4592 | 9.0 | 14139 | 5.0131 | 0.0213 |
| 5.1587 | 10.0 | 15710 | 4.9544 | 0.0213 |
| 5.0384 | 11.0 | 17281 | 5.1836 | 0.0680 |
| 4.898 | 12.0 | 18852 | 5.8572 | 0.0191 |
| 18.2396 | 13.0 | 20423 | 20.2482 | 0.0213 |
| 10.6256 | 14.0 | 21994 | 7.5909 | 0.0081 |
| 9.6053 | 15.0 | 23565 | 8.0450 | 0.0093 |
| 8.2451 | 16.0 | 25136 | 8.3533 | 0.0089 |
| 9.9174 | 17.0 | 26707 | 9.0433 | 0.0081 |
| 8.1073 | 18.0 | 28278 | 4.9106 | 0.0474 |
| 8.9419 | 19.0 | 29849 | 12.2422 | 0.0213 |
| 7.1818 | 20.0 | 31420 | 4.6110 | 0.0688 |
| 4.9119 | 21.0 | 32991 | 4.3465 | 0.0698 |
| 4.6421 | 22.0 | 34562 | 4.3478 | 0.0699 |
| 4.6135 | 23.0 | 36133 | 4.2387 | 0.0911 |
| 4.5608 | 24.0 | 37704 | 4.2641 | 0.0801 |
| 5.3436 | 25.0 | 39275 | 5.2223 | 0.0143 |
| 5.7516 | 26.0 | 40846 | 4.6906 | 0.0593 |
| 5.7152 | 27.0 | 42417 | 6.9208 | 0.0092 |
| 5.9756 | 28.0 | 43988 | 4.6900 | 0.0486 |
| 4.7482 | 29.0 | 45559 | 4.6581 | 0.0699 |
| 4.7309 | 30.0 | 47130 | 4.6590 | 0.0699 |
| 4.7248 | 31.0 | 48701 | 4.6665 | 0.0486 |
| 4.7521 | 32.0 | 50272 | 4.6829 | 0.0486 |
| 4.7483 | 33.0 | 51843 | 4.6769 | 0.0486 |
| 5.3519 | 34.0 | 53414 | 6.8476 | 0.0001 |
| 5.3354 | 35.0 | 54985 | 4.7741 | 0.0486 |
| 5.082 | 36.0 | 56556 | 7.3852 | 0.0001 |
| 7.889 | 37.0 | 58127 | 6.7698 | 0.0086 |
| 5.8798 | 38.0 | 59698 | 4.7111 | 0.0490 |
| 4.8743 | 39.0 | 61269 | 4.7041 | 0.0490 |
| 4.8162 | 40.0 | 62840 | 4.7026 | 0.0486 |
| 4.8256 | 41.0 | 64411 | 4.7210 | 0.0487 |
| 4.8315 | 42.0 | 65982 | 4.7242 | 0.0487 |
| 4.8213 | 43.0 | 67553 | 4.6986 | 0.0486 |
| 4.8361 | 44.0 | 69124 | 4.8042 | 0.0461 |
| 5.3172 | 45.0 | 70695 | 5.6720 | 0.0089 |
| 5.7134 | 46.0 | 72266 | 5.6720 | 0.0089 |
| 5.7121 | 47.0 | 73837 | 5.7657 | 0.0107 |
| 5.5466 | 48.0 | 75408 | 5.3030 | 0.0213 |
| 5.1238 | 49.0 | 76979 | 5.0950 | 0.0337 |
| 5.2237 | 50.0 | 78550 | 5.1819 | 0.0213 |
| 5.1471 | 51.0 | 80121 | 5.1693 | 0.0060 |
| 5.3024 | 52.0 | 81692 | 6.2183 | 0.0178 |
| 5.959 | 53.0 | 83263 | 6.5510 | 0.0182 |
| 5.9614 | 54.0 | 84834 | 6.5510 | 0.0182 |
| 5.9591 | 55.0 | 86405 | 6.5510 | 0.0182 |
| 5.9598 | 56.0 | 87976 | 6.5510 | 0.0182 |
| 5.9609 | 57.0 | 89547 | 6.5510 | 0.0182 |
| 5.9607 | 58.0 | 91118 | 6.5510 | 0.0182 |
| 5.9605 | 59.0 | 92689 | 6.5510 | 0.0182 |
| 5.9598 | 60.0 | 94260 | 6.5510 | 0.0182 |
| 5.9607 | 61.0 | 95831 | 6.5510 | 0.0182 |
| 5.962 | 62.0 | 97402 | 6.5510 | 0.0182 |
| 5.9592 | 63.0 | 98973 | 6.5510 | 0.0182 |
| 5.9589 | 64.0 | 100544 | 6.5510 | 0.0182 |
| 5.9609 | 65.0 | 102115 | 6.5510 | 0.0182 |
| 5.9597 | 66.0 | 103686 | 6.5510 | 0.0182 |
| 5.9579 | 67.0 | 105257 | 6.5510 | 0.0182 |
| 5.9598 | 68.0 | 106828 | 6.5510 | 0.0182 |
| 5.9597 | 69.0 | 108399 | 6.5510 | 0.0182 |
| 5.9614 | 70.0 | 109970 | 6.5510 | 0.0182 |
| 5.9612 | 71.0 | 111541 | 6.5510 | 0.0182 |
| 5.9589 | 72.0 | 113112 | 6.5510 | 0.0182 |
| 5.9594 | 73.0 | 114683 | 6.5510 | 0.0182 |
| 5.9586 | 74.0 | 116254 | 6.5510 | 0.0182 |
| 5.9611 | 75.0 | 117825 | 6.5510 | 0.0182 |
| 5.9603 | 76.0 | 119396 | 6.5510 | 0.0182 |
| 5.9603 | 77.0 | 120967 | 6.5510 | 0.0182 |
| 5.9604 | 78.0 | 122538 | 6.5510 | 0.0182 |
| 5.961 | 79.0 | 124109 | 6.5510 | 0.0182 |
| 5.959 | 80.0 | 125680 | 6.5510 | 0.0182 |
| 5.959 | 81.0 | 127251 | 6.5510 | 0.0182 |
| 5.96 | 82.0 | 128822 | 6.5510 | 0.0182 |
| 5.9589 | 83.0 | 130393 | 6.5510 | 0.0182 |
| 5.9604 | 84.0 | 131964 | 6.5510 | 0.0182 |
| 5.9599 | 85.0 | 133535 | 6.5510 | 0.0182 |
| 5.959 | 86.0 | 135106 | 6.5510 | 0.0182 |
| 5.9599 | 87.0 | 136677 | 6.5510 | 0.0182 |
| 5.9616 | 88.0 | 138248 | 6.5510 | 0.0182 |
| 5.9598 | 89.0 | 139819 | 6.5510 | 0.0182 |
| 5.9613 | 90.0 | 141390 | 6.5510 | 0.0182 |
| 5.9613 | 91.0 | 142961 | 6.5510 | 0.0182 |
| 5.9608 | 92.0 | 144532 | 6.5510 | 0.0182 |
| 5.9581 | 93.0 | 146103 | 6.5510 | 0.0182 |
| 5.9607 | 94.0 | 147674 | 6.5510 | 0.0182 |
| 5.9613 | 95.0 | 149245 | 6.5510 | 0.0182 |
| 5.9603 | 96.0 | 150816 | 6.5510 | 0.0182 |
| 5.9595 | 97.0 | 152387 | 6.5510 | 0.0182 |
| 5.961 | 98.0 | 153958 | 6.5510 | 0.0182 |
| 5.9578 | 99.0 | 155529 | 6.5510 | 0.0182 |
| 5.9601 | 100.0 | 157100 | 6.5510 | 0.0182 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/random25eof_find_passage_train100000_eval1000_rare"], "metrics": ["accuracy"], "base_model": "gpt2", "model-index": [{"name": "random25eof_find_passage_train100000_eval1000_rare_gpt2_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/random25eof_find_passage_train100000_eval1000_rare", "type": "tyzhu/random25eof_find_passage_train100000_eval1000_rare"}, "metrics": [{"type": "accuracy", "value": 0.018212765957446808, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/random25eof_find_passage_train100000_eval1000_rare_gpt2_1e-4 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/random25eof_find_passage_train100000_eval1000_rare",
"base_model:gpt2",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:32:33+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train100000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| random25eof\_find\_passage\_train100000\_eval1000\_rare\_gpt2\_1e-4
===================================================================
This model is a fine-tuned version of gpt2 on the tyzhu/random25eof\_find\_passage\_train100000\_eval1000\_rare dataset.
It achieves the following results on the evaluation set:
* Loss: 6.5510
* Accuracy: 0.0182
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 100.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train100000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
100,
98,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train100000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.13503578305244446,
0.173614963889122,
-0.002906620968133211,
0.12718772888183594,
0.1274844855070114,
0.03987348824739456,
0.11818910390138626,
0.16249899566173553,
-0.0963704064488411,
0.08600426465272903,
0.15096540749073029,
0.098212830722332,
0.05562806501984596,
0.16963504254817963,
-0.03551382198929787,
-0.22636358439922333,
0.014957527630031109,
0.02718714065849781,
-0.014612836763262749,
0.14432044327259064,
0.07346000522375107,
-0.11622476577758789,
0.0898846909403801,
0.003924031741917133,
-0.18124976754188538,
-0.023064570501446724,
-0.007874610833823681,
-0.05250623822212219,
0.11959546059370041,
0.0191073976457119,
0.08426757156848907,
0.027699600905179977,
0.07630058377981186,
-0.14962854981422424,
0.0015655229799449444,
0.053166937083005905,
0.001430536387488246,
0.10289579629898071,
0.06872997432947159,
-0.031335558742284775,
0.09097132831811905,
-0.04870549589395523,
0.024143991991877556,
0.016156209632754326,
-0.13486279547214508,
-0.17866557836532593,
-0.09375696629285812,
0.08162908256053925,
0.018792688846588135,
0.09137001633644104,
-0.014057413674890995,
0.11930854618549347,
-0.05340786650776863,
0.07598106563091278,
0.27747803926467896,
-0.28532886505126953,
-0.058111224323511124,
0.03706125542521477,
0.016038062050938606,
0.06227150559425354,
-0.09257163852453232,
-0.04731715843081474,
0.05157594382762909,
0.030893905088305473,
0.11490783095359802,
0.0017311264527961612,
-0.035877346992492676,
0.015589444898068905,
-0.1420970857143402,
-0.06637077033519745,
0.13584782183170319,
0.03190215304493904,
-0.03657776862382889,
-0.04777541384100914,
-0.07698892056941986,
-0.20004212856292725,
-0.015743793919682503,
0.0282772034406662,
0.019052105024456978,
-0.03109589032828808,
-0.08224465698003769,
0.01597205363214016,
-0.06357191503047943,
-0.07107318937778473,
-0.018758470192551613,
0.06871362775564194,
0.04802289232611656,
0.020409759134054184,
-0.0013306215405464172,
0.1290060579776764,
-0.0312618613243103,
-0.15128584206104279,
0.0005368125275708735,
0.002123008482158184,
-0.004329166375100613,
-0.02281494066119194,
-0.041779518127441406,
-0.00023985210282262415,
0.024057045578956604,
0.15940648317337036,
-0.042538098990917206,
0.04336002096533775,
0.012568593956530094,
0.026917608454823494,
-0.07083109766244888,
0.1213906779885292,
-0.09757161885499954,
-0.041126467287540436,
0.01993383653461933,
0.10237956047058105,
0.028263840824365616,
-0.011705167591571808,
-0.09041675925254822,
-0.0205006655305624,
0.12985464930534363,
0.026424558833241463,
-0.017026003450155258,
0.05914553254842758,
-0.04876938462257385,
-0.03610425814986229,
0.05069791153073311,
-0.09594246000051498,
0.00707347271963954,
0.0287867933511734,
-0.1128101497888565,
-0.05459630861878395,
-0.011981547810137272,
-0.018628349527716637,
-0.04493844136595726,
0.07979388535022736,
-0.11610673367977142,
0.0065888469107449055,
-0.06995273381471634,
-0.11965369433164597,
0.004961450584232807,
-0.1012822613120079,
-0.01270283292979002,
-0.07090254127979279,
-0.22055356204509735,
-0.03420679271221161,
0.018563341349363327,
-0.06583666801452637,
-0.08055945485830307,
-0.07895155251026154,
-0.10269699990749359,
0.03425123542547226,
-0.022238921374082565,
0.07974862307310104,
-0.06913337856531143,
0.11085094511508942,
0.0314885750412941,
0.05270063132047653,
0.019691312685608864,
0.04750288650393486,
-0.09006541222333908,
0.04277312383055687,
-0.1398204118013382,
0.08525644987821579,
-0.054979898035526276,
0.028349218890070915,
-0.0951492115855217,
-0.11992280185222626,
0.04081135243177414,
-0.035371508449316025,
0.10347389429807663,
0.14465712010860443,
-0.14562520384788513,
-0.06881893426179886,
0.1888085901737213,
-0.06595665961503983,
-0.10435939580202103,
0.12212435901165009,
-0.059146661311388016,
-0.025179391726851463,
0.05192648991942406,
0.1728271245956421,
0.07372761517763138,
-0.047484397888183594,
-0.039738114923238754,
-0.025754185393452644,
0.05638707056641579,
-0.04889291152358055,
0.09039800614118576,
0.008786852471530437,
0.015063137747347355,
0.015441226772964,
-0.04281311854720116,
0.05519697815179825,
-0.11489880830049515,
-0.08865927159786224,
-0.033692292869091034,
-0.09690017998218536,
0.07060132175683975,
0.05074126645922661,
0.07051688432693481,
-0.09320484101772308,
-0.09468811750411987,
0.024483628571033478,
0.11087539047002792,
-0.08556296676397324,
0.003007598454132676,
-0.06804610788822174,
0.14585468173027039,
-0.07586278766393661,
-0.022344186902046204,
-0.16737976670265198,
-0.024657128378748894,
0.03970348834991455,
0.02078164368867874,
-0.010541224852204323,
-0.02032126858830452,
0.06967229396104813,
0.0865473598241806,
-0.053334131836891174,
-0.06122977286577225,
-0.03687293455004692,
-0.026951860636472702,
-0.11004665493965149,
-0.18885289132595062,
-0.0614330992102623,
-0.0021222897339612246,
0.1433439552783966,
-0.20165576040744781,
0.03446319326758385,
0.0021012581419199705,
0.1085788756608963,
0.0020987021271139383,
-0.051551222801208496,
-0.006254345178604126,
0.057297226041555405,
-0.05629860237240791,
-0.08035667985677719,
0.06309064477682114,
0.015713324770331383,
-0.06776564568281174,
-0.011786009185016155,
-0.11791939288377762,
0.11546464264392853,
0.11636754870414734,
-0.01953139528632164,
-0.10136859118938446,
0.014096383936703205,
-0.07360484451055527,
-0.029577208682894707,
-0.037609491497278214,
-0.003027913859114051,
0.13456405699253082,
0.0036115392576903105,
0.1504376083612442,
-0.09370507299900055,
-0.04830150678753853,
0.03809883072972298,
0.013350464403629303,
0.023000724613666534,
0.1426357626914978,
0.06140431761741638,
-0.04044652730226517,
0.15394659340381622,
0.029772324487566948,
-0.056354016065597534,
0.10559801757335663,
-0.0495772510766983,
-0.08768583089113235,
-0.03743842616677284,
0.018750470131635666,
0.020868854597210884,
0.09774385392665863,
-0.09886635839939117,
-0.016842668876051903,
0.035965368151664734,
0.01837448962032795,
0.018476804718375206,
-0.183954119682312,
-0.032988958060741425,
0.02579154074192047,
-0.06835849583148956,
-0.020942669361829758,
-0.017004381865262985,
0.007174132391810417,
0.11252936720848083,
0.004019003827124834,
-0.08145485073328018,
0.030019614845514297,
0.002627631416544318,
-0.08079522103071213,
0.20602375268936157,
-0.07826431840658188,
-0.13018162548542023,
-0.12272659689188004,
-0.030122684314846992,
-0.0602630190551281,
0.014635760337114334,
0.042790647596120834,
-0.05709759518504143,
-0.009758244268596172,
-0.09310891479253769,
0.007650682702660561,
-0.031129805371165276,
0.025892920792102814,
0.015095354057848454,
-0.0312487930059433,
0.06225940212607384,
-0.11190903186798096,
0.003100703004747629,
-0.02695377543568611,
-0.044978972524404526,
0.060053884983062744,
0.015203365124762058,
0.09559915214776993,
0.1279037743806839,
-0.011424806900322437,
0.02674991823732853,
-0.02847723290324211,
0.2643381357192993,
-0.03684234619140625,
-0.030575957149267197,
0.11174164712429047,
0.026069365441799164,
0.07675940543413162,
0.11982639878988266,
0.04453909024596214,
-0.07474973797798157,
-0.0059680151753127575,
0.022160574793815613,
-0.023202061653137207,
-0.23220348358154297,
-0.03490694239735603,
-0.04046732932329178,
0.026020942255854607,
0.11336374282836914,
0.02555290423333645,
0.010710702277719975,
0.0803615152835846,
-0.008820242248475552,
0.0779016986489296,
-0.03941253200173378,
0.07427168637514114,
0.08478882908821106,
0.061477940529584885,
0.1241111010313034,
-0.0073166945949196815,
-0.03793637827038765,
0.050459105521440506,
-0.043477121740579605,
0.23325152695178986,
-0.0754266306757927,
0.18699932098388672,
0.01990731991827488,
0.19313013553619385,
0.012335558421909809,
0.0756271556019783,
-0.01918295957148075,
0.012702444568276405,
-0.002403165912255645,
-0.05244143307209015,
-0.050321631133556366,
0.009556284174323082,
-0.034765563905239105,
0.07486742734909058,
-0.11688531935214996,
-0.00007815061690052971,
0.04166748374700546,
0.2417617291212082,
0.07663608342409134,
-0.36520999670028687,
-0.09873494505882263,
-0.014954070560634136,
0.0005376372719183564,
-0.04234812408685684,
0.012096141465008259,
0.10971687734127045,
-0.10622073709964752,
0.02331695519387722,
-0.07760624587535858,
0.09258780628442764,
-0.07383367419242859,
0.01594538241624832,
0.04219402000308037,
0.09077758342027664,
-0.019500574097037315,
0.07318413257598877,
-0.24387043714523315,
0.23967617750167847,
0.009456629864871502,
0.06590960174798965,
-0.06343193352222443,
0.005669387057423592,
0.02799619548022747,
0.005477034021168947,
0.08068548142910004,
0.0026852439623326063,
0.001325851771980524,
-0.2037096917629242,
-0.12281814962625504,
0.0019257260719314218,
0.07133521884679794,
-0.045234791934490204,
0.1182536706328392,
-0.004929713439196348,
-0.0031699424143880606,
0.02943057380616665,
0.006621123757213354,
-0.05278746038675308,
-0.0803532749414444,
0.024328071624040604,
0.01305107306689024,
0.015567073598504066,
-0.06301840394735336,
-0.12141599506139755,
-0.08195997029542923,
0.1507745385169983,
-0.05339599400758743,
-0.07282043993473053,
-0.10791001468896866,
0.11131206899881363,
0.13555189967155457,
-0.0920088067650795,
0.024299312382936478,
0.01026975642889738,
0.0834328904747963,
0.021038085222244263,
-0.07203240692615509,
0.08388927578926086,
-0.04410829022526741,
-0.2102675884962082,
-0.06388919055461884,
0.12484712898731232,
0.0440574549138546,
0.0668615847826004,
-0.03272514417767525,
0.04211140051484108,
-0.03162788972258568,
-0.08678875118494034,
0.03622567653656006,
-0.0002619712904561311,
0.08848800510168076,
0.047207679599523544,
-0.01922612264752388,
0.033165883272886276,
-0.061140455305576324,
-0.017351016402244568,
0.1513339877128601,
0.27329736948013306,
-0.09402454644441605,
0.041764043271541595,
0.025414573028683662,
-0.06774602085351944,
-0.15872150659561157,
0.020101487636566162,
0.08299650251865387,
0.024949364364147186,
-0.015363634563982487,
-0.2128857672214508,
0.059233732521533966,
0.11650843918323517,
-0.01160366553813219,
0.11707616597414017,
-0.3580528795719147,
-0.11896778643131256,
0.06872095167636871,
0.10123589634895325,
0.11287049949169159,
-0.15651115775108337,
-0.06175283342599869,
-0.004464998841285706,
-0.14951421320438385,
0.0990806445479393,
-0.03886071592569351,
0.12706619501113892,
-0.06368016451597214,
0.06958460807800293,
0.02173420414328575,
-0.06892905384302139,
0.13082683086395264,
0.02913098782300949,
0.0713292732834816,
-0.05223209410905838,
-0.01771494373679161,
0.09736122190952301,
-0.056368280202150345,
0.03097572736442089,
-0.08555518090724945,
0.07172807306051254,
-0.14741890132427216,
-0.018530048429965973,
-0.08961738646030426,
0.02711276151239872,
-0.03284564986824989,
-0.048137977719306946,
-0.04596896469593048,
0.03727872297167778,
0.07419230788946152,
-0.0042091733776032925,
0.09860144555568695,
0.04183119535446167,
0.14615343511104584,
0.09838774055242538,
0.03334513306617737,
-0.034326087683439255,
-0.08446009457111359,
-0.011008214205503464,
-0.0055305808782577515,
0.04663006588816643,
-0.1201397180557251,
0.007822442799806595,
0.1673501580953598,
0.04360470548272133,
0.13494323194026947,
0.08128342777490616,
-0.06705628335475922,
0.031611427664756775,
0.04044311121106148,
-0.17688724398612976,
-0.07488464564085007,
-0.02112744003534317,
-0.054967496544122696,
-0.13004806637763977,
0.015914112329483032,
0.09833183884620667,
-0.0744495764374733,
-0.0342470183968544,
-0.010702893137931824,
0.024283401668071747,
-0.0036068607587367296,
0.2260550856590271,
0.04396796599030495,
0.06584390252828598,
-0.11869511008262634,
0.06774208694696426,
0.06626773625612259,
-0.05711161717772484,
0.03188152611255646,
0.07877236604690552,
-0.09305982291698456,
-0.009446506388485432,
0.07236085832118988,
0.15156278014183044,
-0.07389369606971741,
-0.011760363355278969,
-0.14651335775852203,
-0.0838756337761879,
0.09604102373123169,
0.12727105617523193,
0.08205386996269226,
0.050527993589639664,
-0.013721965253353119,
-0.02221233770251274,
-0.1142793521285057,
0.10177997499704361,
0.09081201255321503,
0.0745730996131897,
-0.12184170633554459,
0.16929464042186737,
-0.023003553971648216,
0.025285447016358376,
-0.010521934367716312,
0.025055106729269028,
-0.11426009982824326,
-0.008653264492750168,
-0.13200552761554718,
0.03673935681581497,
-0.07240475714206696,
-0.007110919803380966,
-0.022918108850717545,
-0.032006919384002686,
-0.049770697951316833,
0.024331463500857353,
-0.10163363069295883,
-0.05511084198951721,
0.0015278421342372894,
0.03582129627466202,
-0.13265694677829742,
-0.020303860306739807,
0.007276046089828014,
-0.08357656002044678,
0.10529046505689621,
0.0812053233385086,
0.017307331785559654,
0.012786787934601307,
-0.06520514190196991,
-0.010321587324142456,
0.00423767464235425,
0.005830044858157635,
0.05102279409766197,
-0.09749171137809753,
0.02258864790201187,
-0.018771907314658165,
-0.006439820397645235,
0.025772154331207275,
0.07119743525981903,
-0.13942714035511017,
-0.019975509494543076,
-0.005358271300792694,
-0.01404380053281784,
-0.07988271117210388,
0.06013552471995354,
0.09341172873973846,
0.010028003714978695,
0.15938876569271088,
-0.07861342281103134,
0.04858317971229553,
-0.22856710851192474,
-0.015215630643069744,
-0.004613425582647324,
-0.10446927696466446,
-0.09826410561800003,
-0.012483850121498108,
0.09238612651824951,
-0.05582829564809799,
0.11846544593572617,
-0.018859494477510452,
-0.0029714915435761213,
0.006326789502054453,
-0.015040628612041473,
0.04418374225497246,
0.019687633961439133,
0.20734567940235138,
0.04223864525556564,
-0.05594317615032196,
0.05798409506678581,
0.03370096534490585,
0.08619140088558197,
0.1297958642244339,
0.16457349061965942,
0.09428481757640839,
0.04079306870698929,
0.07464897632598877,
0.03870787099003792,
-0.0918421745300293,
-0.12408691644668579,
0.04756830260157585,
-0.053279757499694824,
0.112648606300354,
0.0016724137822166085,
0.21460527181625366,
0.08147991448640823,
-0.15361854434013367,
0.04965830221772194,
-0.05216752737760544,
-0.09566957503557205,
-0.09671060740947723,
-0.08233533054590225,
-0.08164256066083908,
-0.14535225927829742,
0.01808924414217472,
-0.13718535006046295,
0.02888174168765545,
0.1180807426571846,
0.022353095933794975,
-0.008509927429258823,
0.09159518778324127,
0.07203561067581177,
0.003725666319951415,
0.05580105632543564,
0.014476748183369637,
-0.016538599506020546,
-0.0434233583509922,
-0.09186475723981857,
0.046697717159986496,
-0.024581661447882652,
0.06215060502290726,
-0.034142881631851196,
0.007952754385769367,
0.048774365335702896,
-0.005202006082981825,
-0.09760542958974838,
0.015378409065306187,
0.0007849382236599922,
0.06658179312944412,
0.06681209802627563,
0.01680990494787693,
0.02010180614888668,
-0.027611812576651573,
0.21079879999160767,
-0.057241324335336685,
-0.026399752125144005,
-0.11176072806119919,
0.22746169567108154,
0.031160645186901093,
-0.038562431931495667,
0.06058301031589508,
-0.09340349584817886,
0.0032815441954880953,
0.19708694517612457,
0.2020554542541504,
-0.05575459450483322,
-0.03033224493265152,
0.024607427418231964,
-0.024162137880921364,
0.016394300386309624,
0.0820893719792366,
0.09882034361362457,
0.04459886625409126,
-0.0992712453007698,
-0.028493640944361687,
-0.05652338266372681,
-0.014672351069748402,
-0.03306088224053383,
0.0703345388174057,
0.009901232086122036,
0.00014863864635117352,
-0.049917444586753845,
0.033988989889621735,
-0.08421529829502106,
-0.08576150983572006,
0.050238341093063354,
-0.20633438229560852,
-0.18033018708229065,
-0.02004077658057213,
0.03325420245528221,
0.03793014585971832,
0.056688662618398666,
-0.009182472713291645,
0.021692857146263123,
0.06541910022497177,
-0.02490757405757904,
-0.1130383089184761,
-0.10200046002864838,
0.07210039347410202,
-0.08018404245376587,
0.18717950582504272,
-0.03827475383877754,
0.06587065011262894,
0.13217975199222565,
0.05226118490099907,
-0.13088154792785645,
0.03517909348011017,
0.0662931278347969,
-0.0608343742787838,
0.02551826275885105,
0.12526513636112213,
-0.01692570187151432,
0.06779079139232635,
0.03389660269021988,
-0.06331592053174973,
-0.018006497994065285,
-0.009521562606096268,
-0.009777862578630447,
-0.06539911031723022,
-0.057124681770801544,
-0.03083414025604725,
0.13902929425239563,
0.20637311041355133,
-0.06515128910541534,
-0.008131654933094978,
-0.06273410469293594,
-0.009203283116221428,
0.051834117621183395,
0.04550262540578842,
-0.03385689854621887,
-0.263713002204895,
0.008959752507507801,
0.06186707317829132,
0.020695220679044724,
-0.23829688131809235,
-0.068141408264637,
0.004009630065411329,
-0.06454388797283173,
-0.08771450817584991,
0.11341589689254761,
0.04319624602794647,
0.0658569410443306,
-0.04835867881774902,
0.02069137617945671,
-0.0829535573720932,
0.15536099672317505,
-0.1437208503484726,
-0.10831715166568756
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# random25eof_find_passage_train1000000_eval1000_rare_gpt2_1e-4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the tyzhu/random25eof_find_passage_train1000000_eval1000_rare dataset.
It achieves the following results on the evaluation set:
- Loss: 16.0353
- Accuracy: 0.0323
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-------:|:---------------:|:--------:|
| 5.0954 | 1.0 | 15633 | 4.9196 | 0.0660 |
| 18.0683 | 2.0 | 31266 | 16.0353 | 0.0323 |
| 13.7299 | 3.0 | 46899 | 16.0353 | 0.0323 |
| 13.7253 | 4.0 | 62532 | 16.0353 | 0.0323 |
| 13.7207 | 5.0 | 78165 | 16.0353 | 0.0323 |
| 13.7278 | 6.0 | 93798 | 16.0353 | 0.0323 |
| 13.7344 | 7.0 | 109431 | 16.0353 | 0.0323 |
| 13.7286 | 8.0 | 125064 | 16.0353 | 0.0323 |
| 13.7285 | 9.0 | 140697 | 16.0353 | 0.0323 |
| 13.7342 | 10.0 | 156330 | 16.0353 | 0.0323 |
| 13.7288 | 11.0 | 171963 | 16.0353 | 0.0323 |
| 13.7282 | 12.0 | 187596 | 16.0353 | 0.0323 |
| 13.7293 | 13.0 | 203229 | 16.0353 | 0.0323 |
| 13.7279 | 14.0 | 218862 | 16.0353 | 0.0323 |
| 13.73 | 15.0 | 234495 | 16.0353 | 0.0323 |
| 13.7299 | 16.0 | 250128 | 16.0353 | 0.0323 |
| 13.73 | 17.0 | 265761 | 16.0353 | 0.0323 |
| 13.7213 | 18.0 | 281394 | 16.0353 | 0.0323 |
| 13.7269 | 19.0 | 297027 | 16.0353 | 0.0323 |
| 13.7219 | 20.0 | 312660 | 16.0353 | 0.0323 |
| 13.7292 | 21.0 | 328293 | 16.0353 | 0.0323 |
| 13.7239 | 22.0 | 343926 | 16.0353 | 0.0323 |
| 13.7279 | 23.0 | 359559 | 16.0353 | 0.0323 |
| 13.7222 | 24.0 | 375192 | 16.0353 | 0.0323 |
| 13.723 | 25.0 | 390825 | 16.0353 | 0.0323 |
| 13.7311 | 26.0 | 406458 | 16.0353 | 0.0323 |
| 13.7253 | 27.0 | 422091 | 16.0353 | 0.0323 |
| 13.7238 | 28.0 | 437724 | 16.0353 | 0.0323 |
| 13.7302 | 29.0 | 453357 | 16.0353 | 0.0323 |
| 13.7251 | 30.0 | 468990 | 16.0353 | 0.0323 |
| 13.7254 | 31.0 | 484623 | 16.0353 | 0.0323 |
| 13.7297 | 32.0 | 500256 | 16.0353 | 0.0323 |
| 13.727 | 33.0 | 515889 | 16.0353 | 0.0323 |
| 13.7286 | 34.0 | 531522 | 16.0353 | 0.0323 |
| 13.7268 | 35.0 | 547155 | 16.0353 | 0.0323 |
| 13.7307 | 36.0 | 562788 | 16.0353 | 0.0323 |
| 13.7274 | 37.0 | 578421 | 16.0353 | 0.0323 |
| 13.7296 | 38.0 | 594054 | 16.0353 | 0.0323 |
| 13.7294 | 39.0 | 609687 | 16.0353 | 0.0323 |
| 13.7268 | 40.0 | 625320 | 16.0353 | 0.0323 |
| 13.7234 | 41.0 | 640953 | 16.0353 | 0.0323 |
| 13.7221 | 42.0 | 656586 | 16.0353 | 0.0323 |
| 13.7291 | 43.0 | 672219 | 16.0353 | 0.0323 |
| 13.7283 | 44.0 | 687852 | 16.0353 | 0.0323 |
| 13.7283 | 45.0 | 703485 | 16.0353 | 0.0323 |
| 13.7231 | 46.0 | 719118 | 16.0353 | 0.0323 |
| 13.7252 | 47.0 | 734751 | 16.0353 | 0.0323 |
| 13.7328 | 48.0 | 750384 | 16.0353 | 0.0323 |
| 13.734 | 49.0 | 766017 | 16.0353 | 0.0323 |
| 13.7288 | 50.0 | 781650 | 16.0353 | 0.0323 |
| 13.7259 | 51.0 | 797283 | 16.0353 | 0.0323 |
| 13.7295 | 52.0 | 812916 | 16.0353 | 0.0323 |
| 13.7299 | 53.0 | 828549 | 16.0353 | 0.0323 |
| 13.7278 | 54.0 | 844182 | 16.0353 | 0.0323 |
| 13.7286 | 55.0 | 859815 | 16.0353 | 0.0323 |
| 13.7323 | 56.0 | 875448 | 16.0353 | 0.0323 |
| 13.7266 | 57.0 | 891081 | 16.0353 | 0.0323 |
| 13.7277 | 58.0 | 906714 | 16.0353 | 0.0323 |
| 13.7273 | 59.0 | 922347 | 16.0353 | 0.0323 |
| 13.7343 | 60.0 | 937980 | 16.0353 | 0.0323 |
| 13.7278 | 61.0 | 953613 | 16.0353 | 0.0323 |
| 13.7265 | 62.0 | 969246 | 16.0353 | 0.0323 |
| 13.7264 | 63.0 | 984879 | 16.0353 | 0.0323 |
| 13.736 | 64.0 | 1000512 | 16.0353 | 0.0323 |
| 13.7281 | 65.0 | 1016145 | 16.0353 | 0.0323 |
| 13.7307 | 66.0 | 1031778 | 16.0353 | 0.0323 |
| 13.7305 | 67.0 | 1047411 | 16.0353 | 0.0323 |
| 13.7273 | 68.0 | 1063044 | 16.0353 | 0.0323 |
| 13.7288 | 69.0 | 1078677 | 16.0353 | 0.0323 |
| 13.7252 | 70.0 | 1094310 | 16.0353 | 0.0323 |
| 13.7258 | 71.0 | 1109943 | 16.0353 | 0.0323 |
| 13.725 | 72.0 | 1125576 | 16.0353 | 0.0323 |
| 13.7257 | 73.0 | 1141209 | 16.0353 | 0.0323 |
| 13.7274 | 74.0 | 1156842 | 16.0353 | 0.0323 |
| 13.7319 | 75.0 | 1172475 | 16.0353 | 0.0323 |
| 13.7341 | 76.0 | 1188108 | 16.0353 | 0.0323 |
| 13.7281 | 77.0 | 1203741 | 16.0353 | 0.0323 |
| 13.7277 | 78.0 | 1219374 | 16.0353 | 0.0323 |
| 13.7266 | 79.0 | 1235007 | 16.0353 | 0.0323 |
| 13.7277 | 80.0 | 1250640 | 16.0353 | 0.0323 |
| 13.726 | 81.0 | 1266273 | 16.0353 | 0.0323 |
| 13.7251 | 82.0 | 1281906 | 16.0353 | 0.0323 |
| 13.7285 | 83.0 | 1297539 | 16.0353 | 0.0323 |
| 13.7263 | 84.0 | 1313172 | 16.0353 | 0.0323 |
| 13.7273 | 85.0 | 1328805 | 16.0353 | 0.0323 |
| 13.7238 | 86.0 | 1344438 | 16.0353 | 0.0323 |
| 13.7298 | 87.0 | 1360071 | 16.0353 | 0.0323 |
| 13.7283 | 88.0 | 1375704 | 16.0353 | 0.0323 |
| 13.7306 | 89.0 | 1391337 | 16.0353 | 0.0323 |
| 13.7235 | 90.0 | 1406970 | 16.0353 | 0.0323 |
| 13.7292 | 91.0 | 1422603 | 16.0353 | 0.0323 |
| 13.7245 | 92.0 | 1438236 | 16.0353 | 0.0323 |
| 13.7256 | 93.0 | 1453869 | 16.0353 | 0.0323 |
| 13.7247 | 94.0 | 1469502 | 16.0353 | 0.0323 |
| 13.7254 | 95.0 | 1485135 | 16.0353 | 0.0323 |
| 13.7275 | 96.0 | 1500768 | 16.0353 | 0.0323 |
| 13.7269 | 97.0 | 1516401 | 16.0353 | 0.0323 |
| 13.7287 | 98.0 | 1532034 | 16.0353 | 0.0323 |
| 13.7251 | 99.0 | 1547667 | 16.0353 | 0.0323 |
| 13.7272 | 100.0 | 1563300 | 16.0353 | 0.0323 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/random25eof_find_passage_train1000000_eval1000_rare"], "metrics": ["accuracy"], "base_model": "gpt2", "model-index": [{"name": "random25eof_find_passage_train1000000_eval1000_rare_gpt2_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/random25eof_find_passage_train1000000_eval1000_rare", "type": "tyzhu/random25eof_find_passage_train1000000_eval1000_rare"}, "metrics": [{"type": "accuracy", "value": 0.03227659574468085, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/random25eof_find_passage_train1000000_eval1000_rare_gpt2_1e-4 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/random25eof_find_passage_train1000000_eval1000_rare",
"base_model:gpt2",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:32:41+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train1000000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| random25eof\_find\_passage\_train1000000\_eval1000\_rare\_gpt2\_1e-4
====================================================================
This model is a fine-tuned version of gpt2 on the tyzhu/random25eof\_find\_passage\_train1000000\_eval1000\_rare dataset.
It achieves the following results on the evaluation set:
* Loss: 16.0353
* Accuracy: 0.0323
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 100.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train1000000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
100,
98,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train1000000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.13479222357273102,
0.1747519075870514,
-0.0029949790332466364,
0.12786096334457397,
0.1275678277015686,
0.0390346460044384,
0.11845956742763519,
0.16259004175662994,
-0.09738057106733322,
0.08606753498315811,
0.1519254595041275,
0.09837449342012405,
0.05428653955459595,
0.16902774572372437,
-0.03531928360462189,
-0.2275296002626419,
0.015109183266758919,
0.02638334408402443,
-0.016436411067843437,
0.14473144710063934,
0.07378850877285004,
-0.11540509015321732,
0.08899237215518951,
0.0037856544367969036,
-0.18091356754302979,
-0.02317948080599308,
-0.008058733306825161,
-0.05198712646961212,
0.1198599711060524,
0.01950531080365181,
0.08429427444934845,
0.028651289641857147,
0.07459047436714172,
-0.14942842721939087,
0.0015765647403895855,
0.052301693707704544,
0.0006842316943220794,
0.10271954536437988,
0.06870944797992706,
-0.03291090950369835,
0.08986841887235641,
-0.048745542764663696,
0.02422347664833069,
0.016836171969771385,
-0.13559497892856598,
-0.17970973253250122,
-0.09267212450504303,
0.08188379555940628,
0.017434420064091682,
0.09189252555370331,
-0.01448580902069807,
0.11844254285097122,
-0.0543387234210968,
0.07664082199335098,
0.2778255343437195,
-0.2853204607963562,
-0.058530043810606,
0.0365738607943058,
0.01606488786637783,
0.06259410083293915,
-0.09286109358072281,
-0.04844190180301666,
0.05137711018323898,
0.030750954523682594,
0.11485949158668518,
0.0008316839230246842,
-0.03372816741466522,
0.0159812793135643,
-0.14224138855934143,
-0.06775011867284775,
0.13606297969818115,
0.030680185183882713,
-0.03675542026758194,
-0.046420421451330185,
-0.07737976312637329,
-0.2014453411102295,
-0.015267561189830303,
0.0285376887768507,
0.01845334656536579,
-0.03073679283261299,
-0.08239593356847763,
0.01629231497645378,
-0.0641888678073883,
-0.07001525908708572,
-0.01726558431982994,
0.07026655226945877,
0.04816189780831337,
0.02002350054681301,
-0.0015782517148181796,
0.12953180074691772,
-0.03045734390616417,
-0.15198403596878052,
0.0005285319639369845,
0.002836937317624688,
-0.004331338685005903,
-0.022307738661766052,
-0.04140176251530647,
-0.00016097252955660224,
0.023329099640250206,
0.15959912538528442,
-0.04331668093800545,
0.043372638523578644,
0.01190882921218872,
0.027664098888635635,
-0.07024948298931122,
0.12239929288625717,
-0.0973515659570694,
-0.03878092020750046,
0.019028985872864723,
0.10305368900299072,
0.02743719518184662,
-0.012546636164188385,
-0.09134376049041748,
-0.019311659038066864,
0.13041652739048004,
0.02718564122915268,
-0.01618569903075695,
0.05882412940263748,
-0.0492267906665802,
-0.03632945567369461,
0.050050631165504456,
-0.0962308943271637,
0.006908145267516375,
0.02934313751757145,
-0.11239948123693466,
-0.05554636940360069,
-0.011879956349730492,
-0.01888955570757389,
-0.045402176678180695,
0.08082768321037292,
-0.11679194122552872,
0.007338171824812889,
-0.06922722607851028,
-0.11939817667007446,
0.004110087640583515,
-0.10047708451747894,
-0.01277357991784811,
-0.0709482952952385,
-0.2202882617712021,
-0.033278435468673706,
0.019276460632681847,
-0.0661386251449585,
-0.08158557862043381,
-0.0789300948381424,
-0.10333807021379471,
0.03438510000705719,
-0.021943941712379456,
0.07914736121892929,
-0.06880198419094086,
0.11134188622236252,
0.031368713825941086,
0.05225825682282448,
0.020256569609045982,
0.047982022166252136,
-0.09033756703138351,
0.04369352385401726,
-0.14136067032814026,
0.08589182794094086,
-0.05535567179322243,
0.028348242864012718,
-0.09472072124481201,
-0.12076647579669952,
0.042046889662742615,
-0.03582104295492172,
0.10298969596624374,
0.1447206437587738,
-0.14456962049007416,
-0.0697476863861084,
0.18814511597156525,
-0.06681187450885773,
-0.10281123965978622,
0.12333990633487701,
-0.05972409248352051,
-0.02411956712603569,
0.050311170518398285,
0.17339272797107697,
0.07625611126422882,
-0.04693111777305603,
-0.03911138325929642,
-0.025672858580946922,
0.05592838302254677,
-0.04724832624197006,
0.09094732999801636,
0.009685657918453217,
0.014136354438960552,
0.015646815299987793,
-0.04311669245362282,
0.05469868332147598,
-0.11490081250667572,
-0.08918575942516327,
-0.0332232303917408,
-0.09541328251361847,
0.07244439423084259,
0.05089632421731949,
0.07039398699998856,
-0.09284280985593796,
-0.0948900356888771,
0.023977598175406456,
0.11057671159505844,
-0.08504325151443481,
0.0032743948977440596,
-0.06777146458625793,
0.1467311829328537,
-0.07508863508701324,
-0.02188829705119133,
-0.16762858629226685,
-0.024228479713201523,
0.03958386555314064,
0.02161286398768425,
-0.009689997881650925,
-0.018956737592816353,
0.06956013292074203,
0.08671797066926956,
-0.05332619696855545,
-0.06238017603754997,
-0.03693027049303055,
-0.02739303931593895,
-0.1098303496837616,
-0.18962866067886353,
-0.061133190989494324,
-0.0026809689588844776,
0.14434652030467987,
-0.2012729048728943,
0.03476119413971901,
0.003197034588083625,
0.1074277013540268,
0.0020421973895281553,
-0.05090922862291336,
-0.006543300114572048,
0.05699697509407997,
-0.056812528520822525,
-0.07959583401679993,
0.06280859559774399,
0.016347669064998627,
-0.06767763197422028,
-0.009689412079751492,
-0.1181952953338623,
0.11826327443122864,
0.11551666259765625,
-0.020340943709015846,
-0.10191184282302856,
0.013797295279800892,
-0.07423708587884903,
-0.02964651957154274,
-0.03624621778726578,
-0.0034667893778532743,
0.13639391958713531,
0.0034438238944858313,
0.15113264322280884,
-0.09365150332450867,
-0.04802841693162918,
0.03864511474967003,
0.0126101765781641,
0.02204037271440029,
0.14406998455524445,
0.05994720757007599,
-0.04024414345622063,
0.15503713488578796,
0.030367081984877586,
-0.05620715767145157,
0.10692800581455231,
-0.04920532926917076,
-0.08741538971662521,
-0.03940870240330696,
0.019985150545835495,
0.021114934235811234,
0.09820038080215454,
-0.09941353648900986,
-0.016740936785936356,
0.03560420498251915,
0.018890203908085823,
0.018636884167790413,
-0.18428191542625427,
-0.033751700073480606,
0.02632557787001133,
-0.06880350410938263,
-0.02033350244164467,
-0.017269842326641083,
0.007509855553507805,
0.11231157183647156,
0.0037910486571490765,
-0.08271477371454239,
0.030836647376418114,
0.002801473718136549,
-0.08071473240852356,
0.20613402128219604,
-0.07793880254030228,
-0.13172373175621033,
-0.12447426468133926,
-0.0312206894159317,
-0.0602676086127758,
0.014533634297549725,
0.043865762650966644,
-0.05692035332322121,
-0.00908564031124115,
-0.09322063624858856,
0.007523293606936932,
-0.03322000429034233,
0.02529509738087654,
0.013489974662661552,
-0.031407639384269714,
0.06285328418016434,
-0.11134612560272217,
0.00328632490709424,
-0.02593148685991764,
-0.04460559040307999,
0.06177927181124687,
0.015474683605134487,
0.09516769647598267,
0.12841492891311646,
-0.011330769397318363,
0.02706318348646164,
-0.028772937133908272,
0.26415586471557617,
-0.036444615572690964,
-0.0313078910112381,
0.11094583570957184,
0.025218013674020767,
0.07786952704191208,
0.12073902785778046,
0.043989285826683044,
-0.07389423996210098,
-0.006119426805526018,
0.021870264783501625,
-0.023341631516814232,
-0.23271441459655762,
-0.03467028588056564,
-0.04070932790637016,
0.02971050888299942,
0.11353897303342819,
0.026020612567663193,
0.011590378358960152,
0.07975006103515625,
-0.008366464637219906,
0.07737085968255997,
-0.03923000395298004,
0.07453496754169464,
0.08498378098011017,
0.060827989131212234,
0.1242683082818985,
-0.007024306338280439,
-0.03842061012983322,
0.050244372338056564,
-0.04352586716413498,
0.2327384352684021,
-0.07573439925909042,
0.18894541263580322,
0.020097199827432632,
0.19404834508895874,
0.012853945605456829,
0.07492922246456146,
-0.018419401720166206,
0.012454423122107983,
-0.0026762057095766068,
-0.052577342838048935,
-0.05002398416399956,
0.010207926854491234,
-0.03345854952931404,
0.07499704509973526,
-0.11737271398305893,
0.0007746436167508364,
0.04181951284408569,
0.24291108548641205,
0.07693558931350708,
-0.36429497599601746,
-0.09867289662361145,
-0.015436127781867981,
0.0007318488205783069,
-0.04105447977781296,
0.012123999185860157,
0.1104419156908989,
-0.10624656826257706,
0.02145865373313427,
-0.07815198600292206,
0.09207501262426376,
-0.0734204575419426,
0.01655942015349865,
0.04271717369556427,
0.08925013244152069,
-0.019376056268811226,
0.07397639751434326,
-0.24431326985359192,
0.24075885117053986,
0.009261331520974636,
0.06389163434505463,
-0.06264962255954742,
0.005661272909492254,
0.027692876756191254,
0.0060149566270411015,
0.08063871413469315,
0.0029223687015473843,
0.0018198476172983646,
-0.20478606224060059,
-0.12366189062595367,
0.0014661365421488881,
0.07191173732280731,
-0.04642010107636452,
0.11866606026887894,
-0.005521023645997047,
-0.003185427747666836,
0.02947968803346157,
0.008272778242826462,
-0.050621021538972855,
-0.08032523840665817,
0.0254118163138628,
0.011790641583502293,
0.015685230493545532,
-0.0634009912610054,
-0.12196848541498184,
-0.08097855001688004,
0.15216827392578125,
-0.05301375687122345,
-0.07265593111515045,
-0.10764449834823608,
0.1114099770784378,
0.13453517854213715,
-0.09293379634618759,
0.023782551288604736,
0.010063225403428078,
0.08278072625398636,
0.02085161954164505,
-0.07155055552721024,
0.08420504629611969,
-0.04384441673755646,
-0.21016457676887512,
-0.06417180597782135,
0.1253243386745453,
0.04328014701604843,
0.06713969260454178,
-0.03401787579059601,
0.041682396084070206,
-0.03174908459186554,
-0.08707497268915176,
0.03623704984784126,
-0.0037762420251965523,
0.08765176683664322,
0.04805946350097656,
-0.018676746636629105,
0.033355046063661575,
-0.06158480420708656,
-0.01711214706301689,
0.1523907631635666,
0.27510565519332886,
-0.09502623975276947,
0.0417579710483551,
0.025479186326265335,
-0.06722386926412582,
-0.15933316946029663,
0.019081050530076027,
0.08314497023820877,
0.02457304298877716,
-0.014905828051269054,
-0.2131517231464386,
0.05743986740708351,
0.11552181094884872,
-0.011601055040955544,
0.11710355430841446,
-0.3595782220363617,
-0.11895902454853058,
0.06854390352964401,
0.1008276492357254,
0.11379870772361755,
-0.15660671889781952,
-0.06246660649776459,
-0.0028108402621001005,
-0.1489195078611374,
0.09794202446937561,
-0.03834257647395134,
0.1274939626455307,
-0.06358566880226135,
0.0696503072977066,
0.02181820571422577,
-0.06902401149272919,
0.13106773793697357,
0.02886638417840004,
0.07147863507270813,
-0.05229737237095833,
-0.018996497616171837,
0.09740675240755081,
-0.05690274015069008,
0.031044719740748405,
-0.08551280945539474,
0.072105772793293,
-0.14726504683494568,
-0.0185968317091465,
-0.08978290110826492,
0.026838185265660286,
-0.03390240669250488,
-0.048484135419130325,
-0.04609760269522667,
0.03700558468699455,
0.07378576695919037,
-0.004407286178320646,
0.09869382530450821,
0.04181773588061333,
0.145836740732193,
0.10197422653436661,
0.03186620771884918,
-0.03330755606293678,
-0.08656233549118042,
-0.011449437588453293,
-0.004960406571626663,
0.04697992652654648,
-0.12037872523069382,
0.00824886467307806,
0.16767258942127228,
0.04364556074142456,
0.13639496266841888,
0.08154970407485962,
-0.06697123497724533,
0.031611744314432144,
0.03968460112810135,
-0.17774255573749542,
-0.07674571871757507,
-0.02219696156680584,
-0.054575420916080475,
-0.13008534908294678,
0.015460626222193241,
0.0993303656578064,
-0.07482843101024628,
-0.0338866226375103,
-0.010037649422883987,
0.023845747113227844,
-0.0037417321000248194,
0.2255629003047943,
0.044276054948568344,
0.06685951352119446,
-0.11809226870536804,
0.06685797870159149,
0.06737589836120605,
-0.05792310833930969,
0.0314982533454895,
0.07917072623968124,
-0.09223784506320953,
-0.010477240197360516,
0.07059866935014725,
0.15138526260852814,
-0.07383439689874649,
-0.011278071440756321,
-0.1477593183517456,
-0.08428790420293808,
0.09675122797489166,
0.12751182913780212,
0.08215481787919998,
0.05126595124602318,
-0.014423616230487823,
-0.021795004606246948,
-0.11401189863681793,
0.1031927689909935,
0.0906330794095993,
0.0744386538863182,
-0.12284567207098007,
0.16956867277622223,
-0.022935686632990837,
0.027223970741033554,
-0.010423862375319004,
0.023007407784461975,
-0.11490784585475922,
-0.008020695298910141,
-0.13203397393226624,
0.03752788156270981,
-0.07237084954977036,
-0.007029444444924593,
-0.022842245176434517,
-0.03202543035149574,
-0.04944417625665665,
0.024295056238770485,
-0.1018589437007904,
-0.05468342825770378,
0.001593231107108295,
0.03614893928170204,
-0.13234783709049225,
-0.02063208445906639,
0.00783966202288866,
-0.08393139392137527,
0.10609129071235657,
0.08134830743074417,
0.01610037125647068,
0.011635152623057365,
-0.06394368410110474,
-0.009105181321501732,
0.0039522903971374035,
0.004877839237451553,
0.05120617896318436,
-0.09819957613945007,
0.022348668426275253,
-0.019735869020223618,
-0.006982137449085712,
0.02590038813650608,
0.0715179368853569,
-0.14035047590732574,
-0.01843887008726597,
-0.004404284060001373,
-0.015742309391498566,
-0.07971801608800888,
0.060664158314466476,
0.0911327376961708,
0.009643835946917534,
0.16014331579208374,
-0.07872696220874786,
0.04974319040775299,
-0.22843053936958313,
-0.015478872694075108,
-0.003985034767538309,
-0.1041119322180748,
-0.09706717729568481,
-0.013387433253228664,
0.09111934155225754,
-0.0567484013736248,
0.11669346690177917,
-0.018030181527137756,
-0.0036138819996267557,
0.006135337986052036,
-0.01591164618730545,
0.04512408748269081,
0.020521463826298714,
0.204328715801239,
0.041650861501693726,
-0.056377001106739044,
0.0576503649353981,
0.0331420935690403,
0.08635949343442917,
0.13117024302482605,
0.1641320288181305,
0.09428951889276505,
0.04199972003698349,
0.07442368566989899,
0.03816777095198631,
-0.09175270795822144,
-0.12566527724266052,
0.0474570207297802,
-0.053626179695129395,
0.11339953541755676,
0.001878863200545311,
0.21392761170864105,
0.08221601694822311,
-0.15319764614105225,
0.05012238398194313,
-0.05183877423405647,
-0.09557565301656723,
-0.09597235172986984,
-0.08268821984529495,
-0.08140906691551208,
-0.14558438956737518,
0.017050692811608315,
-0.13669364154338837,
0.029228664934635162,
0.11801151186227798,
0.022285478189587593,
-0.00834101252257824,
0.09171994775533676,
0.07319065928459167,
0.0035953489132225513,
0.05603514984250069,
0.014439510181546211,
-0.01598723977804184,
-0.044524285942316055,
-0.09039543569087982,
0.04605092480778694,
-0.024299025535583496,
0.06137332320213318,
-0.0336669497191906,
0.00955564808100462,
0.04857015982270241,
-0.006472018081694841,
-0.09784672409296036,
0.015478085726499557,
0.0012254720786586404,
0.06613287329673767,
0.06613050401210785,
0.016206713393330574,
0.01994619145989418,
-0.02726379781961441,
0.21056446433067322,
-0.05692484229803085,
-0.0259418748319149,
-0.11170840263366699,
0.2292625457048416,
0.03034759871661663,
-0.03791578859090805,
0.06031046062707901,
-0.09335371106863022,
0.003746731672435999,
0.19663093984127045,
0.20302341878414154,
-0.056474193930625916,
-0.0298161581158638,
0.025374697521328926,
-0.02394319325685501,
0.017637677490711212,
0.08166500180959702,
0.09865101426839828,
0.046264540404081345,
-0.09964518994092941,
-0.02883780375123024,
-0.057319220155477524,
-0.014844216406345367,
-0.0327804870903492,
0.07006426900625229,
0.009780310094356537,
0.00111332256346941,
-0.050675168633461,
0.033107977360486984,
-0.08590289205312729,
-0.08354344964027405,
0.05022672936320305,
-0.20686164498329163,
-0.1801658272743225,
-0.020054569467902184,
0.0343330092728138,
0.03701876848936081,
0.05735809728503227,
-0.009233271703124046,
0.020555714145302773,
0.06480500102043152,
-0.025368379428982735,
-0.11252345889806747,
-0.10111185163259506,
0.07253611087799072,
-0.08063235133886337,
0.1877547651529312,
-0.038924604654312134,
0.06450428068637848,
0.1322609782218933,
0.05260826647281647,
-0.13099387288093567,
0.03363057225942612,
0.06663770973682404,
-0.060837727040052414,
0.024169154465198517,
0.1257874220609665,
-0.016571596264839172,
0.06878332793712616,
0.034021418541669846,
-0.06351669877767563,
-0.01802009716629982,
-0.009715357795357704,
-0.008806753903627396,
-0.06492354720830917,
-0.05809670314192772,
-0.030356433242559433,
0.1379341185092926,
0.20710065960884094,
-0.06503849476575851,
-0.008442244492471218,
-0.06276317685842514,
-0.010290209203958511,
0.05141029506921768,
0.046855803579092026,
-0.03352468088269234,
-0.26406756043434143,
0.009289858862757683,
0.06278090178966522,
0.02106192335486412,
-0.24079374969005585,
-0.06943517923355103,
0.005818366538733244,
-0.06408659368753433,
-0.08734536170959473,
0.11432657390832901,
0.042118486016988754,
0.06669557839632034,
-0.04828772321343422,
0.020660972222685814,
-0.08400142937898636,
0.1556757390499115,
-0.142680361866951,
-0.108217753469944
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# random25eof_find_passage_train500000_eval1000_rare_gpt2_1e-4
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the tyzhu/random25eof_find_passage_train500000_eval1000_rare dataset.
It achieves the following results on the evaluation set:
- Loss: 8.1444
- Accuracy: 0.0429
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.4636 | 1.0 | 7821 | 3.2297 | 0.2716 |
| 3.7106 | 2.0 | 15642 | 4.0106 | 0.1526 |
| 3.7508 | 3.0 | 23463 | 3.2367 | 0.2480 |
| 4.1675 | 4.0 | 31284 | 4.4917 | 0.0805 |
| 6.7235 | 5.0 | 39105 | 4.7860 | 0.0746 |
| 5.1842 | 6.0 | 46926 | 4.8181 | 0.0631 |
| 4.9571 | 7.0 | 54747 | 4.7880 | 0.0486 |
| 4.8685 | 8.0 | 62568 | 4.7267 | 0.0570 |
| 4.9291 | 9.0 | 70389 | 4.5794 | 0.0631 |
| 5.1418 | 10.0 | 78210 | 4.7474 | 0.0324 |
| 5.1076 | 11.0 | 86031 | 4.6376 | 0.0235 |
| 5.1574 | 12.0 | 93852 | 5.6543 | 0.0209 |
| 5.4022 | 13.0 | 101673 | 5.2926 | 0.0318 |
| 5.196 | 14.0 | 109494 | 4.6389 | 0.0274 |
| 5.1263 | 15.0 | 117315 | 4.6482 | 0.0509 |
| 5.2671 | 16.0 | 125136 | 5.0535 | 0.0486 |
| 5.3196 | 17.0 | 132957 | 5.0969 | 0.0485 |
| 5.3886 | 18.0 | 140778 | 5.1684 | 0.0484 |
| 5.3472 | 19.0 | 148599 | 5.1207 | 0.0490 |
| 5.3396 | 20.0 | 156420 | 5.0926 | 0.0431 |
| 5.3467 | 21.0 | 164241 | 5.0309 | 0.0436 |
| 5.4736 | 22.0 | 172062 | 5.1763 | 0.0421 |
| 5.5901 | 23.0 | 179883 | 5.3917 | 0.0428 |
| 5.5784 | 24.0 | 187704 | 5.2969 | 0.0471 |
| 5.7878 | 25.0 | 195525 | 6.1804 | 0.0216 |
| 5.8226 | 26.0 | 203346 | 5.5547 | 0.0287 |
| 5.575 | 27.0 | 211167 | 5.4069 | 0.0399 |
| 5.5609 | 28.0 | 218988 | 5.0071 | 0.0453 |
| 5.5837 | 29.0 | 226809 | 5.0225 | 0.0461 |
| 5.5653 | 30.0 | 234630 | 5.0185 | 0.0516 |
| 5.4724 | 31.0 | 242451 | 5.1361 | 0.0360 |
| 5.5069 | 32.0 | 250272 | 5.0624 | 0.0493 |
| 5.4248 | 33.0 | 258093 | 4.9379 | 0.0595 |
| 5.3906 | 34.0 | 265914 | 4.9166 | 0.0499 |
| 5.3928 | 35.0 | 273735 | 4.9810 | 0.0473 |
| 5.4231 | 36.0 | 281556 | 4.9896 | 0.0497 |
| 5.4229 | 37.0 | 289377 | 4.9450 | 0.0504 |
| 5.4311 | 38.0 | 297198 | 5.0714 | 0.0482 |
| 5.4962 | 39.0 | 305019 | 5.1698 | 0.0273 |
| 5.8669 | 40.0 | 312840 | 6.0263 | 0.0206 |
| 6.1279 | 41.0 | 320661 | 5.8430 | 0.0060 |
| 6.0694 | 42.0 | 328482 | 5.7233 | 0.0043 |
| 5.9916 | 43.0 | 336303 | 5.5829 | 0.0069 |
| 5.8846 | 44.0 | 344124 | 5.7421 | 0.0535 |
| 6.0304 | 45.0 | 351945 | 5.8849 | 0.0229 |
| 6.0668 | 46.0 | 359766 | 5.7382 | 0.0324 |
| 5.935 | 47.0 | 367587 | 5.6805 | 0.0456 |
| 6.017 | 48.0 | 375408 | 5.6578 | 0.0232 |
| 5.9654 | 49.0 | 383229 | 5.7026 | 0.0215 |
| 6.1431 | 50.0 | 391050 | 6.9215 | 0.0120 |
| 6.6877 | 51.0 | 398871 | 7.0450 | 0.0136 |
| 7.0868 | 52.0 | 406692 | 7.3231 | 0.0313 |
| 7.2371 | 53.0 | 414513 | 7.2233 | 0.0296 |
| 7.228 | 54.0 | 422334 | 7.4405 | 0.0286 |
| 7.3329 | 55.0 | 430155 | 7.5372 | 0.0286 |
| 7.3697 | 56.0 | 437976 | 7.6262 | 0.0275 |
| 7.4112 | 57.0 | 445797 | 7.7340 | 0.0275 |
| 7.4351 | 58.0 | 453618 | 7.7265 | 0.0284 |
| 7.4332 | 59.0 | 461439 | 7.6818 | 0.0315 |
| 7.4711 | 60.0 | 469260 | 7.7316 | 0.0308 |
| 7.5108 | 61.0 | 477081 | 8.0771 | 0.0348 |
| 7.5441 | 62.0 | 484902 | 8.0771 | 0.0348 |
| 7.5434 | 63.0 | 492723 | 8.0771 | 0.0348 |
| 7.5699 | 64.0 | 500544 | 8.1542 | 0.0288 |
| 7.5941 | 65.0 | 508365 | 8.1362 | 0.0290 |
| 7.6153 | 66.0 | 516186 | 8.1578 | 0.0272 |
| 7.6334 | 67.0 | 524007 | 8.1578 | 0.0272 |
| 7.6341 | 68.0 | 531828 | 8.1578 | 0.0272 |
| 7.6332 | 69.0 | 539649 | 8.1578 | 0.0272 |
| 7.6333 | 70.0 | 547470 | 8.1578 | 0.0272 |
| 7.6333 | 71.0 | 555291 | 8.1578 | 0.0272 |
| 7.6555 | 72.0 | 563112 | 8.2466 | 0.0284 |
| 7.6625 | 73.0 | 570933 | 8.2466 | 0.0284 |
| 7.6646 | 74.0 | 578754 | 8.2466 | 0.0284 |
| 7.6627 | 75.0 | 586575 | 8.2466 | 0.0284 |
| 7.6626 | 76.0 | 594396 | 8.2466 | 0.0284 |
| 7.6618 | 77.0 | 602217 | 8.2782 | 0.0301 |
| 7.6207 | 78.0 | 610038 | 8.2760 | 0.0372 |
| 7.6182 | 79.0 | 617859 | 8.2760 | 0.0372 |
| 7.5707 | 80.0 | 625680 | 7.7851 | 0.0396 |
| 7.5331 | 81.0 | 633501 | 7.7851 | 0.0396 |
| 7.5329 | 82.0 | 641322 | 7.7851 | 0.0396 |
| 7.5339 | 83.0 | 649143 | 7.7851 | 0.0396 |
| 7.472 | 84.0 | 656964 | 7.8727 | 0.0405 |
| 7.4681 | 85.0 | 664785 | 7.8727 | 0.0405 |
| 7.4684 | 86.0 | 672606 | 7.8727 | 0.0405 |
| 7.4693 | 87.0 | 680427 | 7.8774 | 0.0404 |
| 7.5544 | 88.0 | 688248 | 7.8729 | 0.0389 |
| 7.5296 | 89.0 | 696069 | 7.9503 | 0.0408 |
| 7.5069 | 90.0 | 703890 | 7.9503 | 0.0408 |
| 7.5087 | 91.0 | 711711 | 7.9503 | 0.0408 |
| 7.5068 | 92.0 | 719532 | 7.9503 | 0.0408 |
| 7.5088 | 93.0 | 727353 | 7.9503 | 0.0408 |
| 7.5086 | 94.0 | 735174 | 7.9503 | 0.0408 |
| 7.5077 | 95.0 | 742995 | 7.9503 | 0.0408 |
| 7.5071 | 96.0 | 750816 | 7.9503 | 0.0408 |
| 7.5075 | 97.0 | 758637 | 7.9503 | 0.0408 |
| 7.5084 | 98.0 | 766458 | 7.9503 | 0.0408 |
| 7.508 | 99.0 | 774279 | 7.9503 | 0.0408 |
| 7.4938 | 100.0 | 782100 | 8.1444 | 0.0429 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
| {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/random25eof_find_passage_train500000_eval1000_rare"], "metrics": ["accuracy"], "base_model": "gpt2", "model-index": [{"name": "random25eof_find_passage_train500000_eval1000_rare_gpt2_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/random25eof_find_passage_train500000_eval1000_rare", "type": "tyzhu/random25eof_find_passage_train500000_eval1000_rare"}, "metrics": [{"type": "accuracy", "value": 0.042893617021276594, "name": "Accuracy"}]}]}]} | text-generation | tyzhu/random25eof_find_passage_train500000_eval1000_rare_gpt2_1e-4 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:tyzhu/random25eof_find_passage_train500000_eval1000_rare",
"base_model:gpt2",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:32:41+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train500000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| random25eof\_find\_passage\_train500000\_eval1000\_rare\_gpt2\_1e-4
===================================================================
This model is a fine-tuned version of gpt2 on the tyzhu/random25eof\_find\_passage\_train500000\_eval1000\_rare dataset.
It achieves the following results on the evaluation set:
* Loss: 8.1444
* Accuracy: 0.0429
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 100.0
### Training results
### Framework versions
* Transformers 4.34.0
* Pytorch 2.1.0+cu121
* Datasets 2.14.5
* Tokenizers 0.14.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train500000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
100,
98,
4,
33
] | [
"passage: TAGS\n#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-tyzhu/random25eof_find_passage_train500000_eval1000_rare #base_model-gpt2 #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 100.0### Training results### Framework versions\n\n\n* Transformers 4.34.0\n* Pytorch 2.1.0+cu121\n* Datasets 2.14.5\n* Tokenizers 0.14.1"
] | [
-0.13491442799568176,
0.1754964143037796,
-0.0028995631728321314,
0.12749259173870087,
0.12788289785385132,
0.04030558839440346,
0.11770209670066833,
0.16186630725860596,
-0.09739474952220917,
0.08583777397871017,
0.15014956891536713,
0.09718387573957443,
0.055753711611032486,
0.1705670952796936,
-0.03476661071181297,
-0.2267860472202301,
0.014631465077400208,
0.026233136653900146,
-0.017186380922794342,
0.14501290023326874,
0.07285086065530777,
-0.11593322455883026,
0.08992369472980499,
0.003157045692205429,
-0.18277773261070251,
-0.02121318131685257,
-0.007897973991930485,
-0.05179565027356148,
0.11884991824626923,
0.020005883648991585,
0.08461262285709381,
0.02725246734917164,
0.07701490819454193,
-0.14977815747261047,
0.0013954045716673136,
0.052444666624069214,
0.0008209251100197434,
0.10316366702318192,
0.0689171627163887,
-0.03135228157043457,
0.09180431813001633,
-0.04854274168610573,
0.024772798642516136,
0.016935663297772408,
-0.13482391834259033,
-0.17608045041561127,
-0.09311951696872711,
0.08231570571660995,
0.019907912239432335,
0.0920255184173584,
-0.014465322718024254,
0.118277907371521,
-0.05498233810067177,
0.07598859071731567,
0.2756398618221283,
-0.2862604856491089,
-0.0585906095802784,
0.03701294958591461,
0.014556687325239182,
0.06310772150754929,
-0.09311597794294357,
-0.04801102355122566,
0.052431654185056686,
0.030260978266596794,
0.11445685476064682,
0.001843775506131351,
-0.035626500844955444,
0.01571669802069664,
-0.14258433878421783,
-0.06531089544296265,
0.136569544672966,
0.03229715675115585,
-0.035666774958372116,
-0.04710402712225914,
-0.07665205746889114,
-0.20177076756954193,
-0.01562618277966976,
0.026897575706243515,
0.019193517044186592,
-0.031515851616859436,
-0.08201535046100616,
0.01686064712703228,
-0.06329730153083801,
-0.0710025280714035,
-0.019017493352293968,
0.06841098517179489,
0.04828568547964096,
0.020434824749827385,
-0.0018092970130965114,
0.12833818793296814,
-0.030406948179006577,
-0.15075066685676575,
0.0009605970117263496,
0.001967561198398471,
-0.005786991212517023,
-0.023606298491358757,
-0.04078570753335953,
-0.0012058288557454944,
0.02316245064139366,
0.15893900394439697,
-0.042263977229595184,
0.043004076927900314,
0.013341042213141918,
0.026807645335793495,
-0.07061030715703964,
0.12145908921957016,
-0.09838134050369263,
-0.04250171780586243,
0.01971651241183281,
0.10289053618907928,
0.02728777565062046,
-0.010873817838728428,
-0.09011903405189514,
-0.020302247256040573,
0.1282946765422821,
0.026785634458065033,
-0.017024070024490356,
0.05730335786938667,
-0.04925502836704254,
-0.035660963505506516,
0.048599038273096085,
-0.09611339867115021,
0.007665620185434818,
0.028600241988897324,
-0.1123674213886261,
-0.05400959029793739,
-0.013064711354672909,
-0.018847813829779625,
-0.04450289532542229,
0.08129600435495377,
-0.11739692836999893,
0.006796007975935936,
-0.07026826590299606,
-0.1192527711391449,
0.00399295799434185,
-0.09975280612707138,
-0.01410334650427103,
-0.07031746208667755,
-0.2190866470336914,
-0.03419967740774155,
0.018493128940463066,
-0.06665191054344177,
-0.08199470490217209,
-0.07950747013092041,
-0.10165639221668243,
0.034082502126693726,
-0.021026743575930595,
0.07953909039497375,
-0.06822056323289871,
0.11070950329303741,
0.03155630826950073,
0.05308716744184494,
0.020731735974550247,
0.04752780869603157,
-0.09059076011180878,
0.04228971526026726,
-0.1395697146654129,
0.08546390384435654,
-0.05497802793979645,
0.028818204998970032,
-0.09471109509468079,
-0.12055826187133789,
0.039123475551605225,
-0.03628338873386383,
0.10332800447940826,
0.1449604630470276,
-0.14565294981002808,
-0.06932235509157181,
0.18840913474559784,
-0.06747777760028839,
-0.10352816432714462,
0.12158249318599701,
-0.05857781693339348,
-0.02534377947449684,
0.05110969766974449,
0.17206203937530518,
0.07443773746490479,
-0.04592243209481239,
-0.039730723947286606,
-0.026342911645770073,
0.05597684532403946,
-0.05051654204726219,
0.09075417369604111,
0.009050220251083374,
0.013069410808384418,
0.015040075406432152,
-0.04121709614992142,
0.054508406668901443,
-0.11550480872392654,
-0.0894513800740242,
-0.033467236906290054,
-0.09725800156593323,
0.07046179473400116,
0.05058499425649643,
0.07074902206659317,
-0.09257873147726059,
-0.0939769595861435,
0.02403618022799492,
0.11082190275192261,
-0.0841241404414177,
0.0028034099377691746,
-0.06751003861427307,
0.14562535285949707,
-0.07601816952228546,
-0.022312650457024574,
-0.16724678874015808,
-0.024805568158626556,
0.03980409726500511,
0.020683255046606064,
-0.009564968757331371,
-0.019145656377077103,
0.06932961940765381,
0.08701510727405548,
-0.054093994200229645,
-0.06074223667383194,
-0.037985991686582565,
-0.02696380577981472,
-0.11082150787115097,
-0.18917810916900635,
-0.06048395112156868,
-0.0017173233209177852,
0.14224115014076233,
-0.2007904052734375,
0.0344342403113842,
0.0013305642642080784,
0.10860661417245865,
0.0022294127847999334,
-0.051801979541778564,
-0.0061006098985672,
0.05751378461718559,
-0.055786117911338806,
-0.07961656898260117,
0.06229814141988754,
0.014971899800002575,
-0.06743451207876205,
-0.013386501930654049,
-0.1161763146519661,
0.11926402896642685,
0.11550004035234451,
-0.019273731857538223,
-0.1021973043680191,
0.014801422134041786,
-0.07424729317426682,
-0.02961849607527256,
-0.03907953202724457,
-0.0026537098456174135,
0.1334875375032425,
0.003215889213606715,
0.1500808298587799,
-0.0933508649468422,
-0.04859643802046776,
0.03814591467380524,
0.014448638074100018,
0.02254023589193821,
0.14377449452877045,
0.06361421197652817,
-0.04053039103746414,
0.1550932079553604,
0.029890459030866623,
-0.05651373416185379,
0.10565026104450226,
-0.048735111951828,
-0.08815319091081619,
-0.038342997431755066,
0.018347380682826042,
0.02042488567531109,
0.09835279732942581,
-0.09786919504404068,
-0.01647777669131756,
0.03526094928383827,
0.017885057255625725,
0.018624626100063324,
-0.183682382106781,
-0.033935606479644775,
0.02577509917318821,
-0.06807207316160202,
-0.021875135600566864,
-0.01731974072754383,
0.007005807012319565,
0.11330655962228775,
0.003710993332788348,
-0.08054649084806442,
0.029496394097805023,
0.0031314780935645103,
-0.08109153807163239,
0.20581528544425964,
-0.0777510553598404,
-0.13075464963912964,
-0.12344339489936829,
-0.026479074731469154,
-0.06024782732129097,
0.013483356684446335,
0.042677514255046844,
-0.05919724330306053,
-0.010172893293201923,
-0.09314428269863129,
0.007275882642716169,
-0.03274501487612724,
0.02636856958270073,
0.015132410451769829,
-0.030835984274744987,
0.06195543706417084,
-0.11094813793897629,
0.003905853722244501,
-0.027580486610531807,
-0.04460836201906204,
0.05974016338586807,
0.01620471477508545,
0.09577114135026932,
0.1279211938381195,
-0.012155914679169655,
0.027183305472135544,
-0.028572438284754753,
0.2649534344673157,
-0.03632459044456482,
-0.031223980709910393,
0.10946926474571228,
0.02766943909227848,
0.0764886662364006,
0.1216123029589653,
0.04513183981180191,
-0.07511468976736069,
-0.0053597441874444485,
0.02343735098838806,
-0.02243741601705551,
-0.23315733671188354,
-0.03453785553574562,
-0.04087596386671066,
0.026037653908133507,
0.11341618746519089,
0.02590356580913067,
0.009017893113195896,
0.0800401046872139,
-0.008051341399550438,
0.0781310498714447,
-0.040242161601781845,
0.07397444546222687,
0.08308705687522888,
0.06171812117099762,
0.1247776672244072,
-0.008011222817003727,
-0.038396984338760376,
0.051023874431848526,
-0.045184243470430374,
0.2343176305294037,
-0.07392016798257828,
0.1852445900440216,
0.01930103451013565,
0.1941269040107727,
0.013104241341352463,
0.07552167028188705,
-0.018251173198223114,
0.012224690057337284,
-0.001303560216911137,
-0.05221475660800934,
-0.04963964223861694,
0.010083525441586971,
-0.03302374482154846,
0.07588841766119003,
-0.11768946796655655,
0.0008874483755789697,
0.04194515570998192,
0.24186880886554718,
0.07632429897785187,
-0.36339902877807617,
-0.09714236110448837,
-0.015115669928491116,
-0.000290668715024367,
-0.04106386750936508,
0.0125204436480999,
0.10981902480125427,
-0.10631048679351807,
0.023247161880135536,
-0.07764378190040588,
0.09260116517543793,
-0.07278279960155487,
0.015233220532536507,
0.04231065884232521,
0.0909615159034729,
-0.020212342962622643,
0.0732765644788742,
-0.24490973353385925,
0.24038027226924896,
0.009823324158787727,
0.06545654684305191,
-0.06177060306072235,
0.005017714574933052,
0.02709646336734295,
0.005819110199809074,
0.0809079110622406,
0.002840382046997547,
0.0007112083840183914,
-0.2042948454618454,
-0.12335105240345001,
0.002195226028561592,
0.07191479206085205,
-0.04664827138185501,
0.11744564026594162,
-0.004754084162414074,
-0.0038649661000818014,
0.029212314635515213,
0.0065523190423846245,
-0.054243192076683044,
-0.08173678815364838,
0.02422141283750534,
0.011936835944652557,
0.01587051898241043,
-0.06224863976240158,
-0.12192823737859726,
-0.08059483021497726,
0.15173637866973877,
-0.05582185089588165,
-0.07228096574544907,
-0.10809272527694702,
0.1131451353430748,
0.13518919050693512,
-0.09174184501171112,
0.024630334228277206,
0.010861799120903015,
0.08254797011613846,
0.02122095786035061,
-0.0720520168542862,
0.08381585776805878,
-0.04402313381433487,
-0.20923829078674316,
-0.06419096887111664,
0.12526023387908936,
0.04423757642507553,
0.06758245080709457,
-0.03348635137081146,
0.04146591201424599,
-0.03098234161734581,
-0.08703767508268356,
0.0360756553709507,
-0.0008935987716540694,
0.08817441016435623,
0.04873402789235115,
-0.02065272442996502,
0.03192874416708946,
-0.06100256368517876,
-0.017548510804772377,
0.1512039601802826,
0.2724354565143585,
-0.09413967281579971,
0.04147160053253174,
0.02552385814487934,
-0.06813234090805054,
-0.1582513451576233,
0.02118474803864956,
0.08303304016590118,
0.025643642991781235,
-0.014605664648115635,
-0.21311978995800018,
0.05969784036278725,
0.11698337644338608,
-0.011257356032729149,
0.11645740270614624,
-0.3593624532222748,
-0.11930473893880844,
0.06707931309938431,
0.10131525248289108,
0.11487535387277603,
-0.1557089239358902,
-0.0618545338511467,
-0.003760433290153742,
-0.14904865622520447,
0.09976845234632492,
-0.03762025758624077,
0.12667594850063324,
-0.0645950585603714,
0.06896974891424179,
0.021776266396045685,
-0.0689576044678688,
0.13031788170337677,
0.02894430048763752,
0.07135919481515884,
-0.05125240609049797,
-0.017589470371603966,
0.09673580527305603,
-0.05605004355311394,
0.030818691477179527,
-0.08569490164518356,
0.07164229452610016,
-0.14668330550193787,
-0.018879245966672897,
-0.08874721080064774,
0.02649889513850212,
-0.033443041145801544,
-0.04800810292363167,
-0.04630373418331146,
0.03760614991188049,
0.07408011704683304,
-0.005146408453583717,
0.09727112948894501,
0.04290240257978439,
0.14727777242660522,
0.0970393493771553,
0.03401314467191696,
-0.033510319888591766,
-0.08586917817592621,
-0.010941578075289726,
-0.005309329368174076,
0.0469466969370842,
-0.11912880837917328,
0.00766900135204196,
0.16867397725582123,
0.04378217086195946,
0.13520826399326324,
0.08132106810808182,
-0.0660240575671196,
0.030630696564912796,
0.041525378823280334,
-0.17594844102859497,
-0.07784439623355865,
-0.021565940231084824,
-0.05582301691174507,
-0.13201424479484558,
0.015060356818139553,
0.09694015979766846,
-0.07505495101213455,
-0.03490515425801277,
-0.009813392534852028,
0.024283982813358307,
-0.0035582655109465122,
0.2274780571460724,
0.04317242652177811,
0.06633895635604858,
-0.11841927468776703,
0.06775572150945663,
0.06648716330528259,
-0.05744506046175957,
0.031276095658540726,
0.07944692671298981,
-0.09281077980995178,
-0.009084044024348259,
0.07300366461277008,
0.15244655311107635,
-0.07405447959899902,
-0.010367955081164837,
-0.14679843187332153,
-0.08464743942022324,
0.0964696928858757,
0.12625788152217865,
0.08180811256170273,
0.04978414252400398,
-0.01412274595350027,
-0.022055942565202713,
-0.11389623582363129,
0.10252930223941803,
0.09162795543670654,
0.0745946392416954,
-0.12245607376098633,
0.16862386465072632,
-0.022891253232955933,
0.02493574284017086,
-0.010558689944446087,
0.02537444233894348,
-0.11470889300107956,
-0.008863206021487713,
-0.12883514165878296,
0.03588203713297844,
-0.07171912491321564,
-0.007047464605420828,
-0.02324194274842739,
-0.03213253989815712,
-0.05088186636567116,
0.024496635422110558,
-0.1014462560415268,
-0.05519270524382591,
0.0015458010602742434,
0.035444874316453934,
-0.13245351612567902,
-0.019055897369980812,
0.0073564364574849606,
-0.08285189419984818,
0.10448799282312393,
0.08108018338680267,
0.01770535483956337,
0.012747312895953655,
-0.06345213204622269,
-0.008977439254522324,
0.0037737637758255005,
0.00577177107334137,
0.05150560662150383,
-0.09759383648633957,
0.02310973033308983,
-0.018730968236923218,
-0.006173571106046438,
0.0260078776627779,
0.07065346837043762,
-0.14012053608894348,
-0.01999218948185444,
-0.006360960192978382,
-0.015204427763819695,
-0.07925498485565186,
0.059932366013526917,
0.09401386231184006,
0.009388985112309456,
0.1610085517168045,
-0.07880112528800964,
0.04817391559481621,
-0.22904206812381744,
-0.01479256059974432,
-0.004397546872496605,
-0.10317711532115936,
-0.09876400977373123,
-0.012947800569236279,
0.09183786064386368,
-0.0558399073779583,
0.1178390234708786,
-0.017645953223109245,
-0.002495109336450696,
0.007076311390846968,
-0.014988106675446033,
0.04453645646572113,
0.019948039203882217,
0.20658749341964722,
0.04279225692152977,
-0.056317996233701706,
0.057550545781850815,
0.03313746675848961,
0.08654556423425674,
0.12949460744857788,
0.16636675596237183,
0.0933288112282753,
0.03944088891148567,
0.07469158619642258,
0.0384272001683712,
-0.09208986908197403,
-0.1233753114938736,
0.048817094415426254,
-0.054581545293331146,
0.11216777563095093,
0.0016433614073321223,
0.21386750042438507,
0.08233251422643661,
-0.152699276804924,
0.0501411147415638,
-0.05073865130543709,
-0.09583820402622223,
-0.09740304946899414,
-0.08138897269964218,
-0.08208203315734863,
-0.14644049108028412,
0.017957504838705063,
-0.1374317854642868,
0.029101908206939697,
0.11700690537691116,
0.022953644394874573,
-0.008177057839930058,
0.0914001315832138,
0.0723075196146965,
0.004413416143506765,
0.056120794266462326,
0.014696963131427765,
-0.01694668084383011,
-0.04311036318540573,
-0.09103978425264359,
0.04628893733024597,
-0.025421805679798126,
0.06204315647482872,
-0.03437219560146332,
0.006282424088567495,
0.048615701496601105,
-0.004650287330150604,
-0.09685932099819183,
0.015070633962750435,
0.00004382890620036051,
0.0661962702870369,
0.06689183413982391,
0.01641613431274891,
0.01969914883375168,
-0.027917785570025444,
0.21024920046329498,
-0.05754482001066208,
-0.0255763940513134,
-0.11233298480510712,
0.22754321992397308,
0.03186807036399841,
-0.03745882958173752,
0.06061090901494026,
-0.09364897757768631,
0.003090054029598832,
0.19605018198490143,
0.2014564573764801,
-0.05532771348953247,
-0.031031426042318344,
0.02468131296336651,
-0.02426430769264698,
0.01688510552048683,
0.08187251538038254,
0.09785368293523788,
0.04513543099164963,
-0.09896347671747208,
-0.028187641873955727,
-0.05757594853639603,
-0.015640949830412865,
-0.03135523945093155,
0.07005695253610611,
0.010374912992119789,
0.0006591546698473394,
-0.05015704408288002,
0.03478039801120758,
-0.08458911627531052,
-0.08346370607614517,
0.050753191113471985,
-0.20618917047977448,
-0.18113327026367188,
-0.020342038944363594,
0.03363543003797531,
0.036384839564561844,
0.05624036863446236,
-0.008554509840905666,
0.02131763845682144,
0.0657467171549797,
-0.02488446608185768,
-0.11418252438306808,
-0.1049594134092331,
0.07211241126060486,
-0.08060595393180847,
0.18707256019115448,
-0.037706177681684494,
0.06530351936817169,
0.13180500268936157,
0.05250891298055649,
-0.13061895966529846,
0.03434242308139801,
0.06565152108669281,
-0.06037810444831848,
0.025920044630765915,
0.12625660002231598,
-0.016547907143831253,
0.0687825083732605,
0.03328720107674599,
-0.06222807243466377,
-0.018476760014891624,
-0.012498574331402779,
-0.009357014670968056,
-0.06579636037349701,
-0.05537916719913483,
-0.030346453189849854,
0.13897667825222015,
0.207087904214859,
-0.06497044116258621,
-0.007453423924744129,
-0.06270984560251236,
-0.009304308332502842,
0.05132098123431206,
0.04816637560725212,
-0.0329822413623333,
-0.2653957009315491,
0.008866329677402973,
0.061074014753103256,
0.02061571180820465,
-0.23860028386116028,
-0.06860415637493134,
0.00390103692188859,
-0.06420246511697769,
-0.08823928236961365,
0.11413854360580444,
0.04467277601361275,
0.06648004055023193,
-0.04810599982738495,
0.01720697246491909,
-0.08257438242435455,
0.1556212455034256,
-0.14322741329669952,
-0.10731494426727295
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Image_Captioner_Mimic
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0963
- Rouge1: 32.528
- Rouge2: 19.9922
- Rougel: 31.403
- Rougelsum: 31.9372
- Gen Len: 12.5584
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.0597 | 1.0 | 24457 | 0.0567 | 37.8657 | 27.8087 | 37.4596 | 37.752 | 9.9527 |
| 0.0533 | 2.0 | 48914 | 0.0526 | 39.2211 | 28.2036 | 38.5786 | 38.9976 | 10.7079 |
| 0.0507 | 3.0 | 73371 | 0.0499 | 39.3449 | 28.3875 | 38.7151 | 39.0449 | 10.2091 |
| 0.0457 | 4.0 | 97828 | 0.0479 | 39.8753 | 28.5 | 39.127 | 39.6178 | 11.2407 |
| 0.0419 | 5.0 | 122285 | 0.0461 | 40.0478 | 28.797 | 39.3201 | 39.7468 | 10.3153 |
| 0.0406 | 6.0 | 146742 | 0.0445 | 39.7923 | 28.4281 | 39.0583 | 39.4523 | 10.4186 |
| 0.0373 | 7.0 | 171199 | 0.0429 | 39.954 | 28.535 | 39.2226 | 39.6457 | 10.6640 |
| 0.0347 | 8.0 | 195656 | 0.0419 | 39.4329 | 28.0336 | 38.6815 | 39.0968 | 10.7775 |
| 0.031 | 9.0 | 220113 | 0.0411 | 39.4524 | 28.1057 | 38.6998 | 39.0906 | 10.8397 |
| 0.0286 | 10.0 | 244570 | 0.0407 | 39.1493 | 27.639 | 38.3784 | 38.8085 | 10.9530 |
| 0.0261 | 11.0 | 269027 | 0.0408 | 38.8083 | 27.2206 | 37.9679 | 38.422 | 11.2390 |
| 0.0249 | 12.0 | 293484 | 0.0412 | 38.3972 | 26.7316 | 37.5838 | 38.0409 | 11.4510 |
| 0.0214 | 13.0 | 317941 | 0.0424 | 37.785 | 26.3302 | 36.9553 | 37.3764 | 11.4482 |
| 0.0188 | 14.0 | 342398 | 0.0438 | 36.9552 | 25.3108 | 36.0278 | 36.4965 | 11.6232 |
| 0.0174 | 15.0 | 366855 | 0.0458 | 35.6476 | 23.9574 | 34.6526 | 35.1259 | 11.6605 |
| 0.0153 | 16.0 | 391312 | 0.0487 | 34.657 | 22.8337 | 33.5891 | 34.1343 | 12.2395 |
| 0.013 | 17.0 | 415769 | 0.0518 | 33.5548 | 21.1569 | 32.4899 | 33.0394 | 12.2604 |
| 0.0114 | 18.0 | 440226 | 0.0559 | 34.3809 | 22.0108 | 33.2698 | 33.8578 | 12.0861 |
| 0.01 | 19.0 | 464683 | 0.0601 | 32.9062 | 20.3145 | 31.8147 | 32.3802 | 12.5176 |
| 0.0081 | 20.0 | 489140 | 0.0651 | 32.9482 | 20.3862 | 31.865 | 32.3837 | 12.4577 |
| 0.0069 | 21.0 | 513597 | 0.0698 | 32.3054 | 19.764 | 31.2178 | 31.7592 | 12.4939 |
| 0.0057 | 22.0 | 538054 | 0.0751 | 31.7627 | 19.0106 | 30.6263 | 31.175 | 12.7530 |
| 0.0048 | 23.0 | 562511 | 0.0793 | 31.8295 | 19.255 | 30.6958 | 31.2314 | 12.6077 |
| 0.0041 | 24.0 | 586968 | 0.0834 | 32.1523 | 19.2017 | 30.9774 | 31.5383 | 12.7461 |
| 0.0032 | 25.0 | 611425 | 0.0870 | 32.5379 | 20.0041 | 31.3903 | 31.9037 | 12.6848 |
| 0.0025 | 26.0 | 635882 | 0.0903 | 32.6757 | 20.1388 | 31.5495 | 32.0827 | 12.5950 |
| 0.0023 | 27.0 | 660339 | 0.0927 | 32.0874 | 19.3546 | 30.9125 | 31.4675 | 12.6290 |
| 0.0019 | 28.0 | 684796 | 0.0947 | 32.6988 | 20.1847 | 31.5643 | 32.1143 | 12.5412 |
| 0.0017 | 29.0 | 709253 | 0.0958 | 32.4574 | 19.7702 | 31.2955 | 31.8608 | 12.5558 |
| 0.0014 | 30.0 | 733710 | 0.0963 | 32.528 | 19.9922 | 31.403 | 31.9372 | 12.5584 |
### Framework versions
- Transformers 4.37.1
- Pytorch 1.13.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.1
| {"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "Image_Captioner_Mimic", "results": []}]} | null | ChayanM/Image_Captioner_Mimic | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | 2024-02-11T07:33:57+00:00 | [] | [] | TAGS
#transformers #safetensors #vision-encoder-decoder #generated_from_trainer #endpoints_compatible #region-us
| Image\_Captioner\_Mimic
=======================
This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0963
* Rouge1: 32.528
* Rouge2: 19.9922
* Rougel: 31.403
* Rougelsum: 31.9372
* Gen Len: 12.5584
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30
### Training results
### Framework versions
* Transformers 4.37.1
* Pytorch 1.13.1+cu117
* Datasets 2.15.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.1\n* Pytorch 1.13.1+cu117\n* Datasets 2.15.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #safetensors #vision-encoder-decoder #generated_from_trainer #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.1\n* Pytorch 1.13.1+cu117\n* Datasets 2.15.0\n* Tokenizers 0.15.1"
] | [
37,
98,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #vision-encoder-decoder #generated_from_trainer #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30### Training results### Framework versions\n\n\n* Transformers 4.37.1\n* Pytorch 1.13.1+cu117\n* Datasets 2.15.0\n* Tokenizers 0.15.1"
] | [
-0.10855867713689804,
-0.00858139805495739,
-0.0006251870072446764,
0.10129912942647934,
0.20619811117649078,
0.02004164271056652,
0.11243978887796402,
0.06559620797634125,
-0.14605942368507385,
0.028839699923992157,
0.11454207450151443,
0.14212143421173096,
-0.0033048768527805805,
0.1143215149641037,
-0.07296603173017502,
-0.25386425852775574,
0.000060848979046568274,
0.050685495138168335,
-0.11042865365743637,
0.11461608856916428,
0.0917426124215126,
-0.16994445025920868,
0.09043344110250473,
-0.021052278578281403,
-0.26802772283554077,
0.028537755832076073,
0.026751484721899033,
-0.06784257292747498,
0.13073576986789703,
0.016833389177918434,
0.1706329584121704,
-0.017855742946267128,
0.10130798816680908,
-0.16800256073474884,
0.0065105631947517395,
0.08490626513957977,
0.01488395407795906,
0.051330357789993286,
0.056688342243433,
-0.006026587914675474,
0.08349542319774628,
-0.13055077195167542,
0.08541987836360931,
0.021208398044109344,
-0.15127433836460114,
-0.2519228160381317,
-0.06263407319784164,
-0.003431755816563964,
0.08775173127651215,
0.11020749062299728,
-0.003566995495930314,
0.150608628988266,
-0.09018434584140778,
0.11972688138484955,
0.25367775559425354,
-0.22887569665908813,
-0.08696090430021286,
0.03651579096913338,
-0.002467486308887601,
0.07740920782089233,
-0.13112083077430725,
-0.006882438901811838,
0.0843692496418953,
0.051907770335674286,
0.11914321035146713,
-0.0324183851480484,
-0.1315561980009079,
0.00224344152957201,
-0.14930269122123718,
-0.019514132291078568,
0.11385943740606308,
0.029832856729626656,
-0.027977915480732918,
-0.016205308958888054,
-0.08036544919013977,
-0.16774384677410126,
-0.055645547807216644,
-0.019972681999206543,
0.06023554503917694,
-0.06829065829515457,
-0.11910854279994965,
0.030725067481398582,
-0.11776949465274811,
-0.08630174398422241,
-0.044609878212213516,
0.21566228568553925,
0.041854795068502426,
0.03234308212995529,
-0.06424906849861145,
0.1073022186756134,
-0.013055379502475262,
-0.14816834032535553,
0.00898646004498005,
0.015319980680942535,
-0.013336117379367352,
-0.06052190437912941,
-0.08339071273803711,
-0.06397445499897003,
-0.020048169419169426,
0.11753338575363159,
-0.09898164868354797,
0.06324277818202972,
0.024001678451895714,
0.0363205261528492,
-0.11305411159992218,
0.2102789580821991,
-0.040959566831588745,
0.019810454919934273,
0.00011286293738521636,
0.036618661135435104,
0.0119591373950243,
0.008805514313280582,
-0.06941385567188263,
0.007004249840974808,
0.10086967051029205,
0.009947135113179684,
-0.11703336983919144,
0.06884560734033585,
-0.025032903999090195,
0.01385575719177723,
-0.018961017951369286,
-0.10050782561302185,
0.04242213815450668,
-0.006220420356839895,
-0.06724780052900314,
-0.011794175021350384,
0.037623316049575806,
0.0024599027819931507,
0.001987241208553314,
0.14061470329761505,
-0.08178531378507614,
0.05270007625222206,
-0.12515173852443695,
-0.10240098834037781,
-0.004918897524476051,
-0.022078776732087135,
0.044112928211688995,
-0.10956452041864395,
-0.14608539640903473,
-0.0017427894053980708,
0.05803144350647926,
-0.006155109964311123,
0.02913389541208744,
-0.04312300309538841,
-0.12625636160373688,
0.0033550821244716644,
-0.01736004836857319,
0.13055378198623657,
-0.05035463348031044,
0.1121472641825676,
0.10036833584308624,
0.07261551171541214,
-0.07287760078907013,
0.029950106516480446,
-0.09813740849494934,
0.009633074514567852,
-0.2753300368785858,
0.045497287064790726,
-0.044775303453207016,
0.0714639350771904,
-0.03576722741127014,
-0.12824401259422302,
0.022460173815488815,
0.009398840367794037,
0.09479521960020065,
0.09844201058149338,
-0.18219821155071259,
-0.06411100924015045,
0.14257104694843292,
-0.12302322685718536,
-0.13025447726249695,
0.09529764950275421,
-0.05174417421221733,
0.0071566905826330185,
0.07895764708518982,
0.15432555973529816,
0.03760752081871033,
-0.13662844896316528,
-0.007984617725014687,
-0.04108129069209099,
0.02345735765993595,
-0.04693160206079483,
0.040943462401628494,
0.04583244398236275,
0.02957320027053356,
0.02317061834037304,
-0.05496995151042938,
0.061407726258039474,
-0.13103827834129333,
-0.08276335895061493,
-0.06584440171718597,
-0.09867700934410095,
0.020881962031126022,
0.09151323139667511,
0.07516685128211975,
-0.13736498355865479,
-0.05459769442677498,
0.110377237200737,
0.06790713965892792,
-0.07890976220369339,
0.025465313345193863,
-0.062203627079725266,
0.017934689298272133,
-0.07260004431009293,
-0.0342419296503067,
-0.18385228514671326,
-0.049233146011829376,
-0.008403738029301167,
0.022504782304167747,
-0.013321801088750362,
-0.02170513942837715,
0.09411661326885223,
0.09362735599279404,
-0.08277226239442825,
-0.050003599375486374,
-0.06199901923537254,
0.0026139849796891212,
-0.1180221438407898,
-0.19176273047924042,
-0.025240032002329826,
-0.006358210928738117,
0.0629207193851471,
-0.2169332206249237,
0.022672707214951515,
0.01202896423637867,
0.1268579363822937,
0.03412368893623352,
-0.015115595422685146,
-0.07151762396097183,
0.10024242103099823,
-0.0038397167809307575,
-0.07747498899698257,
0.03241477906703949,
-0.016907403245568275,
-0.03746653348207474,
-0.060922909528017044,
-0.11759041994810104,
0.20581714808940887,
0.1581105887889862,
-0.17758437991142273,
-0.09450258314609528,
0.05965672433376312,
-0.062155697494745255,
-0.02116750180721283,
-0.05671375244855881,
0.024120105430483818,
0.16743707656860352,
-0.027626601979136467,
0.14461171627044678,
-0.07631752640008926,
-0.03647884726524353,
0.025686997920274734,
-0.04068674519658089,
0.029893193393945694,
0.08751358836889267,
0.06420866400003433,
-0.0956718921661377,
0.12681907415390015,
0.13720427453517914,
-0.09503152221441269,
0.12483062595129013,
-0.06191789731383324,
-0.0760689228773117,
-0.010991374962031841,
-0.015903718769550323,
0.0009948553051799536,
0.1606748253107071,
-0.10112620145082474,
-0.006943623069673777,
-0.019085150212049484,
0.025018813088536263,
0.032680634409189224,
-0.24632835388183594,
-0.03348734602332115,
0.021836381405591965,
-0.010545097291469574,
0.014412094838917255,
-0.022652726620435715,
0.028668925166130066,
0.0937066376209259,
-0.017239248380064964,
-0.05202319845557213,
0.03226060792803764,
-0.0077264802530407906,
-0.0675257071852684,
0.23239317536354065,
-0.0852179154753685,
-0.13006804883480072,
-0.11589210480451584,
-0.040328092873096466,
-0.0293428972363472,
0.01325964368879795,
0.06034228950738907,
-0.12799762189388275,
-0.04639225825667381,
-0.04598023369908333,
0.036285996437072754,
0.024791153147816658,
0.05299372598528862,
0.04523114860057831,
0.018671143800020218,
0.0841287225484848,
-0.11116298288106918,
-0.0090210922062397,
-0.06049496680498123,
-0.07211392372846603,
0.05197329446673393,
0.06208633631467819,
0.12170617282390594,
0.14219346642494202,
-0.0480487085878849,
0.01913595199584961,
-0.02346033975481987,
0.25919419527053833,
-0.10191299021244049,
-0.06999311596155167,
0.11863089352846146,
-0.013389418832957745,
0.03310607373714447,
0.09987898170948029,
0.06675656884908676,
-0.13612693548202515,
0.01717407815158367,
0.03484141454100609,
-0.030892668291926384,
-0.178191140294075,
-0.03210504353046417,
-0.03659779950976372,
-0.06363189220428467,
0.06372860819101334,
0.01184985414147377,
0.011309980414807796,
0.06213013455271721,
0.03052370250225067,
0.06934508681297302,
-0.03535447269678116,
0.07403022050857544,
0.09672290831804276,
0.038629110902547836,
0.10200712084770203,
-0.06166081503033638,
-0.08692638576030731,
0.00985272228717804,
-0.05987339839339256,
0.2367810606956482,
-0.017657345160841942,
0.02996603585779667,
0.05522940680384636,
0.13868437707424164,
0.0034484302159398794,
0.09109866619110107,
0.009841776452958584,
-0.08432038873434067,
0.014182853512465954,
-0.05548480525612831,
-0.041037555783987045,
0.014929849654436111,
-0.11359500885009766,
0.09061460942029953,
-0.13965405523777008,
0.01759696565568447,
0.08326178789138794,
0.25587257742881775,
0.044588226824998856,
-0.35463055968284607,
-0.07947474718093872,
-0.000059799986047437415,
-0.01755692809820175,
-0.03998051956295967,
0.01941480115056038,
0.15028847754001617,
-0.06536389887332916,
0.055107299238443375,
-0.06606005877256393,
0.07119103521108627,
-0.019984135404229164,
0.042388640344142914,
0.04973253607749939,
0.0960204228758812,
-0.0033128580544143915,
0.03369544446468353,
-0.30943381786346436,
0.28486180305480957,
0.01221447717398405,
0.14114166796207428,
-0.045122042298316956,
-0.019780410453677177,
0.01962204836308956,
0.09133915603160858,
0.039692677557468414,
-0.01869402453303337,
-0.04151281714439392,
-0.23137550055980682,
0.0007521493243984878,
0.047970399260520935,
0.1624491959810257,
0.02903500385582447,
0.10760737210512161,
-0.013554957695305347,
-0.002036063699051738,
0.08903118968009949,
-0.06037487834692001,
-0.09240126609802246,
-0.053674280643463135,
-0.04698188230395317,
0.025189371779561043,
0.012223717756569386,
-0.08852136880159378,
-0.09486822038888931,
-0.0814753845334053,
0.10454973578453064,
-0.005396679975092411,
-0.017672745510935783,
-0.1186140775680542,
0.09789161384105682,
0.08401831984519958,
-0.06055184453725815,
0.07185319811105728,
0.04211055114865303,
0.08891034871339798,
0.044127240777015686,
-0.06250148266553879,
0.10374517738819122,
-0.07114527374505997,
-0.16056564450263977,
-0.04347186163067818,
0.08782856166362762,
0.03366447985172272,
0.0186185073107481,
-0.014234719797968864,
0.025876520201563835,
0.005660769063979387,
-0.08593933284282684,
0.0187908373773098,
-0.026362860575318336,
0.07297814637422562,
0.06758830696344376,
-0.011935083195567131,
-0.008674309588968754,
-0.04794692620635033,
-0.005630803294479847,
0.13028042018413544,
0.25245752930641174,
-0.06955641508102417,
-0.06644237786531448,
0.048192594200372696,
-0.04575447738170624,
-0.1892032027244568,
0.12362198531627655,
0.0686347484588623,
-0.010016484186053276,
0.014611872844398022,
-0.1123550683259964,
0.1545606404542923,
0.0965024009346962,
-0.0027799459639936686,
0.11171313375234604,
-0.2981743812561035,
-0.13216769695281982,
0.08919499814510345,
0.2064586728811264,
0.1151626706123352,
-0.14925794303417206,
0.00516190892085433,
-0.0427708625793457,
-0.1585628092288971,
0.07371436804533005,
-0.0925932452082634,
0.11784393340349197,
-0.019729794934391975,
0.06301073729991913,
0.004318739287555218,
-0.0699462965130806,
0.11903619021177292,
-0.01121427770704031,
0.15829482674598694,
-0.05508111044764519,
-0.021931733936071396,
0.10777615755796432,
-0.04353008419275284,
-0.0009414617670699954,
0.01621462032198906,
0.0503309890627861,
-0.022794539108872414,
-0.012750038877129555,
-0.09075630456209183,
0.018755393102765083,
-0.0314551517367363,
-0.06482454389333725,
-0.035315148532390594,
0.01970811001956463,
0.0287859495729208,
-0.02576500177383423,
0.14615516364574432,
0.029503928497433662,
0.13214580714702606,
0.04702035337686539,
0.05312233418226242,
-0.0956696942448616,
-0.06310431659221649,
0.011591996066272259,
-0.015320824459195137,
0.07740309089422226,
-0.1466212272644043,
0.03333612158894539,
0.13097409904003143,
0.032850731164216995,
0.11872172355651855,
0.1053045317530632,
-0.012198256328701973,
0.0244879312813282,
0.08005550503730774,
-0.15885135531425476,
-0.07648933678865433,
-0.002115825191140175,
-0.040277499705553055,
-0.06754978001117706,
0.10795940458774567,
0.08299069851636887,
-0.09513076394796371,
0.016925115138292313,
-0.03958936408162117,
-0.0201178640127182,
-0.0752769485116005,
0.21132850646972656,
0.07180745899677277,
0.05392468720674515,
-0.1172429695725441,
0.09547163546085358,
0.01309121586382389,
-0.09577053785324097,
0.0019764036405831575,
0.07563402503728867,
-0.07085257023572922,
-0.011400988325476646,
0.12154436856508255,
0.20482663810253143,
-0.0653320699930191,
-0.05528293177485466,
-0.15310245752334595,
-0.1211690902709961,
0.05753489211201668,
0.2480207234621048,
0.10348339378833771,
0.009969419799745083,
-0.02037867344915867,
0.050410639494657516,
-0.16809986531734467,
0.06755667924880981,
0.009382855147123337,
0.0945567786693573,
-0.1755857914686203,
0.19004207849502563,
0.0138125941157341,
0.028290951624512672,
-0.03527658432722092,
0.04017163813114166,
-0.13264252245426178,
0.0375179797410965,
-0.11570856720209122,
-0.03988265618681908,
0.008882596157491207,
-0.0006535813445225358,
0.0036030185874551535,
-0.0647333413362503,
-0.08519814163446426,
0.0456508994102478,
-0.10849897563457489,
-0.013644195161759853,
0.05907692760229111,
0.01493437122553587,
-0.12677039206027985,
-0.04810060188174248,
0.015544925816357136,
-0.07564520835876465,
0.023935381323099136,
0.0678679496049881,
0.00953533872961998,
0.07968798279762268,
-0.19367121160030365,
-0.045600809156894684,
0.11129960417747498,
-0.02200314961373806,
0.07671663910150528,
-0.04158500209450722,
-0.011334306560456753,
0.001402058289386332,
0.10904781520366669,
0.01937529817223549,
0.08139286190271378,
-0.12566223740577698,
0.00025211498723365366,
-0.040566377341747284,
-0.06341007351875305,
-0.05987611413002014,
0.016016190871596336,
0.08768424391746521,
0.0026131283957511187,
0.16461578011512756,
-0.09806884825229645,
0.02952718175947666,
-0.20440272986888885,
-0.01955367438495159,
-0.015128359198570251,
-0.12382837384939194,
-0.09048742800951004,
-0.02858576364815235,
0.07954411208629608,
-0.06120936572551727,
0.13320598006248474,
0.0021241342183202505,
0.08786267787218094,
0.04524083808064461,
-0.036822229623794556,
-0.015138469636440277,
0.0608481764793396,
0.24707958102226257,
0.02904827520251274,
-0.038962770253419876,
0.0771455243229866,
0.09599070996046066,
0.13983651995658875,
0.09691547602415085,
0.18690624833106995,
0.1682191640138626,
-0.08888779580593109,
0.1287619024515152,
0.02762211114168167,
-0.04210259020328522,
-0.1271767020225525,
-0.0026235124096274376,
-0.061981890350580215,
0.07006502151489258,
-0.03163115680217743,
0.14696210622787476,
0.10182750970125198,
-0.15749837458133698,
0.03366560861468315,
-0.06230791285634041,
-0.08728604763746262,
-0.0741444006562233,
0.059700675308704376,
-0.09242983907461166,
-0.16984842717647552,
0.03609165549278259,
-0.12254668772220612,
0.020590974017977715,
0.147523432970047,
0.008543744683265686,
-0.008379523642361164,
0.26282167434692383,
0.0633050724864006,
0.05215316638350487,
0.05859965458512306,
0.0003501244354993105,
-0.01963994652032852,
-0.060921262949705124,
-0.05980561301112175,
0.009520855732262135,
-0.046147823333740234,
0.0238779466599226,
-0.055551398545503616,
-0.10696297883987427,
0.04347064718604088,
0.010067124851047993,
-0.0999966561794281,
0.036390434950590134,
0.042502470314502716,
0.058333393186330795,
-0.003916448447853327,
0.002101559890434146,
0.011127980425953865,
-0.025885796174407005,
0.23323199152946472,
-0.09923595190048218,
-0.1161436066031456,
-0.09351135045289993,
0.24988755583763123,
0.06274478137493134,
0.02850678563117981,
0.012725019827485085,
-0.10198353976011276,
-0.0032549328170716763,
0.20612461864948273,
0.11930568516254425,
-0.07597415149211884,
-0.006356614641845226,
-0.02274351194500923,
-0.01635151542723179,
-0.06943869590759277,
0.11812865734100342,
0.13848312199115753,
0.04871983453631401,
-0.10196775943040848,
-0.045600008219480515,
-0.03933095932006836,
-0.02231779880821705,
-0.03230429068207741,
0.01121524441987276,
0.04043491557240486,
0.016451330855488777,
-0.06065141037106514,
0.064461849629879,
-0.02478964813053608,
-0.09399450570344925,
0.12773075699806213,
-0.21192578971385956,
-0.13120511174201965,
-0.0060624731704592705,
0.13160736858844757,
-0.020953061059117317,
0.06586627662181854,
-0.02770032361149788,
-0.01940084435045719,
0.04207223281264305,
-0.014750408008694649,
-0.056257013231515884,
-0.11936130374670029,
0.051236342638731,
-0.15378674864768982,
0.20829465985298157,
-0.04453037679195404,
0.07801502197980881,
0.1189083680510521,
0.045735374093055725,
-0.07104335725307465,
0.07129918038845062,
0.019493846222758293,
-0.1401245892047882,
-0.0011432934552431107,
0.14693871140480042,
-0.052641380578279495,
0.06815531849861145,
0.01829596236348152,
-0.18567633628845215,
0.02606256492435932,
-0.030375421047210693,
-0.038800280541181564,
-0.04221494868397713,
-0.07811885327100754,
-0.06011154502630234,
0.09867886453866959,
0.1998519003391266,
-0.018833309412002563,
0.04757099971175194,
-0.08136532455682755,
0.03897731751203537,
0.07541985809803009,
0.037915363907814026,
-0.04909539595246315,
-0.2720383405685425,
0.030965229496359825,
0.1204347088932991,
-0.05365853011608124,
-0.2064717561006546,
-0.09161471575498581,
0.025528961792588234,
-0.08226677775382996,
-0.07312101870775223,
0.06780590116977692,
0.10266035795211792,
0.06006305664777756,
-0.05696389451622963,
-0.15045040845870972,
-0.07195519655942917,
0.1834418624639511,
-0.1408838927745819,
-0.11207175254821777
] |
null | null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# first_train
This model is a fine-tuned version of [cognitivecomputations/dolphin-2.6-mistral-7b](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b) on the generator dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
### Training results
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1 | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "cognitivecomputations/dolphin-2.6-mistral-7b", "model-index": [{"name": "first_train", "results": []}]} | null | theyoffa/first_train | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:cognitivecomputations/dolphin-2.6-mistral-7b",
"license:apache-2.0",
"region:us"
] | 2024-02-11T07:36:28+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-cognitivecomputations/dolphin-2.6-mistral-7b #license-apache-2.0 #region-us
|
# first_train
This model is a fine-tuned version of cognitivecomputations/dolphin-2.6-mistral-7b on the generator dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
### Training results
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1 | [
"# first_train\n\nThis model is a fine-tuned version of cognitivecomputations/dolphin-2.6-mistral-7b on the generator dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 0.0002\n- train_batch_size: 3\n- eval_batch_size: 8\n- seed: 42\n- gradient_accumulation_steps: 2\n- total_train_batch_size: 6\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: constant\n- lr_scheduler_warmup_ratio: 0.03\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- PEFT 0.8.2\n- Transformers 4.37.2\n- Pytorch 2.2.0+cu121\n- Datasets 2.17.0\n- Tokenizers 0.15.1"
] | [
"TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-cognitivecomputations/dolphin-2.6-mistral-7b #license-apache-2.0 #region-us \n",
"# first_train\n\nThis model is a fine-tuned version of cognitivecomputations/dolphin-2.6-mistral-7b on the generator dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 0.0002\n- train_batch_size: 3\n- eval_batch_size: 8\n- seed: 42\n- gradient_accumulation_steps: 2\n- total_train_batch_size: 6\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: constant\n- lr_scheduler_warmup_ratio: 0.03\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- PEFT 0.8.2\n- Transformers 4.37.2\n- Pytorch 2.2.0+cu121\n- Datasets 2.17.0\n- Tokenizers 0.15.1"
] | [
66,
36,
6,
12,
8,
3,
128,
4,
39
] | [
"passage: TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-cognitivecomputations/dolphin-2.6-mistral-7b #license-apache-2.0 #region-us \n# first_train\n\nThis model is a fine-tuned version of cognitivecomputations/dolphin-2.6-mistral-7b on the generator dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 0.0002\n- train_batch_size: 3\n- eval_batch_size: 8\n- seed: 42\n- gradient_accumulation_steps: 2\n- total_train_batch_size: 6\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: constant\n- lr_scheduler_warmup_ratio: 0.03\n- num_epochs: 3### Training results### Framework versions\n\n- PEFT 0.8.2\n- Transformers 4.37.2\n- Pytorch 2.2.0+cu121\n- Datasets 2.17.0\n- Tokenizers 0.15.1"
] | [
-0.07333319634199142,
0.16819830238819122,
-0.003778584534302354,
0.0560295395553112,
0.14015178382396698,
0.025830157101154327,
0.11782120168209076,
0.1392616480588913,
-0.07132343202829361,
0.09541266411542892,
0.034768637269735336,
0.05552477017045021,
0.07928143441677094,
0.1122121661901474,
-0.022686278447508812,
-0.24607320129871368,
0.02554203011095524,
-0.010432789102196693,
-0.058074627071619034,
0.10452283173799515,
0.09014267474412918,
-0.10101821273565292,
0.0470123291015625,
0.00030111780506558716,
-0.12782417237758636,
-0.00933244451880455,
-0.03826736658811569,
-0.04428241401910782,
0.09255462139844894,
-0.027972571551799774,
0.12346029281616211,
0.02217661216855049,
0.15072299540042877,
-0.20841668546199799,
0.002836250700056553,
0.09974408894777298,
0.04683350399136543,
0.09800026565790176,
0.09732720255851746,
-0.00734646525233984,
0.08152659982442856,
-0.14383789896965027,
0.12950001657009125,
0.00038761369069106877,
-0.09287463128566742,
-0.1897159218788147,
-0.12512783706188202,
0.04144306853413582,
0.13418230414390564,
0.07880245894193649,
0.0005548116751015186,
0.1602102518081665,
-0.06390286982059479,
0.07083699107170105,
0.2237221598625183,
-0.25930118560791016,
-0.08124031871557236,
0.057399850338697433,
0.009463370777666569,
0.06581564247608185,
-0.08659964799880981,
-0.01646468974649906,
0.03269956633448601,
0.029906287789344788,
0.04047189652919769,
0.017585618421435356,
-0.04761584475636482,
-0.025078104808926582,
-0.1367141753435135,
0.005918907001614571,
0.09763000160455704,
0.04017995297908783,
-0.03889806568622589,
-0.08200703561306,
-0.07228061556816101,
-0.13401775062084198,
-0.027394955977797508,
-0.025457141920924187,
0.0507308728992939,
-0.055544111877679825,
-0.01114465482532978,
-0.02846810407936573,
-0.06821275502443314,
-0.06180095300078392,
-0.009506158530712128,
0.14657346904277802,
0.04812374338507652,
0.028827210888266563,
-0.037504374980926514,
0.11635012924671173,
0.023232245817780495,
-0.11899017542600632,
0.013590310700237751,
0.01856195367872715,
-0.09241316467523575,
-0.07063218951225281,
-0.037096649408340454,
-0.08223675936460495,
-0.017725525423884392,
0.13784447312355042,
-0.023677246645092964,
0.08901681005954742,
-0.023452257737517357,
0.0014013299951329827,
-0.03872712329030037,
0.1621929109096527,
-0.08084358274936676,
-0.02561875805258751,
0.012947619892656803,
0.13022206723690033,
0.025397617369890213,
-0.01794419437646866,
-0.08525749295949936,
0.0007519641076214612,
0.07208190113306046,
0.06397503614425659,
-0.02847236581146717,
0.0036608760710805655,
-0.028389940038323402,
-0.03604579344391823,
0.029950015246868134,
-0.13637354969978333,
0.05535373091697693,
0.029691161587834358,
-0.09279704838991165,
0.020924249663949013,
0.02221665158867836,
0.022249212488532066,
-0.0036615582648664713,
0.1338132917881012,
-0.058988504111766815,
0.01702265813946724,
-0.08741296827793121,
-0.05526100844144821,
0.02471204474568367,
-0.05009588971734047,
-0.017883015796542168,
-0.06274116784334183,
-0.17323251068592072,
-0.03860653191804886,
0.06417261064052582,
-0.10567265748977661,
-0.031012585386633873,
-0.01146989967674017,
-0.09065999835729599,
0.011270400136709213,
-0.005535599309951067,
0.15890927612781525,
-0.0411851741373539,
0.07458677142858505,
-0.011909738183021545,
0.0363331139087677,
0.030994897708296776,
0.017447205260396004,
-0.06537216901779175,
0.02615867182612419,
-0.15744473040103912,
0.06291826069355011,
-0.06092488393187523,
0.01865408942103386,
-0.12348700314760208,
-0.08492019772529602,
-0.03276366367936134,
-0.042761508375406265,
0.07884158939123154,
0.0948353111743927,
-0.23904281854629517,
0.0014347955584526062,
0.15499860048294067,
-0.07947568595409393,
-0.06823624670505524,
0.09838709235191345,
-0.04131321981549263,
0.04611486569046974,
0.0648118108510971,
0.13414064049720764,
0.03202502429485321,
-0.15717270970344543,
0.02306290715932846,
-0.04504162818193436,
0.09962528198957443,
0.08052467554807663,
0.0628158450126648,
0.0062727429904043674,
0.06968650966882706,
-0.004399353638291359,
-0.11756902188062668,
0.019488345831632614,
-0.06595734506845474,
-0.07857414335012436,
-0.032969385385513306,
-0.08883384615182877,
0.025186093524098396,
0.03625296428799629,
0.031138025224208832,
-0.05742917209863663,
-0.12991537153720856,
0.09268175065517426,
0.12434493005275726,
-0.06050397455692291,
0.028740353882312775,
-0.07073512673377991,
0.06670860201120377,
-0.03402550145983696,
-0.024793125689029694,
-0.19739672541618347,
-0.09791842103004456,
0.04531603306531906,
-0.0851229801774025,
0.014203892089426517,
0.00047077020280994475,
0.07817639410495758,
0.07666268199682236,
-0.05164620280265808,
-0.009252280928194523,
-0.07463196665048599,
0.01007908210158348,
-0.0972592756152153,
-0.20072203874588013,
-0.023853104561567307,
-0.02502973936498165,
0.19103345274925232,
-0.20800897479057312,
0.019946925342082977,
0.025664862245321274,
0.18497422337532043,
0.018166204914450645,
-0.07529780268669128,
-0.023348307237029076,
0.01821475476026535,
0.0005347717669792473,
-0.10485516488552094,
0.04326091334223747,
0.0006923446198925376,
-0.057618629187345505,
-0.04922058433294296,
-0.184868723154068,
0.011244552209973335,
0.10155286639928818,
0.0859830379486084,
-0.1089293360710144,
0.03392304480075836,
-0.057693686336278915,
-0.03785671293735504,
-0.07176565378904343,
0.007264989893883467,
0.18985706567764282,
0.04916111379861832,
0.12243647128343582,
-0.08854563534259796,
-0.07672283798456192,
0.009023473598062992,
0.0040352302603423595,
0.008423718623816967,
0.06996238976716995,
0.05479666590690613,
-0.10379229485988617,
0.0860593318939209,
0.07170848548412323,
-0.04907434433698654,
0.0777800902724266,
-0.0421912856400013,
-0.10568395256996155,
-0.03007851541042328,
0.029386421665549278,
0.0035452477168291807,
0.147810697555542,
-0.019295064732432365,
0.01629914529621601,
0.028435735031962395,
0.03372063487768173,
0.025815516710281372,
-0.21354039013385773,
0.0006854776875115931,
0.03435683995485306,
-0.0201830193400383,
0.012299205176532269,
-0.048315614461898804,
0.0424027293920517,
0.10387244820594788,
0.018111757934093475,
-0.032345615327358246,
0.0015375172952190042,
-0.019829344004392624,
-0.0821983739733696,
0.1703541874885559,
-0.10081682354211807,
-0.1459122747182846,
-0.0946241170167923,
0.03201981633901596,
-0.009299742989242077,
-0.045189592987298965,
-0.014509443193674088,
-0.09535334259271622,
-0.056917786598205566,
-0.08854274451732635,
-0.031209759414196014,
0.0029501912649720907,
-0.010762229561805725,
0.10919442772865295,
-0.0055135865695774555,
0.09006643295288086,
-0.11610827594995499,
0.019135836511850357,
-0.036585237830877304,
-0.0742751881480217,
-0.01736016385257244,
0.07875759899616241,
0.0654246062040329,
0.17207403481006622,
-0.044876422733068466,
0.02183511108160019,
-0.016641946509480476,
0.24111643433570862,
-0.09904029965400696,
0.02295518107712269,
0.10107023268938065,
-0.037076834589242935,
0.04679485037922859,
0.12541510164737701,
0.04283322021365166,
-0.10938522964715958,
0.022071247920393944,
0.08208508044481277,
-0.03278905153274536,
-0.2538895308971405,
-0.018531721085309982,
0.005937596317380667,
-0.0866260752081871,
0.08684483915567398,
0.04680391401052475,
0.019184855744242668,
0.023802202194929123,
-0.007708702702075243,
0.0014311629347503185,
0.038952723145484924,
0.09550537914037704,
0.04931456595659256,
0.03468894213438034,
0.090789295732975,
-0.02250535786151886,
-0.030639782547950745,
0.03168032318353653,
0.051460713148117065,
0.21743662655353546,
-0.011485046707093716,
0.1114850714802742,
0.011581278406083584,
0.07719650119543076,
-0.04508376121520996,
0.040362611413002014,
-0.02172817476093769,
-0.008661779575049877,
-0.005089642945677042,
-0.06615286320447922,
-0.019184425473213196,
0.018633829429745674,
-0.03317345678806305,
0.06943053752183914,
-0.04061417654156685,
0.036568090319633484,
0.04489641636610031,
0.24999472498893738,
0.006605992559343576,
-0.26143142580986023,
-0.031894635409116745,
0.013046517968177795,
-0.034390851855278015,
-0.0476161390542984,
-0.005783617962151766,
0.10258736461400986,
-0.10643021762371063,
0.05193210020661354,
-0.08634650707244873,
0.08102075755596161,
-0.03914931043982506,
-0.019613519310951233,
0.11189724504947662,
0.08750086277723312,
0.023730019107460976,
0.046961624175310135,
-0.136373832821846,
0.19621005654335022,
0.012795895338058472,
0.12032104283571243,
-0.04293982684612274,
0.04881653934717178,
0.0030981358140707016,
0.052059367299079895,
0.08014055341482162,
-0.0033025676384568214,
-0.0691450834274292,
-0.16279755532741547,
-0.1180320754647255,
0.011557742021977901,
0.11475889384746552,
-0.041169073432683945,
0.09544238448143005,
-0.03614098206162453,
-0.017922133207321167,
0.03078785538673401,
-0.07579344511032104,
-0.10715650022029877,
-0.12074273824691772,
0.04036884754896164,
-0.038509514182806015,
-0.05416364222764969,
-0.08584898710250854,
-0.1149660274386406,
-0.11165600270032883,
0.11387770622968674,
-0.027280615642666817,
-0.04742870479822159,
-0.12400782853364944,
0.05051742121577263,
0.14276617765426636,
-0.03422050550580025,
0.002070733578875661,
0.00949198380112648,
0.1394387185573578,
0.026840340346097946,
-0.06506399065256119,
0.036939945071935654,
-0.06179184094071388,
-0.21504902839660645,
-0.07724950462579727,
0.1510072946548462,
0.048476118594408035,
0.06661068648099899,
-0.0148646654561162,
0.04819571599364281,
0.03887471556663513,
-0.06868181377649307,
0.00861525908112526,
0.07039058953523636,
0.07262145727872849,
-0.0005832677707076073,
-0.04696018621325493,
0.05030474066734314,
-0.08189422637224197,
0.0005306035745888948,
0.0863712951540947,
0.22032344341278076,
-0.07388235628604889,
0.08355766534805298,
0.03976195678114891,
-0.0860881507396698,
-0.1453029066324234,
0.0842958614230156,
0.13127177953720093,
-0.016121018677949905,
0.042432159185409546,
-0.1823473572731018,
0.1179366484284401,
0.13344432413578033,
-0.036283716559410095,
0.06180686876177788,
-0.34514349699020386,
-0.12974998354911804,
0.05070530250668526,
0.12202438712120056,
-0.03135151043534279,
-0.18885374069213867,
-0.033622417598962784,
-0.010162495076656342,
-0.16957175731658936,
0.15233173966407776,
-0.09806462377309799,
0.07933756709098816,
0.025951068848371506,
0.10724634677171707,
0.03024371527135372,
-0.051153991371393204,
0.16836729645729065,
-0.0053741647861897945,
0.060739804059267044,
-0.02547805942595005,
-0.005054037552326918,
0.06656579673290253,
-0.06537429988384247,
0.025602253153920174,
0.019355738535523415,
0.030827779322862625,
-0.08295201510190964,
-0.011471751146018505,
-0.08607165515422821,
0.006868816912174225,
-0.06384831666946411,
-0.04394582286477089,
-0.03031861037015915,
0.06443645060062408,
0.09147799015045166,
-0.036218076944351196,
0.08321704715490341,
0.031444087624549866,
0.09854479134082794,
0.07903096079826355,
0.07249964773654938,
0.005770415998995304,
-0.12205705791711807,
0.0035336327273398638,
-0.013942902907729149,
0.03621523082256317,
-0.1240336149930954,
0.024353301152586937,
0.12809300422668457,
0.03458140045404434,
0.12677349150180817,
0.03295590355992317,
-0.10104988515377045,
-0.0388229563832283,
0.01958293840289116,
-0.07957399636507034,
-0.12210942804813385,
0.043063659220933914,
0.07670567184686661,
-0.1127815842628479,
0.00020372634753584862,
0.1024765893816948,
-0.04236006736755371,
-0.036459214985370636,
0.014219407923519611,
0.039263367652893066,
0.0020848996937274933,
0.16771410405635834,
0.03478601574897766,
0.06502445787191391,
-0.09243234992027283,
0.12023862451314926,
0.08378172665834427,
-0.08969239890575409,
0.04505764693021774,
0.07610394060611725,
-0.07194105535745621,
0.00855069700628519,
0.056289345026016235,
0.13392922282218933,
0.02205611765384674,
-0.0326058566570282,
-0.10396908968687057,
-0.10374655574560165,
0.02011820301413536,
0.14617258310317993,
0.044925373047590256,
-0.008778083138167858,
-0.019019093364477158,
0.04761146381497383,
-0.16378960013389587,
0.10958120226860046,
0.022492431104183197,
0.08296074718236923,
-0.1474982500076294,
0.1077033206820488,
0.017613284289836884,
-0.016738997772336006,
-0.00629059411585331,
0.03757055103778839,
-0.06777384877204895,
-0.008730808272957802,
-0.09644155949354172,
0.016330501064658165,
-0.03635542094707489,
0.0005839518853463233,
0.0003131359990220517,
-0.03962131217122078,
-0.04078086093068123,
0.030229642987251282,
-0.08595652133226395,
-0.05565227195620537,
-0.00028377879061736166,
0.002835680963471532,
-0.11728566139936447,
-0.024610696360468864,
0.01991075649857521,
-0.11804044246673584,
0.05057893320918083,
0.052681129425764084,
0.046007052063941956,
0.04579200595617294,
-0.126161128282547,
-0.007256174925714731,
0.0349147729575634,
0.02248326689004898,
0.06340324878692627,
-0.16172142326831818,
-0.01716262474656105,
-0.03166212514042854,
0.04166186973452568,
0.02165391854941845,
0.06456304341554642,
-0.13412539660930634,
-0.02636491321027279,
-0.051027193665504456,
-0.06319926679134369,
-0.027812138199806213,
0.012296796776354313,
0.0912766382098198,
0.04509503394365311,
0.1581614762544632,
-0.07887853682041168,
0.07208431512117386,
-0.19871151447296143,
-0.028349360451102257,
-0.012641347013413906,
-0.009658790193498135,
-0.09861744940280914,
0.005307662300765514,
0.07695697247982025,
-0.062289994210004807,
0.11020905524492264,
-0.004639104474335909,
0.08128714561462402,
0.055291708558797836,
-0.0367140956223011,
-0.03252743184566498,
0.049409445375204086,
0.12329389899969101,
0.04247153550386429,
-0.004384375177323818,
0.07600168883800507,
-0.02409220300614834,
0.047012489289045334,
-0.010113697499036789,
0.1898583471775055,
0.15692394971847534,
0.03528381884098053,
0.06242777407169342,
0.06516902148723602,
-0.10508270561695099,
-0.13423319160938263,
0.151119664311409,
-0.07707227766513824,
0.09099996089935303,
-0.053111955523490906,
0.21793003380298615,
0.09315687417984009,
-0.1706017404794693,
0.03234914317727089,
-0.07899004220962524,
-0.0959649309515953,
-0.1307758241891861,
-0.013123400509357452,
-0.06474287062883377,
-0.09057767689228058,
0.017002679407596588,
-0.10460219532251358,
0.033385660499334335,
0.08445152640342712,
0.012483167462050915,
0.008888443000614643,
0.1528279036283493,
-0.02209438383579254,
0.02695538103580475,
0.03221340849995613,
0.05925527587532997,
-0.003566952422261238,
-0.04242594912648201,
-0.0775151252746582,
0.04735908657312393,
0.021658292040228844,
0.0869649201631546,
-0.03314337506890297,
0.003512569237500429,
0.01667550951242447,
0.010187833569943905,
-0.08261080831289291,
0.05026688799262047,
0.001081025693565607,
0.05328778550028801,
0.039458826184272766,
0.03884626924991608,
0.019744668155908585,
-0.0586567297577858,
0.25144392251968384,
-0.06509146839380264,
-0.07353616505861282,
-0.15285281836986542,
0.19989046454429626,
-0.0021305487025529146,
0.01084129698574543,
0.0734817385673523,
-0.13306842744350433,
-0.03742237389087677,
0.13746826350688934,
0.10567530244588852,
-0.06331313401460648,
-0.03701060265302658,
0.02297423779964447,
-0.017718544229865074,
-0.08431355655193329,
0.08935615420341492,
0.12118081748485565,
0.01421095710247755,
-0.05360540747642517,
-0.00396960973739624,
-0.010104862041771412,
-0.04226382449269295,
-0.07272694259881973,
0.05536384508013725,
0.0038818279281258583,
0.04338584840297699,
-0.05700458213686943,
0.07646902650594711,
0.018588462844491005,
-0.23786833882331848,
0.07536575198173523,
-0.2207941859960556,
-0.19850493967533112,
-0.0016935223247855902,
0.09332399070262909,
-0.052757859230041504,
0.06110268831253052,
0.000015106646969798021,
-0.03665059059858322,
0.1289624571800232,
-0.014540866017341614,
-0.018923675641417503,
-0.08432687819004059,
0.06806135177612305,
-0.13595108687877655,
0.2754669785499573,
-0.009676146320998669,
0.07023003697395325,
0.09079792350530624,
0.007847927510738373,
-0.14520645141601562,
0.005987153388559818,
0.08581389486789703,
-0.09225159138441086,
0.0032210543286055326,
0.19934655725955963,
-0.04803367331624031,
0.10511932522058487,
0.06968269497156143,
-0.14798949658870697,
-0.018511148169636726,
-0.04131265729665756,
-0.04351368546485901,
-0.07698207348585129,
0.0023486388381570578,
-0.07111406326293945,
0.1428063064813614,
0.20398476719856262,
-0.034104906022548676,
0.03689230978488922,
-0.06145254895091057,
-0.003998874686658382,
0.04784127324819565,
0.11063510179519653,
-0.025418002158403397,
-0.23919938504695892,
0.025294512510299683,
-0.005120063200592995,
0.04738833010196686,
-0.23073217272758484,
-0.09379003196954727,
0.057831063866615295,
-0.06616517156362534,
-0.08225076645612717,
0.08620593696832657,
0.03294738009572029,
0.03705944865942001,
-0.042016174644231796,
-0.12100668251514435,
-0.04353125020861626,
0.1558360755443573,
-0.1492484211921692,
-0.029980938881635666
] |
null | null | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
Install the RL Zoo (with SB3 and SB3-Contrib):
```bash
pip install rl_zoo3
```
```
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga tahsinkheya -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
```
If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
```
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga tahsinkheya -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
```
## Training (with the RL Zoo)
```
python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga tahsinkheya
```
## Hyperparameters
```python
OrderedDict([('batch_size', 32),
('buffer_size', 100000),
('env_wrapper',
['stable_baselines3.common.atari_wrappers.AtariWrapper']),
('exploration_final_eps', 0.01),
('exploration_fraction', 0.1),
('frame_stack', 4),
('gradient_steps', 1),
('learning_rate', 0.0001),
('learning_starts', 100000),
('n_timesteps', 1000000.0),
('optimize_memory_usage', False),
('policy', 'CnnPolicy'),
('target_update_interval', 1000),
('train_freq', 4),
('normalize', False)])
```
# Environment Arguments
```python
{'render_mode': 'rgb_array'}
```
| {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFrameskip-v4", "type": "SpaceInvadersNoFrameskip-v4"}, "metrics": [{"type": "mean_reward", "value": "618.00 +/- 138.01", "name": "mean_reward", "verified": false}]}]}]} | reinforcement-learning | tahsinkheya/dqn-spaceincader | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | 2024-02-11T07:42:07+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL Zoo: URL
SB3: URL
SB3 Contrib: URL
Install the RL Zoo (with SB3 and SB3-Contrib):
If you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:
## Training (with the RL Zoo)
## Hyperparameters
# Environment Arguments
| [
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage (with SB3 RL Zoo)\n\nRL Zoo: URL\nSB3: URL\nSB3 Contrib: URL\n\nInstall the RL Zoo (with SB3 and SB3-Contrib):\n\n\n\n\nIf you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:",
"## Training (with the RL Zoo)",
"## Hyperparameters",
"# Environment Arguments"
] | [
"TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage (with SB3 RL Zoo)\n\nRL Zoo: URL\nSB3: URL\nSB3 Contrib: URL\n\nInstall the RL Zoo (with SB3 and SB3-Contrib):\n\n\n\n\nIf you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:",
"## Training (with the RL Zoo)",
"## Hyperparameters",
"# Environment Arguments"
] | [
43,
90,
73,
9,
5,
7
] | [
"passage: TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.## Usage (with SB3 RL Zoo)\n\nRL Zoo: URL\nSB3: URL\nSB3 Contrib: URL\n\nInstall the RL Zoo (with SB3 and SB3-Contrib):\n\n\n\n\nIf you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:## Training (with the RL Zoo)## Hyperparameters# Environment Arguments"
] | [
0.043572068214416504,
0.2414778620004654,
-0.0026879787910729647,
0.012635791674256325,
0.05784223601222038,
0.0030472534708678722,
0.08585051447153091,
0.10650663822889328,
0.024212315678596497,
-0.001382096204906702,
0.003954293206334114,
0.17533031105995178,
0.03632635250687599,
0.13125447928905487,
-0.018073517829179764,
-0.2066594809293747,
-0.013479253277182579,
-0.06247470900416374,
-0.07153085619211197,
0.036099132150411606,
0.07206681370735168,
-0.030116932466626167,
0.036061208695173264,
-0.051406677812337875,
-0.057161085307598114,
0.036824777722358704,
-0.03157254680991173,
0.007067287806421518,
0.15158706903457642,
-0.1222257912158966,
0.12329676002264023,
0.020955175161361694,
0.1896144151687622,
-0.12332789599895477,
0.0339222252368927,
0.08982209116220474,
-0.036988191306591034,
0.013221588917076588,
0.00975361280143261,
-0.052562564611434937,
0.1590864509344101,
-0.09371145814657211,
0.07146181166172028,
0.010926910676062107,
-0.07592244446277618,
-0.1774153709411621,
-0.09356249868869781,
0.07947742193937302,
0.0617753230035305,
0.005319166928529739,
0.03726791962981224,
0.11306490749120712,
-0.020991774275898933,
0.06488905102014542,
0.11562903225421906,
-0.17549200356006622,
0.013578375801444054,
0.17859570682048798,
0.003242473118007183,
0.15767055749893188,
-0.05546637624502182,
0.019877681508660316,
0.02752300351858139,
0.04758313298225403,
0.06873945891857147,
-0.08186400681734085,
-0.1364826112985611,
-0.056155186146497726,
-0.15456219017505646,
-0.03352400287985802,
0.05195203423500061,
-0.011860138736665249,
-0.05783402919769287,
-0.010724928230047226,
-0.04010869935154915,
0.0008851495804265141,
-0.028637725859880447,
0.01805497519671917,
0.07031578570604324,
-0.01226285845041275,
0.02092539705336094,
-0.08391954004764557,
-0.0390290804207325,
-0.038563769310712814,
-0.018022390082478523,
0.12054917961359024,
0.08285853266716003,
0.0266572255641222,
-0.04135355353355408,
0.10274127870798111,
-0.07091585546731949,
-0.05454207584261894,
0.04555258899927139,
-0.03786851093173027,
-0.10615779459476471,
0.02120024710893631,
-0.05905991420149803,
0.026879185810685158,
0.09943640232086182,
0.18048083782196045,
-0.09862488508224487,
0.012620617635548115,
-0.03430783003568649,
0.08121664822101593,
-0.03196052461862564,
0.03197542577981949,
-0.0840383991599083,
-0.016251085326075554,
0.17835216224193573,
0.0030782297253608704,
0.022272996604442596,
0.002074616262689233,
-0.049819961190223694,
-0.02881433069705963,
-0.017756454646587372,
0.06631895154714584,
0.07032092660665512,
0.010587303899228573,
-0.0037596761249005795,
-0.027667716145515442,
-0.036921944469213486,
-0.05629328638315201,
-0.04952820762991905,
0.018803736194968224,
-0.04712437093257904,
-0.047942135483026505,
0.06027210131287575,
-0.005624116864055395,
0.11337806284427643,
-0.025607796385884285,
0.026316547766327858,
-0.019410157576203346,
-0.07494441419839859,
-0.13221681118011475,
-0.0304415225982666,
0.0691632330417633,
0.04371757060289383,
-0.22497159242630005,
-0.16994807124137878,
-0.008539012633264065,
0.017946386709809303,
-0.018741264939308167,
-0.11334165185689926,
0.02453240379691124,
-0.007166135590523481,
-0.049758363515138626,
-0.01601579785346985,
0.10474669933319092,
-0.020438622683286667,
0.018010856583714485,
-0.05593825876712799,
0.16603368520736694,
-0.14290283620357513,
0.031004127115011215,
-0.08706212788820267,
0.023509707301855087,
-0.21286657452583313,
0.041208744049072266,
-0.177636057138443,
0.04863585904240608,
-0.08500861376523972,
0.02327173389494419,
0.021320728585124016,
0.01968831568956375,
0.08580207824707031,
0.10143322497606277,
-0.23631145060062408,
0.05405791476368904,
0.07900930196046829,
-0.022739801555871964,
-0.04218491166830063,
0.06798892468214035,
-0.06558530032634735,
0.1382148116827011,
0.046505436301231384,
0.24831900000572205,
0.10361487418413162,
-0.2036508023738861,
0.061786454170942307,
0.0578593946993351,
-0.08880111575126648,
-0.004730981774628162,
-0.020022382959723473,
0.11598580330610275,
-0.01114928349852562,
0.03338807821273804,
-0.12186288088560104,
0.1456439197063446,
0.02738998830318451,
-0.0165485180914402,
-0.04454165697097778,
-0.1614885926246643,
0.10309953987598419,
-0.015504824928939342,
0.09532155096530914,
-0.042415786534547806,
0.0001161050095106475,
-0.011168917641043663,
0.18012429773807526,
-0.043841805309057236,
0.0007168867159634829,
0.07871408760547638,
0.10895700752735138,
0.028009075671434402,
-0.020230965688824654,
-0.20380273461341858,
-0.0423048660159111,
0.02367858961224556,
0.044489551335573196,
0.2190362960100174,
0.19936694204807281,
0.07770156860351562,
-0.022313760593533516,
-0.025487221777439117,
-0.003248062450438738,
-0.05106664076447487,
0.03467361256480217,
-0.027858436107635498,
-0.024532482028007507,
0.06065356358885765,
-0.09305168688297272,
0.02817818708717823,
-0.13112716376781464,
0.06307920068502426,
-0.17345242202281952,
0.06863926351070404,
0.021998396143317223,
-0.005436043255031109,
0.024577690288424492,
-0.011292695067822933,
-0.034188106656074524,
-0.06233125180006027,
0.07110602408647537,
0.06098933145403862,
0.014702376909554005,
0.0021991983521729708,
-0.0683600977063179,
-0.13828523457050323,
0.08231553435325623,
-0.04042381793260574,
-0.14305958151817322,
0.06392676383256912,
0.011172642931342125,
0.04875864461064339,
-0.05975872278213501,
0.016254881396889687,
0.22900153696537018,
0.05321883037686348,
0.09785865992307663,
-0.04092191904783249,
-0.022525805979967117,
-0.06617844104766846,
-0.06677833944559097,
0.09694591909646988,
0.10812206566333771,
0.060318704694509506,
-0.0030071530491113663,
0.07626225054264069,
0.10942911356687546,
-0.1035122498869896,
-0.0651884600520134,
0.03220061957836151,
-0.05973697826266289,
0.019652515649795532,
0.049140311777591705,
0.02971293032169342,
0.08619047701358795,
0.1833551675081253,
0.008245792239904404,
0.0386311337351799,
-0.025997694581747055,
0.026109617203474045,
-0.15547916293144226,
-0.03145433962345123,
0.04308181628584862,
0.00886955764144659,
-0.07408110797405243,
0.04994636029005051,
0.051439400762319565,
0.13607151806354523,
-0.08217083662748337,
-0.13170577585697174,
-0.059745315462350845,
-0.03804200142621994,
-0.04239124804735184,
0.14975430071353912,
-0.08507520705461502,
-0.19221234321594238,
-0.017164425924420357,
-0.15751953423023224,
-0.02518727444112301,
-0.005179801490157843,
0.002318724524229765,
-0.08325926214456558,
0.017780914902687073,
0.010001576505601406,
-0.03129372000694275,
-0.0684933215379715,
-0.06596160680055618,
-0.05786636844277382,
0.09124112874269485,
0.06932931393384933,
-0.12240120023488998,
-0.00961651187390089,
-0.03742414712905884,
-0.020465577021241188,
0.04516167193651199,
0.08452648669481277,
-0.007267598994076252,
0.07773483544588089,
-0.13209199905395508,
-0.06962883472442627,
0.02834828943014145,
0.2766247093677521,
0.02882981114089489,
0.004668009467422962,
0.17051753401756287,
-0.03629542142152786,
0.04912714660167694,
0.16181479394435883,
0.030781643465161324,
-0.14196757972240448,
0.07090470939874649,
-0.011341600678861141,
-0.09542687982320786,
-0.1706860214471817,
-0.10215658694505692,
-0.037867411971092224,
-0.05015881359577179,
0.05638284236192703,
0.004951419774442911,
-0.04476970434188843,
0.05910305306315422,
0.08782228082418442,
-0.017004497349262238,
-0.06151578947901726,
0.11129767447710037,
0.032263003289699554,
-0.030136963352560997,
0.08078382909297943,
-0.042354047298431396,
-0.04206389561295509,
0.0032403599470853806,
0.22643887996673584,
0.0937788337469101,
-0.01775507442653179,
-0.042567066848278046,
0.019317636266350746,
0.05095715448260307,
0.03613382205367088,
0.11312435567378998,
-0.06975842267274857,
-0.06826137751340866,
-0.035185977816581726,
0.027829548344016075,
-0.02945687249302864,
0.08205190300941467,
0.0630207508802414,
0.005563626065850258,
-0.04653681069612503,
-0.07972332090139389,
-0.04849022626876831,
0.08408913016319275,
-0.027642227709293365,
-0.10093270242214203,
0.09321888536214828,
0.048575710505247116,
0.0016974330646917224,
0.03055831417441368,
0.027994604781270027,
0.01462269201874733,
-0.07982148975133896,
-0.06775744259357452,
0.011468625627458096,
0.07076629996299744,
-0.06822766363620758,
-0.027886953204870224,
-0.19817815721035004,
0.14578363299369812,
0.010630400851368904,
0.04118429124355316,
-0.13048617541790009,
0.1209396943449974,
-0.023116756230592728,
-0.026430301368236542,
0.013811616227030754,
0.0014643745962530375,
0.08203291147947311,
-0.04806509613990784,
0.15762180089950562,
0.009528410620987415,
-0.28092408180236816,
-0.1418946087360382,
-0.08416824042797089,
-0.051183976233005524,
-0.022873088717460632,
0.014752174727618694,
0.0642135739326477,
0.01516205258667469,
0.003868846921250224,
-0.013076163828372955,
0.03185269236564636,
-0.09826882928609848,
-0.06493937969207764,
-0.04839126765727997,
-0.02250157669186592,
-0.06525848805904388,
-0.05647949501872063,
-0.0006809153710491955,
-0.17226077616214752,
0.12522587180137634,
0.11787347495555878,
-0.06451737880706787,
-0.041814323514699936,
-0.06554657220840454,
0.046191465109586716,
-0.07571537792682648,
0.0469326451420784,
0.003414976177737117,
0.019198855385184288,
-0.06806991249322891,
-0.17922484874725342,
0.016097763553261757,
-0.10899919271469116,
0.03772687539458275,
-0.05070559307932854,
0.020257100462913513,
0.08594245463609695,
0.17520126700401306,
0.05856714025139809,
0.01460097823292017,
-0.07239776104688644,
-0.07543374598026276,
-0.0017121878918260336,
-0.06344114243984222,
0.05762333422899246,
-0.009151889942586422,
-0.20333483815193176,
0.02763226442039013,
-0.11414948850870132,
0.06860900670289993,
0.3310066759586334,
0.3324824273586273,
-0.10698744654655457,
0.1177443116903305,
0.04819539934396744,
-0.042202454060316086,
-0.21051374077796936,
-0.002244179602712393,
0.012272895313799381,
0.024992236867547035,
0.13725964725017548,
-0.12924811244010925,
0.05453680083155632,
0.0794181227684021,
-0.024458877742290497,
0.01456840243190527,
-0.09078162908554077,
-0.10816970467567444,
0.20847418904304504,
0.14226987957954407,
0.04421741142868996,
-0.09421348571777344,
0.08391669392585754,
0.004295284394174814,
0.08375877887010574,
0.2107764035463333,
-0.052112679928541183,
0.10695768147706985,
0.005195184610784054,
0.19852910935878754,
0.0328996516764164,
-0.023768596351146698,
0.10834760218858719,
-0.009801650419831276,
0.07911337912082672,
0.03985166177153587,
-0.007676942739635706,
0.010487722232937813,
-0.04522453248500824,
0.014148596674203873,
-0.028376007452607155,
0.010284217074513435,
-0.2274095118045807,
0.0582297146320343,
-0.06368855386972427,
0.04604509472846985,
0.008256820961833,
-0.0999874547123909,
-0.03583388403058052,
0.06431841105222702,
0.08014573156833649,
0.01975327916443348,
0.0436067171394825,
-0.03867863491177559,
0.11051398515701294,
0.20660489797592163,
-0.009811338968575,
0.17751595377922058,
-0.0615963339805603,
0.01464168168604374,
-0.023011628538370132,
-0.04223164543509483,
-0.1462583988904953,
-0.035259708762168884,
0.03498423472046852,
0.057734888046979904,
0.015203364193439484,
0.049647457897663116,
-0.05656236410140991,
0.08498423546552658,
0.021687336266040802,
-0.041541360318660736,
0.033579520881175995,
0.08835696429014206,
0.12415177375078201,
0.010754258371889591,
-0.030121933668851852,
0.06147436052560806,
-0.08128108084201813,
-0.09446098655462265,
-0.004497923422604799,
-0.029991207644343376,
-0.1083834245800972,
0.11353230476379395,
0.16914646327495575,
0.039594944566488266,
-0.057076629251241684,
0.10688766092061996,
-0.02768099494278431,
0.10047874599695206,
0.009198128245770931,
0.06507332623004913,
-0.014091075398027897,
-0.03691792115569115,
0.10611724853515625,
-0.05442855879664421,
-0.01637818105518818,
0.07645545154809952,
-0.06522727757692337,
-0.023877469822764397,
-0.0801999643445015,
0.06034626066684723,
0.09222240000963211,
-0.16854619979858398,
-0.0639432892203331,
-0.032122284173965454,
-0.08628080040216446,
0.013965039514005184,
0.012447911314666271,
0.0710059329867363,
-0.08589600026607513,
0.06316167116165161,
-0.024337708950042725,
0.015639442950487137,
-0.03689891844987869,
0.019222697243094444,
-0.19525384902954102,
-0.002140450058504939,
-0.11280795186758041,
-0.00348020251840353,
-0.002931603929027915,
0.04463808611035347,
-0.04961875081062317,
-0.029358822852373123,
-0.0030675032176077366,
0.044366419315338135,
-0.16609135270118713,
0.002798673929646611,
-0.011639905162155628,
0.03210212290287018,
-0.0002893915225286037,
-0.0983390137553215,
0.014195028692483902,
-0.04294256120920181,
-0.04198618605732918,
0.04925514757633209,
0.009436776861548424,
0.06470516324043274,
-0.2795179784297943,
-0.14905457198619843,
0.030816160142421722,
0.0683867484331131,
0.05483196675777435,
-0.1830425262451172,
0.03568267077207565,
-0.08042316138744354,
-0.02253127470612526,
-0.037770628929138184,
0.018491698428988457,
-0.0539514496922493,
0.0018174031283706427,
-0.04225044324994087,
-0.023033907637000084,
-0.028055014088749886,
-0.07556360960006714,
0.0826747715473175,
0.12462522834539413,
0.07555580884218216,
-0.03807181864976883,
0.09595896303653717,
-0.10009756684303284,
-0.04657831788063049,
-0.04052736237645149,
-0.036951083689928055,
0.017965637147426605,
-0.0870552659034729,
0.048530060797929764,
0.05188591405749321,
0.18719671666622162,
-0.08520494401454926,
-0.058800119906663895,
-0.014255574904382229,
0.0746525228023529,
0.07849094271659851,
0.005095830652862787,
0.17779210209846497,
-0.045693784952163696,
0.05693846940994263,
0.021304311230778694,
0.046699028462171555,
0.10497613251209259,
-0.023569339886307716,
0.14490213990211487,
0.21171095967292786,
-0.037196725606918335,
-0.11048602312803268,
0.043668005615472794,
0.01745123788714409,
-0.002401199424639344,
0.05968761444091797,
0.11983796209096909,
-0.050589341670274734,
-0.10903856158256531,
0.23442286252975464,
0.054169271141290665,
-0.11218088120222092,
0.09546315670013428,
0.039532262831926346,
-0.015890996903181076,
-0.1301896870136261,
0.010444961488246918,
-0.0013640925753861666,
-0.11233190447092056,
0.03386834263801575,
-0.06087532266974449,
-0.025547027587890625,
0.11809267848730087,
0.008789865300059319,
0.03317064419388771,
-0.04139537364244461,
-0.03756232187151909,
-0.04352104663848877,
-0.04273213446140289,
-0.012549578212201595,
-0.02991986647248268,
-0.030186517164111137,
-0.07621737569570541,
-0.007770835887640715,
-0.012012424878776073,
0.030795488506555557,
-0.015285328030586243,
-0.02503054589033127,
-0.021192016080021858,
-0.06697061657905579,
-0.0026312144473195076,
-0.008178025484085083,
0.015549594536423683,
0.010121971368789673,
0.2358063906431198,
0.07042546570301056,
-0.10260069370269775,
-0.01036880537867546,
0.22197756171226501,
-0.03853277862071991,
-0.06528383493423462,
-0.07849395275115967,
0.25128230452537537,
-0.10482002794742584,
0.051095426082611084,
-0.005819917656481266,
-0.06550488620996475,
-0.07153836637735367,
0.2309868484735489,
0.13502730429172516,
-0.1677926480770111,
0.06329060345888138,
-0.0368385910987854,
-0.009490780532360077,
-0.14286863803863525,
0.16013580560684204,
0.1865294873714447,
0.09480160474777222,
-0.12259847670793533,
0.0023130534682422876,
-0.03518044203519821,
-0.018328361213207245,
-0.1660851687192917,
-0.004593863617628813,
-0.029364850372076035,
-0.0427238829433918,
-0.050771355628967285,
0.029773715883493423,
-0.15205919742584229,
-0.0927426889538765,
-0.1916799396276474,
-0.11482496559619904,
-0.12386849522590637,
-0.04549141973257065,
-0.11142764985561371,
-0.0019938007462769747,
0.02257080189883709,
-0.0641874223947525,
0.021061956882476807,
-0.0212461706250906,
-0.05887424945831299,
0.015386379323899746,
-0.08395619690418243,
0.0674985870718956,
0.06488548219203949,
0.15327942371368408,
-0.0790991559624672,
0.025424562394618988,
0.07090727984905243,
-0.057595450431108475,
-0.10164349526166916,
0.06067253649234772,
0.015708057209849358,
-0.1972588747739792,
0.007548294495791197,
0.17712996900081635,
-0.10420889407396317,
0.09745754301548004,
0.048501528799533844,
-0.012951982207596302,
0.0867827981710434,
-0.024721821770071983,
-0.016682926565408707,
-0.04852180927991867,
-0.011212974786758423,
-0.10143939405679703,
0.09892100840806961,
0.0876845121383667,
-0.0517118014395237,
0.07436849176883698,
-0.09508965909481049,
-0.04068392515182495,
0.13103286921977997,
-0.010057874955236912,
-0.08450483530759811,
-0.11667824536561966,
-0.04081142693758011,
0.09684515744447708,
-0.018041390925645828,
-0.20185889303684235,
-0.11639472097158432,
-0.11752668023109436,
-0.00014377340266946703,
-0.03563340753316879,
0.061800602823495865,
0.02430674433708191,
-0.02556120604276657,
-0.008150683715939522,
-0.17615078389644623,
-0.06614746153354645,
0.13479791581630707,
-0.10176112502813339,
-0.07456064969301224
] |
null | null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
### Framework versions
- PEFT 0.4.0
| {"library_name": "peft"} | null | yasithheshan/llama2-7B-with-diversity-epoch-2 | [
"peft",
"region:us"
] | 2024-02-11T07:43:13+00:00 | [] | [] | TAGS
#peft #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
### Framework versions
- PEFT 0.4.0
| [
"## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16",
"### Framework versions\n\n\n- PEFT 0.4.0"
] | [
"TAGS\n#peft #region-us \n",
"## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16",
"### Framework versions\n\n\n- PEFT 0.4.0"
] | [
9,
154,
11
] | [
"passage: TAGS\n#peft #region-us \n## Training procedure\n\n\nThe following 'bitsandbytes' quantization config was used during training:\n- load_in_8bit: False\n- load_in_4bit: True\n- llm_int8_threshold: 6.0\n- llm_int8_skip_modules: None\n- llm_int8_enable_fp32_cpu_offload: False\n- llm_int8_has_fp16_weight: False\n- bnb_4bit_quant_type: nf4\n- bnb_4bit_use_double_quant: False\n- bnb_4bit_compute_dtype: float16### Framework versions\n\n\n- PEFT 0.4.0"
] | [
-0.06979092955589294,
0.021877916529774666,
-0.0024098597932606936,
0.1378258466720581,
0.10862318426370621,
0.07474296540021896,
0.10942144691944122,
0.12339992076158524,
0.0572756864130497,
0.09055759757757187,
0.09443594515323639,
0.05080708488821983,
0.07617583870887756,
0.15425844490528107,
-0.02472618594765663,
-0.030937515199184418,
0.05461447685956955,
0.0024960634764283895,
0.003683591727167368,
0.07837489992380142,
0.05202331766486168,
-0.036243125796318054,
0.037176959216594696,
-0.09029994904994965,
-0.1683429628610611,
-0.0007763148751109838,
0.010803398676216602,
0.03168312832713127,
0.04643981158733368,
0.03667012229561806,
0.061239324510097504,
-0.01880047656595707,
-0.024256091564893723,
-0.2065766304731369,
-0.008815872482955456,
0.12412996590137482,
-0.022375915199518204,
0.0724588930606842,
-0.08079487085342407,
0.13203540444374084,
-0.039120372384786606,
-0.02855866029858589,
0.005213533993810415,
0.031375303864479065,
-0.08930839598178864,
-0.12567098438739777,
-0.06602675467729568,
0.061225954443216324,
0.022498471662402153,
0.0596780888736248,
0.0024417112581431866,
0.19193901121616364,
-0.1333344727754593,
0.08866282552480698,
0.10110592097043991,
-0.24191753566265106,
-0.03025546856224537,
0.14384306967258453,
-0.024540316313505173,
0.15543513000011444,
-0.07628224045038223,
-0.10719222575426102,
0.08085530251264572,
0.0496523417532444,
-0.056598056107759476,
-0.0009009919012896717,
-0.09088310599327087,
0.006839253939688206,
-0.13980844616889954,
-0.05230165645480156,
0.15110687911510468,
0.026294633746147156,
-0.037592023611068726,
-0.031246718019247055,
-0.0950726643204689,
-0.35348814725875854,
0.024415571242570877,
-0.002826953772455454,
-0.06987019628286362,
0.048015810549259186,
0.035156507045030594,
-0.008995379321277142,
0.004349078983068466,
-0.09262323379516602,
-0.04143654555082321,
0.10029355436563492,
0.04808283597230911,
0.04402211308479309,
0.019573308527469635,
0.1058531403541565,
-0.12883538007736206,
-0.021110432222485542,
-0.041084397584199905,
-0.02869381383061409,
-0.050102680921554565,
-0.014695894904434681,
-0.07354352623224258,
0.17733292281627655,
0.06763829290866852,
0.09666602313518524,
-0.1813267171382904,
0.1257096230983734,
-0.02475627325475216,
0.05742272362112999,
-0.035531818866729736,
0.014435730874538422,
-0.11885007470846176,
0.12319590896368027,
0.0007600552635267377,
0.13899193704128265,
0.02280823327600956,
-0.04473873972892761,
-0.0730285570025444,
-0.007154371589422226,
0.1233254000544548,
0.004622994922101498,
-0.11530132591724396,
0.007921767421066761,
-0.1411384791135788,
-0.04554228112101555,
0.0911121591925621,
-0.07906953990459442,
0.015561599284410477,
0.041121818125247955,
-0.04623573645949364,
0.004239376168698072,
0.09626287966966629,
-0.05426957085728645,
-0.04919392615556717,
-0.03332843258976936,
-0.10088252276182175,
0.00408816896378994,
-0.1039951965212822,
-0.13126124441623688,
0.051543787121772766,
-0.1563965529203415,
-0.00575046194717288,
-0.04191170632839203,
-0.06613527983427048,
0.02011139690876007,
0.019768383353948593,
-0.08437694609165192,
0.05859275907278061,
-0.08150110393762589,
-0.1557578295469284,
-0.03541033715009689,
0.018620938062667847,
0.007860139012336731,
-0.02999168075621128,
0.09800084680318832,
0.032462093979120255,
0.10065783560276031,
-0.1774347871541977,
-0.0032585663720965385,
0.013272988609969616,
0.06698489189147949,
0.016430236399173737,
0.11852112412452698,
-0.0984061062335968,
-0.029854416847229004,
-0.05219494178891182,
-0.06776446104049683,
-0.10671226680278778,
-0.009978118352591991,
0.12339237332344055,
0.081203892827034,
-0.15919211506843567,
-0.010960342362523079,
0.07894296199083328,
-0.034127745777368546,
-0.08150023221969604,
0.1462218016386032,
-0.043517038226127625,
0.10362964868545532,
-0.03142445161938667,
0.07441626489162445,
0.2393224835395813,
-0.13294187188148499,
0.0026927399449050426,
0.11512340605258942,
0.04870401695370674,
-0.024512527510523796,
0.001410747179761529,
0.06937900930643082,
-0.142485573887825,
0.03395999222993851,
0.067036472260952,
0.03290358558297157,
-0.059946075081825256,
-0.05717241391539574,
-0.03879120573401451,
-0.054277822375297546,
0.11310963332653046,
0.028706887736916542,
0.012219887226819992,
-0.07421029359102249,
-0.07091692090034485,
0.14475229382514954,
0.13386821746826172,
-0.01724834553897381,
-0.005964277777820826,
-0.1111484244465828,
0.002316186437383294,
-0.04553208500146866,
0.027614165097475052,
-0.12323106080293655,
0.024642376229166985,
0.08063367009162903,
0.01609816960990429,
-0.005867816042155027,
0.048622094094753265,
0.06404208391904831,
0.02775740437209606,
-0.054996591061353683,
0.023086974397301674,
-0.05230040103197098,
-0.002152500906959176,
-0.10709255933761597,
-0.07857770472764969,
-0.013062533922493458,
-0.010289276950061321,
0.18266798555850983,
-0.14896303415298462,
0.03612537682056427,
0.10309912264347076,
0.004995338153094053,
-0.010612043552100658,
-0.036244068294763565,
-0.07481951266527176,
0.11431097984313965,
-0.012485682964324951,
-0.03552611544728279,
0.04104119539260864,
0.034952957183122635,
-0.03309863805770874,
-0.1580384373664856,
-0.09931837022304535,
0.05646728724241257,
0.13403663039207458,
0.07577018439769745,
-0.06703833490610123,
-0.047553446143865585,
-0.020618250593543053,
-0.03879788890480995,
0.056729573756456375,
-0.05360506474971771,
0.023469123989343643,
0.012125842273235321,
0.06819912791252136,
-0.10050064325332642,
-0.03629688918590546,
0.06696230918169022,
-0.011795254424214363,
-0.04454666003584862,
0.11060863733291626,
0.01751997321844101,
-0.07169803977012634,
0.07787928730249405,
0.05941096320748329,
-0.14069285988807678,
0.08998789638280869,
-0.004688691347837448,
-0.023223139345645905,
-0.09080317616462708,
0.17682680487632751,
0.024636752903461456,
0.12305090576410294,
-0.1265403926372528,
0.10609687864780426,
-0.010145329870283604,
0.014946194365620613,
0.07392288744449615,
-0.20129480957984924,
-0.004805627278983593,
-0.0471431165933609,
-0.09572996944189072,
-0.05821099132299423,
-0.015557871200144291,
0.0170791894197464,
0.043467629700899124,
-0.005354706663638353,
0.06044595688581467,
0.142664834856987,
-0.018936002627015114,
-0.08370210230350494,
0.17457811534404755,
-0.21770337224006653,
-0.20481646060943604,
-0.23560066521167755,
0.0029743367340415716,
-0.11851438134908676,
-0.037289947271347046,
-0.05196189507842064,
-0.07753796130418777,
0.03229401260614395,
-0.08353889733552933,
-0.040616557002067566,
-0.019290516152977943,
0.003061749739572406,
0.05178794264793396,
0.011813749559223652,
0.1695105880498886,
-0.0735611766576767,
0.023279182612895966,
0.046429067850112915,
-0.02350066788494587,
0.10787586867809296,
-0.08872182667255402,
-0.03777230158448219,
0.12821447849273682,
-0.009709981270134449,
0.02801087126135826,
0.01423876266926527,
0.3048967123031616,
0.010030297562479973,
0.02763240598142147,
0.09710080921649933,
0.009545043110847473,
0.06174734979867935,
0.07832355052232742,
0.015707092359662056,
-0.10942601412534714,
0.06433121860027313,
0.04781096801161766,
-0.09661031514406204,
-0.13850480318069458,
-0.047762222588062286,
-0.07341255247592926,
0.006593871861696243,
0.08610724657773972,
0.07147743552923203,
0.07943940162658691,
0.07025924324989319,
0.023519491776823997,
0.11204782873392105,
-0.004567211028188467,
-0.005818400532007217,
0.1201663389801979,
-0.020266585052013397,
0.04491112753748894,
-0.030482962727546692,
0.03723101690411568,
0.07022300362586975,
0.14435730874538422,
0.08234275877475739,
-0.0826135203242302,
-0.0026839443016797304,
0.04897516965866089,
0.2717514932155609,
-0.01714148186147213,
0.10665575414896011,
-0.06918495893478394,
-0.013546466827392578,
0.0014700466999784112,
-0.03347883000969887,
-0.07884032279253006,
0.04058695584535599,
-0.02208472229540348,
0.07936602830886841,
-0.017719898372888565,
-0.027150988578796387,
0.07915937900543213,
0.12511037290096283,
0.15299907326698303,
-0.28453946113586426,
-0.11869988590478897,
-0.013159751892089844,
0.11041011661291122,
-0.10107292234897614,
0.0223299078643322,
0.21577490866184235,
0.008470140397548676,
-0.08149175345897675,
-0.03681793436408043,
0.03811902552843094,
-0.01879933662712574,
0.016045289114117622,
0.12573954463005066,
0.14544515311717987,
0.005644232500344515,
0.07689831405878067,
-0.2924128472805023,
0.023194577544927597,
0.05471178889274597,
0.046213310211896896,
-0.04598768800497055,
0.008340165950357914,
-0.04420474171638489,
-0.06625235080718994,
0.029148653149604797,
0.01076830830425024,
0.1823798418045044,
-0.28289252519607544,
-0.06890449672937393,
-0.02097264863550663,
0.1087518259882927,
0.08112131059169769,
0.04162963479757309,
0.01758452132344246,
0.056389037519693375,
0.06615620851516724,
0.03817380219697952,
-0.0343405120074749,
-0.09718122333288193,
0.0010788479121401906,
0.15619537234306335,
-0.14491763710975647,
-0.05582432448863983,
-0.06452815234661102,
-0.024293042719364166,
0.05778651684522629,
-0.1548195481300354,
-0.05276089906692505,
-0.06254495680332184,
0.015085814520716667,
0.1334981471300125,
-0.023490145802497864,
-0.01085786335170269,
-0.0201820470392704,
0.024849023669958115,
-0.04709408059716225,
-0.09744754433631897,
0.11661811918020248,
-0.0471058264374733,
-0.1306038200855255,
-0.019828403368592262,
0.1378549486398697,
0.08238520473241806,
-0.015439215116202831,
-0.0857001468539238,
-0.04882924631237984,
0.027058644220232964,
-0.15197721123695374,
0.005223190877586603,
0.09445921331644058,
-0.0594605952501297,
0.09092224389314651,
-0.11116138100624084,
0.22619131207466125,
-0.04533985257148743,
0.09459085017442703,
0.061151355504989624,
0.2978513538837433,
-0.08713971078395844,
0.018928516656160355,
0.04804879426956177,
-0.018178772181272507,
-0.2438703179359436,
0.04353063553571701,
0.05640896409749985,
0.040471117943525314,
-0.03873369097709656,
-0.1723128706216812,
0.035184476524591446,
0.09765327721834183,
0.009074017405509949,
0.20277278125286102,
-0.32115042209625244,
-0.05401403456926346,
0.04298613592982292,
0.06709850579500198,
0.15412142872810364,
-0.05032355710864067,
0.005308091174811125,
0.00299404701218009,
-0.025177884846925735,
0.14879994094371796,
-0.10914967209100723,
0.11319706588983536,
-0.028690336272120476,
0.024565158411860466,
0.009507894515991211,
-0.03613625466823578,
0.14931310713291168,
0.013264713808894157,
0.089763343334198,
0.019067833200097084,
-0.04837853088974953,
0.05236007273197174,
-0.08060209453105927,
0.048760365694761276,
-0.055018678307533264,
0.08426039665937424,
-0.0716785341501236,
0.014209864661097527,
-0.0624924935400486,
-0.02230324223637581,
-0.07208869606256485,
-0.03789118677377701,
-0.098033107817173,
0.07829388231039047,
-0.014118213206529617,
-0.0252530500292778,
-0.030577998608350754,
0.06026613339781761,
0.06182622164487839,
0.4425763189792633,
-0.06215111166238785,
-0.059386324137449265,
0.0778389647603035,
0.09745035320520401,
-0.018147382885217667,
0.10684601962566376,
-0.12679900228977203,
0.04500621557235718,
0.12372613698244095,
-0.0008733426802791655,
0.12444817274808884,
0.0908789336681366,
-0.11470408737659454,
-0.01735471934080124,
0.03941637650132179,
-0.13241484761238098,
-0.072132408618927,
-0.02437761053442955,
-0.0033349243458360434,
-0.10859358310699463,
0.02123371511697769,
0.10324949026107788,
-0.028791457414627075,
0.054798197001218796,
0.03556765988469124,
0.044085126370191574,
-0.13439145684242249,
0.13734261691570282,
0.03844649717211723,
0.0715968981385231,
-0.09430023282766342,
0.08732116222381592,
0.023660900071263313,
0.012141572311520576,
0.04477553442120552,
-0.0023568833712488413,
-0.10149598866701126,
0.010059066116809845,
-0.038228947669267654,
-0.09548848867416382,
0.09702998399734497,
-0.04586396366357803,
-0.0412009172141552,
-0.11459630727767944,
0.016487689688801765,
0.07441749423742294,
0.06058561056852341,
0.10161381214857101,
-0.0266474150121212,
0.01351380068808794,
-0.1312156319618225,
0.0554811991751194,
-0.034641385078430176,
0.028874071314930916,
-0.15108218789100647,
0.060451265424489975,
-0.01823197305202484,
0.07453461736440659,
-0.019939351826906204,
-0.013813626021146774,
-0.22570104897022247,
0.021174952387809753,
-0.033057328313589096,
0.003854290582239628,
0.029487796127796173,
0.03671148419380188,
0.02527959644794464,
0.05630463361740112,
-0.031085221096873283,
0.04344148188829422,
-0.03895607963204384,
-0.051280442625284195,
0.04188956692814827,
0.0007596524665132165,
-0.035418447107076645,
-0.046238139271736145,
0.04512936249375343,
-0.11377303302288055,
0.037379465997219086,
0.037038300186395645,
-0.05313664302229881,
0.07457074522972107,
0.0551333986222744,
0.020679296925663948,
0.09771078824996948,
0.05872461944818497,
0.05539431795477867,
-0.05644817277789116,
0.038207992911338806,
-0.013830473646521568,
-0.0014212807873263955,
0.05458271503448486,
0.13561320304870605,
-0.05696135014295578,
-0.05802462622523308,
-0.1356644332408905,
-0.022950179874897003,
-0.04388374090194702,
0.04029588773846626,
0.15611368417739868,
0.10005352646112442,
0.08508609980344772,
-0.08406435698270798,
-0.023177621886134148,
-0.1434895098209381,
-0.0838560089468956,
0.057367514818906784,
-0.04613112285733223,
-0.013442962430417538,
-0.03551625832915306,
0.07219497859477997,
0.007350239437073469,
0.15389199554920197,
-0.09119492769241333,
-0.09884331375360489,
-0.050555817782878876,
-0.17701447010040283,
-0.1346471607685089,
-0.005777652841061354,
0.2509252429008484,
0.031908661127090454,
-0.030132247135043144,
-0.06317965686321259,
0.00790130253881216,
0.0689205676317215,
0.13760150969028473,
0.04632747173309326,
0.07801228016614914,
-0.12434402108192444,
0.10745592415332794,
0.04290035367012024,
-0.05061715841293335,
0.12014038860797882,
0.30707380175590515,
-0.08199357986450195,
0.011254170909523964,
-0.08713367581367493,
0.08879105001688004,
0.02187724970281124,
-0.1383187174797058,
0.013609658926725388,
-0.03021937422454357,
-0.15772560238838196,
-0.1141202449798584,
0.03438706323504448,
-0.06414132565259933,
-0.20812147855758667,
-0.02861359901726246,
-0.10091375559568405,
-0.07548198103904724,
0.1385963410139084,
0.036400459706783295,
-0.01720549911260605,
0.1921585202217102,
-0.07791507244110107,
0.047225624322891235,
-0.010112340562045574,
-0.01755616068840027,
-0.004292663186788559,
-0.03010612167418003,
-0.10022464394569397,
0.14229239523410797,
0.0026088182348757982,
0.11017946153879166,
0.0076710316352546215,
0.08859197050333023,
0.05187401920557022,
-0.024778150022029877,
-0.040657348930835724,
-0.0020166346803307533,
0.015454727225005627,
-0.06949343532323837,
0.1287740021944046,
0.06015017256140709,
-0.08151866495609283,
-0.08153397589921951,
-0.020808378234505653,
-0.08484478294849396,
-0.021831484511494637,
-0.1572553515434265,
0.28017404675483704,
-0.03308238461613655,
0.10164105892181396,
-0.009170068427920341,
-0.05692457780241966,
-0.10435646772384644,
0.14374536275863647,
0.120839424431324,
-0.13673727214336395,
-0.012003384530544281,
0.08866086602210999,
-0.007145259529352188,
-0.07515248656272888,
0.155784472823143,
0.09963296353816986,
-0.014980965293943882,
0.02876802533864975,
-0.023070234805345535,
-0.03320426493883133,
0.0033824562560766935,
-0.005501914769411087,
-0.034212253987789154,
0.005797996185719967,
0.03244750574231148,
-0.13621188700199127,
-0.017982242628932,
-0.06249391660094261,
-0.06658949702978134,
0.1939048320055008,
-0.1203932911157608,
-0.08973969519138336,
-0.0308162122964859,
-0.09773550927639008,
-0.10429038852453232,
0.02302357368171215,
-0.11399734765291214,
0.059150729328393936,
0.08660008758306503,
-0.05918910726904869,
-0.015915945172309875,
-0.07759834825992584,
-0.004432562738656998,
0.01995953358709812,
0.06680567562580109,
-0.012953863479197025,
0.07061396539211273,
0.10941770672798157,
-0.02109832689166069,
-0.05627770721912384,
0.09945710748434067,
0.005617896094918251,
-0.058368053287267685,
-0.14522160589694977,
0.017044585198163986,
-0.029553061351180077,
0.10308431833982468,
0.024984009563922882,
-0.06643787026405334,
-0.03581478074193001,
-0.17625966668128967,
-0.011637690477073193,
-0.1381247639656067,
-0.08038759231567383,
-0.07788003236055374,
0.10739508271217346,
0.19482040405273438,
-0.05468401312828064,
0.025051061064004898,
-0.03843652456998825,
0.03321219980716705,
-0.04963286593556404,
0.04273268207907677,
-0.005887014791369438,
-0.14593636989593506,
0.05899544060230255,
-0.05112109333276749,
0.004382130224257708,
-0.28370237350463867,
0.001215865253470838,
0.005580263677984476,
-0.033779751509428024,
-0.05040258169174194,
0.1377897560596466,
0.00042426568688824773,
0.07757376879453659,
-0.062357865273952484,
-0.24849353730678558,
-0.0690150111913681,
0.14145798981189728,
0.0006318931700661778,
-0.07864443957805634
] |
null | null | adapter-transformers | # Model Card for Model ID
The CiPE GenAI project is a revolutionary tool designed to improve medication management and safety by providing alerts for potential drug interactions and side effects using Generative AI technology.
## Model Details
### Model Description
- **Developed by:** Shubhankar Tripathy, Sid Vijay, Jiyeon Song, Aditi Killedar
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:**
- **Model type:** Fine-Tuned RAG Model
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** Neural-Chat-7B
# Model Card for My Fine-Tuned Model
## Model Description
- **Purpose**: [Describe the purpose of your model. What task does it perform?]
- **Model architecture**: [Specify the architecture, e.g., BERT, GPT-2, etc.]
- **Training data**: [Briefly describe the dataset used for training. Include any data cleaning or preprocessing steps.]
## Intended Use
- **Intended users**: [Who are the intended users of the model?]
- **Use cases**: [Describe potential use cases for the model.]
## Limitations
- **Known limitations**: [Mention any known limitations of the model.]
## Hardware
- **Training Platform**: [Describe details about the systems and platform used to train the model.]
## Software Optimizations
- **Known Optimizations**: [Describe details about any optimizations used during training.]
## Ethical Considerations
- **Ethical concerns**: [Discuss any ethical concerns related to the use of your model.]
## More Information
- [Include any additional information, links, or references.]
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/lonexreb/CiPE
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] | {"language": ["en"], "license": "mit", "library_name": "adapter-transformers", "metrics": ["character"], "pipeline_tag": "question-answering"} | question-answering | filius-Dei/CiPE-clinically-intelligient-prediction-engine-neural-7b | [
"adapter-transformers",
"question-answering",
"en",
"arxiv:1910.09700",
"license:mit",
"region:us"
] | 2024-02-11T07:43:43+00:00 | [
"1910.09700"
] | [
"en"
] | TAGS
#adapter-transformers #question-answering #en #arxiv-1910.09700 #license-mit #region-us
| # Model Card for Model ID
The CiPE GenAI project is a revolutionary tool designed to improve medication management and safety by providing alerts for potential drug interactions and side effects using Generative AI technology.
## Model Details
### Model Description
- Developed by: Shubhankar Tripathy, Sid Vijay, Jiyeon Song, Aditi Killedar
- Funded by [optional]:
- Shared by [optional]:
- Model type: Fine-Tuned RAG Model
- Language(s) (NLP):
- License:
- Finetuned from model [optional]: Neural-Chat-7B
# Model Card for My Fine-Tuned Model
## Model Description
- Purpose: [Describe the purpose of your model. What task does it perform?]
- Model architecture: [Specify the architecture, e.g., BERT, GPT-2, etc.]
- Training data: [Briefly describe the dataset used for training. Include any data cleaning or preprocessing steps.]
## Intended Use
- Intended users: [Who are the intended users of the model?]
- Use cases: [Describe potential use cases for the model.]
## Limitations
- Known limitations: [Mention any known limitations of the model.]
## Hardware
- Training Platform: [Describe details about the systems and platform used to train the model.]
## Software Optimizations
- Known Optimizations: [Describe details about any optimizations used during training.]
## Ethical Considerations
- Ethical concerns: [Discuss any ethical concerns related to the use of your model.]
## More Information
- [Include any additional information, links, or references.]
- Repository: URL
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID\n\nThe CiPE GenAI project is a revolutionary tool designed to improve medication management and safety by providing alerts for potential drug interactions and side effects using Generative AI technology.",
"## Model Details",
"### Model Description\n\n- Developed by: Shubhankar Tripathy, Sid Vijay, Jiyeon Song, Aditi Killedar\n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: Fine-Tuned RAG Model \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]: Neural-Chat-7B",
"# Model Card for My Fine-Tuned Model",
"## Model Description\n- Purpose: [Describe the purpose of your model. What task does it perform?]\n- Model architecture: [Specify the architecture, e.g., BERT, GPT-2, etc.]\n- Training data: [Briefly describe the dataset used for training. Include any data cleaning or preprocessing steps.]",
"## Intended Use\n- Intended users: [Who are the intended users of the model?]\n- Use cases: [Describe potential use cases for the model.]",
"## Limitations\n- Known limitations: [Mention any known limitations of the model.]",
"## Hardware \n- Training Platform: [Describe details about the systems and platform used to train the model.]",
"## Software Optimizations\n- Known Optimizations: [Describe details about any optimizations used during training.]",
"## Ethical Considerations\n- Ethical concerns: [Discuss any ethical concerns related to the use of your model.]",
"## More Information\n- [Include any additional information, links, or references.]\n\n\n\n\n- Repository: URL\n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#adapter-transformers #question-answering #en #arxiv-1910.09700 #license-mit #region-us \n",
"# Model Card for Model ID\n\nThe CiPE GenAI project is a revolutionary tool designed to improve medication management and safety by providing alerts for potential drug interactions and side effects using Generative AI technology.",
"## Model Details",
"### Model Description\n\n- Developed by: Shubhankar Tripathy, Sid Vijay, Jiyeon Song, Aditi Killedar\n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: Fine-Tuned RAG Model \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]: Neural-Chat-7B",
"# Model Card for My Fine-Tuned Model",
"## Model Description\n- Purpose: [Describe the purpose of your model. What task does it perform?]\n- Model architecture: [Specify the architecture, e.g., BERT, GPT-2, etc.]\n- Training data: [Briefly describe the dataset used for training. Include any data cleaning or preprocessing steps.]",
"## Intended Use\n- Intended users: [Who are the intended users of the model?]\n- Use cases: [Describe potential use cases for the model.]",
"## Limitations\n- Known limitations: [Mention any known limitations of the model.]",
"## Hardware \n- Training Platform: [Describe details about the systems and platform used to train the model.]",
"## Software Optimizations\n- Known Optimizations: [Describe details about any optimizations used during training.]",
"## Ethical Considerations\n- Ethical concerns: [Discuss any ethical concerns related to the use of your model.]",
"## More Information\n- [Include any additional information, links, or references.]\n\n\n\n\n- Repository: URL\n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
33,
42,
3,
86,
10,
80,
38,
21,
22,
25,
32,
32,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#adapter-transformers #question-answering #en #arxiv-1910.09700 #license-mit #region-us \n# Model Card for Model ID\n\nThe CiPE GenAI project is a revolutionary tool designed to improve medication management and safety by providing alerts for potential drug interactions and side effects using Generative AI technology.## Model Details### Model Description\n\n- Developed by: Shubhankar Tripathy, Sid Vijay, Jiyeon Song, Aditi Killedar\n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: Fine-Tuned RAG Model \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]: Neural-Chat-7B# Model Card for My Fine-Tuned Model## Model Description\n- Purpose: [Describe the purpose of your model. What task does it perform?]\n- Model architecture: [Specify the architecture, e.g., BERT, GPT-2, etc.]\n- Training data: [Briefly describe the dataset used for training. Include any data cleaning or preprocessing steps.]## Intended Use\n- Intended users: [Who are the intended users of the model?]\n- Use cases: [Describe potential use cases for the model.]## Limitations\n- Known limitations: [Mention any known limitations of the model.]## Hardware \n- Training Platform: [Describe details about the systems and platform used to train the model.]## Software Optimizations\n- Known Optimizations: [Describe details about any optimizations used during training.]## Ethical Considerations\n- Ethical concerns: [Discuss any ethical concerns related to the use of your model.]## More Information\n- [Include any additional information, links, or references.]\n\n\n\n\n- Repository: URL\n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations."
] | [
-0.01540797483175993,
0.15799833834171295,
-0.006055174395442009,
0.004574412479996681,
0.07843372225761414,
-0.004063354805111885,
0.05611395463347435,
0.1001909151673317,
0.013334888964891434,
0.102084681391716,
-0.015011503361165524,
0.035008858889341354,
0.06827250868082047,
0.07515732198953629,
0.0416787788271904,
-0.23618845641613007,
0.05604138225317001,
-0.08632133901119232,
-0.04503448307514191,
0.09952720254659653,
0.11476583778858185,
-0.06205574423074722,
0.06444456428289413,
0.008577988483011723,
0.03363294526934624,
-0.025482887402176857,
-0.02116779051721096,
-0.04082543030381203,
0.04828326031565666,
0.039531491696834564,
0.08556144684553146,
-0.014948667027056217,
0.08259925991296768,
-0.2504250109195709,
0.00167267513461411,
0.07606647163629532,
-0.016746707260608673,
0.031374163925647736,
0.04998284950852394,
-0.028315799310803413,
0.16044512391090393,
-0.05786724388599396,
0.1319568157196045,
0.04858121648430824,
-0.09353902190923691,
-0.14676208794116974,
-0.09933318942785263,
0.10286460071802139,
0.10509210079908371,
0.08303892612457275,
-0.040636107325553894,
0.08526747673749924,
-0.0455835685133934,
0.010136088356375694,
0.07743244618177414,
-0.16034680604934692,
-0.03062048740684986,
0.00003002391167683527,
0.07867622375488281,
0.02116057462990284,
-0.09598599374294281,
-0.011248773895204067,
-0.011131901293992996,
0.01682760939002037,
0.10501331835985184,
-0.03830857202410698,
0.11077533662319183,
0.01407422125339508,
-0.14035476744174957,
-0.06411298364400864,
0.09940014034509659,
0.004694669507443905,
-0.07649959623813629,
-0.2087259590625763,
-0.01083083264529705,
0.08475321531295776,
0.015844743698835373,
-0.07481547445058823,
0.026055127382278442,
-0.008991995826363564,
0.0754748061299324,
-0.07303876429796219,
-0.07588788866996765,
-0.04876363277435303,
0.003631303319707513,
0.11059309542179108,
0.05717603489756584,
0.024981440976262093,
0.01123060192912817,
0.07538323849439621,
0.02928055450320244,
-0.07946670800447464,
-0.06005658209323883,
-0.03839984908699989,
-0.11346971988677979,
-0.022515226155519485,
0.021867860108613968,
0.0037940116599202156,
0.02553473226726055,
0.1508490890264511,
-0.00009127177327172831,
0.016612686216831207,
0.031239710748195648,
-0.030932815745472908,
0.08266938477754593,
0.07486705482006073,
-0.03733848035335541,
-0.0643414556980133,
-0.02635940909385681,
0.07960738986730576,
-0.012498822994530201,
-0.012800508178770542,
-0.022478260099887848,
0.0802980288863182,
0.01163115631788969,
0.07473861426115036,
0.05553364381194115,
0.04430171847343445,
-0.032507821917533875,
-0.05158929154276848,
0.17331036925315857,
-0.13766448199748993,
0.0236191526055336,
0.007339277304708958,
-0.003772252704948187,
-0.06432468444108963,
0.021399805322289467,
0.018960952758789062,
-0.0636681318283081,
0.04133205860853195,
-0.04745389148592949,
-0.052787598222494125,
-0.11581908911466599,
-0.07293236255645752,
0.01968684419989586,
0.02877623960375786,
-0.05333986505866051,
-0.07166199386119843,
-0.1529068946838379,
-0.06368950009346008,
0.03123457171022892,
-0.07580017298460007,
-0.01655680313706398,
0.034913916140794754,
-0.02458099275827408,
-0.018729081377387047,
0.0024632737040519714,
-0.046614065766334534,
-0.01715264841914177,
0.03385063633322716,
-0.03832901641726494,
0.024607867002487183,
0.09623859077692032,
0.0356336385011673,
-0.08359406143426895,
0.07452055811882019,
-0.16357743740081787,
0.11553417146205902,
-0.09775187075138092,
-0.020752348005771637,
-0.1300315111875534,
-0.04408799111843109,
0.048774171620607376,
0.014567965641617775,
-0.031617190688848495,
0.0649285614490509,
-0.16608765721321106,
-0.0264297928661108,
0.1314142495393753,
-0.1304716169834137,
-0.062462981790304184,
0.04932986944913864,
-0.06331589072942734,
0.09206782281398773,
0.09384643286466599,
0.10033202171325684,
0.06836526840925217,
-0.08713982999324799,
-0.042582686990499496,
-0.1141573116183281,
0.007805525790899992,
0.18264290690422058,
0.09012242406606674,
-0.07613547891378403,
0.07091169059276581,
0.0022822413593530655,
-0.10799489915370941,
-0.09246804565191269,
0.01592477597296238,
-0.06940805912017822,
0.04274306818842888,
-0.04332630708813667,
0.029759669676423073,
-0.025000136345624924,
-0.068667933344841,
-0.027682550251483917,
-0.11615686118602753,
0.09869883209466934,
0.08469533920288086,
-0.026649463921785355,
-0.012441297061741352,
-0.12070826441049576,
-0.014051854610443115,
0.032411590218544006,
0.004394017159938812,
-0.13502387702465057,
-0.11332138627767563,
0.06920766085386276,
-0.19999657571315765,
0.07562487572431564,
0.0564577654004097,
0.019265562295913696,
0.04771116375923157,
-0.040633395314216614,
0.0027708769775927067,
-0.07357364892959595,
0.02886139415204525,
-0.009144074283540249,
-0.1541205644607544,
-0.013510238379240036,
-0.053833719342947006,
0.06698452681303024,
-0.1664106845855713,
0.016499042510986328,
0.07894483208656311,
0.12913145124912262,
0.04118725284934044,
-0.07047050446271896,
0.014118007384240627,
-0.028795987367630005,
0.013511436991393566,
-0.026093972846865654,
-0.004848568234592676,
-0.04825286567211151,
0.004568004515022039,
0.06507901847362518,
-0.13084334135055542,
-0.03262654319405556,
0.02948726899921894,
0.07643993198871613,
-0.08741006255149841,
-0.06618664413690567,
-0.026897992938756943,
-0.04612750560045242,
-0.08044538646936417,
-0.07536525279283524,
0.17138317227363586,
0.017501994967460632,
0.033562302589416504,
-0.06700354814529419,
-0.05319097265601158,
-0.03771853446960449,
-0.008751335553824902,
-0.009842188097536564,
0.01737941801548004,
0.054150473326444626,
-0.16833752393722534,
0.07590382546186447,
0.03904511779546738,
0.05095866695046425,
0.1078278198838234,
-0.005494396667927504,
-0.09082435071468353,
-0.0295419804751873,
-0.008070113137364388,
0.019755523651838303,
0.11847145110368729,
-0.020694497972726822,
0.03054315783083439,
0.06566911935806274,
0.023885974660515785,
0.007762868423014879,
-0.05934968963265419,
0.04053846001625061,
0.028642306104302406,
-0.022784383967518806,
-0.022310953587293625,
-0.05269909277558327,
-0.019482934847474098,
0.0976455807685852,
0.04227203503251076,
0.10797119140625,
-0.014313209801912308,
-0.03807074576616287,
-0.12902213633060455,
0.1168503686785698,
-0.10996487736701965,
-0.2693195044994354,
-0.11512784659862518,
0.043184369802474976,
0.0021097585558891296,
-0.003909299150109291,
-0.0003190285060554743,
-0.04218687862157822,
-0.09186241775751114,
-0.07560745626688004,
0.07111844420433044,
0.039370346814394,
-0.11125914752483368,
-0.0419512577354908,
0.0514322966337204,
0.028712814673781395,
-0.11016975343227386,
0.011595772579312325,
0.022318925708532333,
-0.11907230317592621,
-0.02961408533155918,
0.06862339377403259,
0.08559116721153259,
0.11897009611129761,
0.03066788986325264,
-0.04060434177517891,
-0.028331656008958817,
0.18789708614349365,
-0.1103748232126236,
0.10589151084423065,
0.10860036313533783,
-0.054670803248882294,
0.06947151571512222,
0.1749154031276703,
0.016789548099040985,
-0.03722196817398071,
0.036803439259529114,
0.097452811896801,
-0.01201542466878891,
-0.23332451283931732,
-0.0652657002210617,
-0.04024290293455124,
-0.09779643267393112,
0.08516503125429153,
0.07740200310945511,
0.09333982318639755,
0.0333818718791008,
-0.07871488481760025,
-0.04044592007994652,
0.056664515286684036,
0.10791594535112381,
0.11303000152111053,
0.011066633276641369,
0.08176171034574509,
-0.034635335206985474,
0.01699209399521351,
0.09657419472932816,
0.042196858674287796,
0.2640446126461029,
-0.021677710115909576,
0.18479296565055847,
0.10955389589071274,
0.025110390037298203,
0.01048488449305296,
-0.021701771765947342,
-0.02263542264699936,
0.05365879461169243,
-0.022060556337237358,
-0.07054784893989563,
-0.0390777662396431,
0.1114291176199913,
0.04547872766852379,
-0.02525424212217331,
0.06747596710920334,
-0.05728255957365036,
0.07360228896141052,
0.12759897112846375,
0.038380131125450134,
-0.09971694648265839,
-0.04592953994870186,
0.08306817710399628,
-0.0959971696138382,
-0.07918483018875122,
0.016354618594050407,
0.09489354491233826,
-0.16437923908233643,
0.06224080175161362,
-0.021887751296162605,
0.10620322078466415,
-0.11264539510011673,
-0.018420135602355003,
0.08058619499206543,
0.018873563036322594,
-0.013896003365516663,
0.10713443905115128,
-0.1500990241765976,
0.09324906766414642,
-0.01627355068922043,
0.059818875044584274,
-0.06584776192903519,
0.07918606698513031,
-0.014978352934122086,
0.015604592859745026,
0.12361032515764236,
0.024353759363293648,
-0.010857361368834972,
0.018580611795186996,
-0.039089564234018326,
0.008175594732165337,
0.06971129775047302,
-0.11547926068305969,
0.09893941134214401,
-0.040316421538591385,
0.010127127170562744,
-0.046084243804216385,
-0.10025770962238312,
-0.13239608705043793,
-0.19041244685649872,
0.09589578211307526,
-0.14191944897174835,
0.032705679535865784,
-0.10982514172792435,
-0.02210274524986744,
-0.01908477023243904,
0.13672210276126862,
-0.1469133496284485,
-0.10450621694326401,
-0.1278686225414276,
-0.07323034852743149,
0.13898663222789764,
-0.07031510025262833,
0.08022419363260269,
0.008649290539324284,
0.1278078854084015,
-0.01151113212108612,
-0.04161366820335388,
0.024538658559322357,
-0.07383183389902115,
-0.21124079823493958,
-0.0708298459649086,
0.12175529450178146,
0.11230394244194031,
0.059349942952394485,
0.006432489491999149,
0.07885532081127167,
0.014049643650650978,
-0.10301129519939423,
0.01902962476015091,
0.1193942204117775,
0.10052964091300964,
0.05175197869539261,
-0.03529319167137146,
-0.05812734365463257,
-0.09909451752901077,
-0.034865472465753555,
0.022144198417663574,
0.11009955406188965,
-0.05090636387467384,
0.18342627584934235,
0.15048015117645264,
-0.0761045590043068,
-0.18532337248325348,
-0.031137678772211075,
0.06673600524663925,
-0.017136096954345703,
0.0638156533241272,
-0.20637819170951843,
0.037775855511426926,
0.03409673646092415,
-0.03920638561248779,
0.04650802165269852,
-0.12709547579288483,
-0.13816601037979126,
0.03920499607920647,
0.066232830286026,
-0.20007650554180145,
-0.14049816131591797,
-0.07953869551420212,
-0.001526592648588121,
-0.20013362169265747,
0.08823957294225693,
0.01879124715924263,
-0.0019714145455509424,
0.0077958605252206326,
0.06854746490716934,
0.0072717019356787205,
-0.01992451585829258,
0.16137884557247162,
-0.007697242312133312,
0.003685461124405265,
-0.09973297268152237,
-0.06549693644046783,
0.08358246833086014,
-0.042662546038627625,
0.061971522867679596,
-0.001264502527192235,
0.011216254904866219,
-0.10402924567461014,
-0.06847761571407318,
-0.06441932171583176,
-0.008519710972905159,
-0.06284836679697037,
-0.1037096306681633,
-0.0918848067522049,
0.12033698707818985,
0.07265424728393555,
-0.04198088496923447,
-0.06941749900579453,
-0.09722115844488144,
-0.03102087415754795,
0.11730577051639557,
0.159073144197464,
0.11376611888408661,
-0.15675924718379974,
-0.009937518276274204,
-0.006739155855029821,
0.05349759757518768,
-0.12151674926280975,
0.05049247667193413,
0.06370590627193451,
0.017548633739352226,
0.1559016853570938,
-0.041146326810121536,
-0.1480766087770462,
-0.015408468432724476,
0.04499724879860878,
-0.030225342139601707,
-0.2256695032119751,
0.00860707089304924,
0.08193106204271317,
-0.14990881085395813,
-0.030676912516355515,
0.07429332286119461,
-0.034011438488960266,
-0.04330344870686531,
-0.007646042853593826,
0.09818814694881439,
-0.0016834224807098508,
0.08817919343709946,
0.04149702936410904,
0.056617092341184616,
-0.07205261290073395,
0.06257840245962143,
0.09264715760946274,
-0.08439256250858307,
0.03821332007646561,
0.06884133070707321,
-0.08090589940547943,
-0.0500188022851944,
-0.015341253019869328,
0.08059131354093552,
0.03162612393498421,
-0.056732624769210815,
0.049378473311662674,
-0.1112554594874382,
0.056282881647348404,
0.05653199553489685,
0.01777101494371891,
0.0018323075491935015,
-0.011363266035914421,
0.032971058040857315,
-0.05170881375670433,
0.1264544427394867,
0.024873699992895126,
0.02144257351756096,
-0.046283986419439316,
-0.035287417471408844,
0.039352498948574066,
-0.018546611070632935,
-0.009071473963558674,
-0.022731024771928787,
-0.09021519869565964,
-0.03219584375619888,
-0.17934396862983704,
0.005374102853238583,
-0.1113339439034462,
-0.005852005444467068,
0.018910733982920647,
-0.050942592322826385,
0.01307525672018528,
0.03491996228694916,
-0.0396028570830822,
-0.049408555030822754,
0.00041664886521175504,
0.08439096808433533,
-0.18423885107040405,
0.008058011531829834,
0.12558449804782867,
-0.08623585850000381,
0.10563929378986359,
-0.00822804681956768,
-0.005944159813225269,
0.024230914190411568,
0.02403140626847744,
0.053115636110305786,
-0.044413480907678604,
0.030004100874066353,
0.01637832075357437,
-0.18624737858772278,
0.00820537656545639,
-0.019414430484175682,
-0.06297571212053299,
-0.006725030019879341,
0.04821323603391647,
-0.06390177458524704,
0.039030738174915314,
0.004405539948493242,
-0.08160654455423355,
-0.03914686292409897,
0.051553674042224884,
0.04499802738428116,
-0.009207485243678093,
0.1348673701286316,
-0.026577025651931763,
0.045689232647418976,
-0.12086553126573563,
-0.03971259295940399,
0.009649553336203098,
0.05307407304644585,
0.008113483898341656,
-0.023440226912498474,
0.014039233326911926,
-0.0038968375883996487,
0.16789813339710236,
-0.03211084380745888,
-0.04405141994357109,
0.05246264114975929,
0.009118999354541302,
0.015608273446559906,
0.0371633805334568,
0.026129307225346565,
-0.004506790544837713,
-0.013176611624658108,
-0.03552082180976868,
-0.06548570841550827,
-0.07760578393936157,
-0.1214577853679657,
0.07032988220453262,
0.19311466813087463,
0.12194909155368805,
-0.05884113907814026,
0.09163150191307068,
-0.08820178359746933,
-0.15837420523166656,
0.05468033254146576,
-0.005551960784941912,
-0.006352971773594618,
-0.05606149137020111,
0.07696574926376343,
0.15683096647262573,
-0.1924348622560501,
0.1270967721939087,
-0.0236863624304533,
-0.06278242915868759,
-0.029005693271756172,
-0.21587173640727997,
-0.034217316657304764,
-0.02786318026483059,
-0.012735686264932156,
-0.07981386035680771,
0.05162334069609642,
0.07275938242673874,
-0.0008785402169451118,
-0.012945580296218395,
0.10630834102630615,
-0.12273205071687698,
-0.062231820076704025,
-0.01285055186599493,
0.046709008514881134,
0.06159886345267296,
0.0788891538977623,
0.09039854258298874,
-0.01381688192486763,
0.07128071784973145,
0.08219083398580551,
0.056326668709516525,
0.002079528057947755,
-0.011730385012924671,
-0.00920858234167099,
-0.036466870456933975,
0.039610013365745544,
-0.009506233036518097,
-0.046946365386247635,
0.20983299612998962,
0.05347495526075363,
-0.007760138250887394,
0.0009780252585187554,
0.19635646045207977,
-0.041097331792116165,
-0.11485712230205536,
-0.18715715408325195,
0.08621181547641754,
-0.012817773967981339,
0.025372376665472984,
0.039419982582330704,
-0.10840076953172684,
0.040622517466545105,
0.14836789667606354,
0.16001081466674805,
-0.02400561235845089,
0.0081098647788167,
0.018833927810192108,
0.021001722663640976,
0.023372840136289597,
0.05794138461351395,
0.007444859016686678,
0.22614838182926178,
-0.043705448508262634,
0.04039400443434715,
-0.029048427939414978,
-0.06120401248335838,
-0.0444045327603817,
0.1087593212723732,
0.0031159836798906326,
-0.003814368974417448,
-0.06608699262142181,
0.085329569876194,
0.037407875061035156,
-0.2540709972381592,
0.03682928532361984,
-0.007913520559668541,
-0.08887796849012375,
0.014083445072174072,
0.05224430933594704,
-0.015820009633898735,
0.005005265586078167,
0.07731180638074875,
-0.03148580715060234,
0.22266064584255219,
0.060680486261844635,
-0.05017894506454468,
-0.002246604301035404,
0.1642419546842575,
0.016833806410431862,
0.2262679785490036,
0.0006109786918386817,
0.08865863084793091,
0.08914022892713547,
0.0024490985088050365,
-0.09981990605592728,
0.06645514070987701,
0.06750548630952835,
-0.06442251056432724,
-0.021697979420423508,
0.16328643262386322,
0.010833482258021832,
0.06930452585220337,
0.09241221845149994,
-0.06975466758012772,
0.020936602726578712,
-0.03927156701683998,
-0.056710951030254364,
-0.10147446393966675,
0.11372332274913788,
-0.11570071429014206,
0.12745603919029236,
0.12598460912704468,
-0.023360466584563255,
0.022014101967215538,
-0.04458929970860481,
0.05061184987425804,
0.027496328577399254,
0.1366834193468094,
0.003387742443010211,
-0.09948458522558212,
-0.020501622930169106,
-0.03895392641425133,
0.09464889019727707,
-0.19607557356357574,
-0.07941383868455887,
0.06929054856300354,
-0.006548041477799416,
-0.008997322991490364,
0.12116238474845886,
0.039550624787807465,
0.018859611824154854,
-0.043263185769319534,
-0.11540798097848892,
-0.006906997412443161,
0.09611653536558151,
-0.09811816364526749,
0.02096652239561081
] |
null | null | null | kjlkj
jkj | {"license": "mit"} | null | muser840/tessst | [
"license:mit",
"region:us"
] | 2024-02-11T07:44:06+00:00 | [] | [] | TAGS
#license-mit #region-us
| kjlkj
jkj | [] | [
"TAGS\n#license-mit #region-us \n"
] | [
11
] | [
"passage: TAGS\n#license-mit #region-us \n"
] | [
0.026221778243780136,
-0.033018264919519424,
-0.008281232789158821,
-0.05295303836464882,
0.052470896393060684,
0.06768012046813965,
0.1598525494337082,
0.04655371606349945,
0.23683255910873413,
-0.05407243221998215,
0.11752297729253769,
0.08923697471618652,
0.004284696187824011,
-0.0009730930323712528,
0.014216204173862934,
-0.17134642601013184,
0.04864625632762909,
-0.02878100797533989,
0.08764812350273132,
0.032233644276857376,
-0.006205103360116482,
-0.03845774009823799,
-0.0022142508532851934,
-0.03178790956735611,
-0.057939812541007996,
0.03869890421628952,
0.045729056000709534,
-0.02754949778318405,
0.14189864695072174,
-0.021783310920000076,
0.13335508108139038,
0.046146418899297714,
-0.011738095432519913,
-0.2486042082309723,
0.008575023151934147,
-0.07252951711416245,
-0.11333522200584412,
0.016201216727495193,
0.035761721432209015,
-0.010069100186228752,
0.032174937427043915,
0.11049123108386993,
-0.011680051684379578,
0.06288356333971024,
-0.2015703022480011,
-0.20486389100551605,
-0.07508610188961029,
-0.07555478066205978,
0.0589042492210865,
0.030872387811541557,
0.05628744140267372,
0.1426718831062317,
-0.18022038042545319,
-0.0018841808196157217,
0.04129622131586075,
-0.3510737717151642,
0.09011197835206985,
0.19666501879692078,
0.06407395005226135,
0.07872317731380463,
-0.04774639382958412,
0.06726468354463577,
0.07745297998189926,
-0.02402484230697155,
-0.10679105669260025,
-0.06142130121588707,
0.040939174592494965,
0.15604156255722046,
-0.03852643445134163,
-0.10356393456459045,
0.2591084837913513,
-0.023262828588485718,
-0.04234466329216957,
0.08201269060373306,
-0.02980397455394268,
-0.040379155427217484,
0.04404358193278313,
0.044016025960445404,
0.036236923187971115,
0.182089164853096,
0.1260262131690979,
-0.03375067934393883,
-0.16269677877426147,
-0.030629513785243034,
-0.2528207004070282,
0.07418664544820786,
-0.003647059667855501,
0.10666298121213913,
-0.20037521421909332,
0.03286786004900932,
-0.15483668446540833,
-0.009493621066212654,
-0.02952384203672409,
-0.059835705906152725,
0.05229754373431206,
-0.0237403754144907,
-0.04600388556718826,
0.07238677144050598,
0.08390641957521439,
0.2046167105436325,
0.023024363443255424,
0.016697337850928307,
-0.10405295342206955,
0.15052515268325806,
0.019140364602208138,
0.024860305711627007,
0.179348424077034,
0.07677878439426422,
-0.04891882464289665,
-0.2251969277858734,
0.027894439175724983,
-0.03671982139348984,
-0.1441805064678192,
0.015881337225437164,
-0.1542915552854538,
0.1736440360546112,
-0.04078168794512749,
-0.06919530034065247,
-0.08578147739171982,
0.09790384024381638,
0.07768166810274124,
-0.021921472623944283,
-0.023105677217245102,
-0.01381723117083311,
0.03522264584898949,
-0.048196230083703995,
-0.11687057465314865,
0.018241960555315018,
0.11869648098945618,
0.12573401629924774,
-0.1483907401561737,
-0.008189842104911804,
-0.017200417816638947,
0.019065292552113533,
0.09696817398071289,
-0.112403005361557,
0.028845038264989853,
-0.09672309458255768,
-0.13033071160316467,
0.036653537303209305,
0.017736904323101044,
-0.019008556380867958,
0.1340927630662918,
0.061849117279052734,
0.056560322642326355,
-0.011025321669876575,
-0.07250872999429703,
-0.14035539329051971,
-0.08679798245429993,
0.1058693379163742,
-0.046787332743406296,
0.010320915840566158,
-0.24556252360343933,
-0.014234079979360104,
-0.14995723962783813,
0.059662189334630966,
-0.0037668521981686354,
-0.08819212019443512,
-0.07740068435668945,
0.21408265829086304,
0.0018596589798107743,
0.04301392287015915,
-0.1078512966632843,
0.054903753101825714,
-0.06764797121286392,
0.10065380483865738,
-0.12895582616329193,
-0.06441528350114822,
0.1613781899213791,
-0.13135331869125366,
-0.14002031087875366,
0.0033312994055449963,
-0.009472889825701714,
0.12053907662630081,
0.0802001804113388,
0.44566696882247925,
-0.058881040662527084,
-0.16201181709766388,
0.1270403116941452,
0.17969723045825958,
-0.13685379922389984,
-0.25928929448127747,
0.12393020838499069,
-0.1636963188648224,
-0.16647985577583313,
0.0040023741312325,
-0.006962866988033056,
0.08049977570772171,
-0.03446655720472336,
-0.056274134665727615,
0.042339932173490524,
0.024350708350539207,
0.029094615951180458,
0.01740112341940403,
0.07037191838026047,
-0.1023021712899208,
0.08444856107234955,
0.058610700070858,
-0.014111426658928394,
0.15077349543571472,
0.011494536884129047,
-0.05393160134553909,
0.014761670492589474,
0.044013332575559616,
-0.015627963468432426,
-0.05899091437458992,
-0.09661509096622467,
0.019826244562864304,
-0.031149597838521004,
0.08229395002126694,
0.1699674129486084,
0.023824702948331833,
-0.02797185815870762,
0.028922779485583305,
0.028606392443180084,
0.1009954959154129,
0.06960704177618027,
0.03099375218153,
-0.04839283227920532,
0.04952205345034599,
-0.0417071171104908,
-0.11430390179157257,
-0.004862460307776928,
-0.011735930107533932,
0.11975742131471634,
-0.08906009048223495,
-0.01223952230066061,
0.05951591953635216,
-0.04513183981180191,
0.0019881438929587603,
0.0428374819457531,
0.0035966038703918457,
0.1388600617647171,
0.004440935328602791,
-0.04352007433772087,
0.17440910637378693,
-0.05288633331656456,
0.15533447265625,
0.1715822070837021,
-0.07049662619829178,
0.015605369582772255,
-0.1273636519908905,
0.003230511210858822,
-0.014480113983154297,
0.05292887985706329,
-0.05400136485695839,
-0.05201306566596031,
-0.01274962443858385,
0.014292534440755844,
-0.03134604170918465,
0.01711403578519821,
-0.06057267636060715,
-0.08167021721601486,
-0.10849859565496445,
0.018649224191904068,
0.20683221518993378,
-0.22544461488723755,
0.1609548032283783,
0.40251004695892334,
0.15190774202346802,
0.21155193448066711,
-0.12478897720575333,
-0.002471078187227249,
-0.06630261242389679,
0.026115071028470993,
-0.024814706295728683,
0.13782677054405212,
-0.13174867630004883,
-0.01413064356893301,
0.03880728408694267,
0.0454997681081295,
0.0661163181066513,
-0.17195898294448853,
-0.15260353684425354,
-0.0034879595041275024,
-0.020591814070940018,
-0.1749730259180069,
0.04874620959162712,
-0.07595308125019073,
0.02181261032819748,
0.018216799944639206,
-0.10832522064447403,
0.16837291419506073,
-0.033566512167453766,
-0.06695768237113953,
0.052613962441682816,
-0.20581911504268646,
-0.07900715619325638,
-0.17772749066352844,
-0.18375012278556824,
0.06050071492791176,
0.05760138854384422,
0.07903145253658295,
-0.05951719731092453,
-0.01922747679054737,
0.061719246208667755,
-0.009363299235701561,
-0.13802112638950348,
-0.04235544428229332,
-0.06993678212165833,
0.08744155615568161,
-0.09474305808544159,
-0.07518411427736282,
-0.07833878695964813,
-0.046996138989925385,
-0.020961694419384003,
0.08125963062047958,
-0.1039251759648323,
0.08903530240058899,
0.1493726521730423,
0.03651920333504677,
0.05440247058868408,
-0.08271230012178421,
0.12693379819393158,
-0.037743739783763885,
-0.09459595382213593,
0.07307634502649307,
0.004350725095719099,
0.04920351505279541,
0.24039287865161896,
0.08962162584066391,
-0.10578162968158722,
-0.01780811697244644,
-0.0968487411737442,
-0.16405464708805084,
-0.2553846538066864,
-0.06823288649320602,
-0.08744750916957855,
0.14417944848537445,
0.014636521227657795,
0.10712126642465591,
0.14313316345214844,
0.01343101728707552,
0.10255914181470871,
-0.08983208239078522,
-0.018939344212412834,
0.031209396198391914,
0.2135104089975357,
-0.05208220332860947,
0.00838248711079359,
-0.13684824109077454,
-0.0256142970174551,
0.14601100981235504,
0.13798639178276062,
0.14503207802772522,
0.31421369314193726,
0.15292863547801971,
0.13410434126853943,
0.13474710285663605,
0.12333164364099503,
0.07403261214494705,
0.03444362059235573,
-0.015304201282560825,
-0.06035377085208893,
-0.003846159903332591,
0.02816268615424633,
0.05421729013323784,
0.06724072247743607,
-0.22906480729579926,
0.041139665991067886,
-0.2661744952201843,
0.03544611483812332,
-0.0854712724685669,
0.1161833181977272,
-0.028890252113342285,
0.11051984131336212,
0.11386284977197647,
0.05553818494081497,
-0.023278791457414627,
0.16036942601203918,
0.032686375081539154,
-0.07703183591365814,
0.020292721688747406,
0.024695809930562973,
0.06633034348487854,
0.08606193959712982,
0.09550496190786362,
-0.020778406411409378,
-0.1831783503293991,
0.025963841006159782,
0.12212833017110825,
-0.20747940242290497,
0.289523184299469,
0.013651901856064796,
-0.0743619054555893,
-0.01690039224922657,
-0.06958060711622238,
0.008433517068624496,
0.12829731404781342,
0.10406835377216339,
0.05508929491043091,
-0.2613787055015564,
-0.13299626111984253,
0.046764206141233444,
-0.00873907096683979,
0.11356569826602936,
-0.0052223424427211285,
-0.14201195538043976,
-0.06640999764204025,
0.05814211815595627,
-0.006591420155018568,
0.13023322820663452,
-0.018290361389517784,
-0.08173255622386932,
-0.010230090469121933,
0.055564697831869125,
-0.001312803477048874,
-0.04580084979534149,
0.07523149996995926,
0.009008137509226799,
0.02259289287030697,
-0.08178020268678665,
0.03887253627181053,
-0.08071476966142654,
-0.25375792384147644,
0.019298138096928596,
-0.04987313598394394,
0.004092312417924404,
-0.04684043675661087,
-0.15448936820030212,
-0.1129264086484909,
-0.15445278584957123,
0.13100723922252655,
-0.03675999864935875,
0.091565802693367,
-0.0817658007144928,
0.13736046850681305,
-0.08521489799022675,
0.05375019088387489,
0.00614814180880785,
0.03918716683983803,
-0.017955513671040535,
-0.1031481996178627,
0.09334362298250198,
-0.1874227225780487,
0.023863423615694046,
0.010427716188132763,
-0.056847453117370605,
-0.01354232057929039,
0.03918023407459259,
-0.08763083070516586,
0.21879427134990692,
0.3331502079963684,
-0.011948764324188232,
0.22546616196632385,
0.35863226652145386,
-0.13763751089572906,
-0.23258967697620392,
-0.1205512136220932,
-0.3263251483440399,
-0.09005610644817352,
0.17321562767028809,
-0.18057219684123993,
0.04850830137729645,
0.16150830686092377,
-0.10868281871080399,
0.22499866783618927,
-0.22723928093910217,
-0.04793389141559601,
0.1823979914188385,
-0.038322996348142624,
0.4527989625930786,
-0.1144307404756546,
-0.1784561723470688,
-0.03637253865599632,
-0.16285361349582672,
0.12426037341356277,
-0.026553882285952568,
0.06700495630502701,
0.02416347898542881,
-0.011372359469532967,
-0.009014161303639412,
-0.04529716446995735,
0.2216065675020218,
0.0522729866206646,
0.10468899458646774,
-0.09159468114376068,
-0.17199653387069702,
0.1907423883676529,
-0.0004908236442133784,
-0.003372655250132084,
-0.05411549657583237,
-0.04850282520055771,
-0.06871756166219711,
0.033092137426137924,
-0.0334564633667469,
0.06195882335305214,
0.03364093229174614,
-0.11903523653745651,
-0.10248823463916779,
0.034111104905605316,
-0.13155671954154968,
-0.054850947111845016,
0.26421889662742615,
-0.02080743946135044,
0.09609334170818329,
0.04959092289209366,
-0.05474294349551201,
-0.13538943231105804,
0.005736751481890678,
-0.07534020394086838,
-0.05711410939693451,
0.06573604047298431,
-0.11453206837177277,
-0.024341827258467674,
0.1293732225894928,
-0.029497180134058,
0.09674722701311111,
0.08061115443706512,
-0.07585363835096359,
0.02032829262316227,
0.15617427229881287,
-0.07247176766395569,
-0.10849180817604065,
0.04999847710132599,
0.04640531167387962,
0.17256882786750793,
0.004101871978491545,
0.02018604800105095,
0.08726977556943893,
0.045959215611219406,
-0.007486662827432156,
0.007311292923986912,
-0.11321697384119034,
-0.04241771996021271,
0.0387241393327713,
-0.005273692775517702,
-0.10946331918239594,
0.16008898615837097,
0.056837860494852066,
0.004653505515307188,
-0.06027700752019882,
0.09720424562692642,
-0.06709636747837067,
-0.07046061009168625,
-0.1753035932779312,
0.018511172384023666,
-0.12734080851078033,
-0.09874535351991653,
0.06846235692501068,
-0.09371624886989594,
-0.04084605351090431,
0.08152704685926437,
0.046927981078624725,
0.14401860535144806,
-0.006597559433430433,
-0.023080874234437943,
0.149825319647789,
-0.0884878933429718,
-0.2241756170988083,
0.01969664730131626,
-0.04083063453435898,
-0.07065816223621368,
-0.0007070365245454013,
0.06069544702768326,
-0.0663156732916832,
-0.11958606541156769,
-0.20477768778800964,
0.10412076860666275,
-0.12043121457099915,
-0.03954985365271568,
-0.1041841059923172,
-0.053260523825883865,
0.07891252636909485,
-0.02613759972155094,
-0.04122013971209526,
-0.047595683485269547,
-0.16630595922470093,
0.054254453629255295,
0.07140932232141495,
0.11125344783067703,
-0.0759999230504036,
-0.018354382365942,
0.1398727148771286,
0.048581548035144806,
0.08479110151529312,
0.07578440010547638,
0.026255371049046516,
0.16728560626506805,
-0.1708206981420517,
-0.0542997270822525,
0.1068294569849968,
-0.026716172695159912,
0.01994573324918747,
0.10631280392408371,
-0.04839588701725006,
0.07042654603719711,
-0.05095988139510155,
0.05859163776040077,
-0.15704534947872162,
-0.13073866069316864,
-0.04184387996792793,
0.023728877305984497,
-0.2260182797908783,
0.015071595087647438,
-0.1769561767578125,
0.19692228734493256,
-0.024228032678365707,
0.11490963399410248,
0.08052190393209457,
0.02052290178835392,
0.03539382666349411,
-0.006019921973347664,
0.00946811307221651,
-0.10524865239858627,
-0.05784677714109421,
-0.07560300827026367,
-0.1168874129652977,
-0.009665017947554588,
0.36614301800727844,
0.02430291846394539,
-0.19682736694812775,
0.051222387701272964,
0.18285293877124786,
0.023639049381017685,
-0.0073763905093073845,
0.26180747151374817,
0.08150359988212585,
-0.023175053298473358,
-0.1782374382019043,
0.0396091528236866,
-0.08699734508991241,
-0.15269799530506134,
0.11385007947683334,
0.09347525984048843,
0.05813581123948097,
0.022930078208446503,
0.10404518246650696,
-0.035940010100603104,
-0.05509711429476738,
-0.13301853835582733,
0.13368983566761017,
-0.001790675800293684,
0.0193882267922163,
0.0897885113954544,
0.19249756634235382,
-0.045275162905454636,
0.05437124893069267,
-0.07336640357971191,
-0.001598604372702539,
-0.15740543603897095,
-0.13358698785305023,
0.06194563955068588,
-0.08269550651311874,
0.06342913210391998,
0.050261519849300385,
0.04341990500688553,
0.31786394119262695,
0.039095040410757065,
-0.046439893543720245,
0.003166865324601531,
-0.14845187962055206,
-0.08075450360774994,
-0.06024569645524025,
-0.03110554814338684,
0.028620192781090736,
-0.13928957283496857,
-0.09898591786623001,
-0.06917677819728851,
-0.130235955119133,
-0.06539803743362427,
0.025270747020840645,
0.014251931570470333,
-0.053083837032318115,
-0.17625881731510162,
-0.04808593541383743,
-0.06644169986248016,
0.10105955600738525,
-0.08462738990783691,
0.1516820639371872,
0.0022449472453445196,
0.030281953513622284,
0.07627002149820328,
0.09585131704807281,
0.018900424242019653,
-0.06975197046995163,
0.05599058046936989,
0.12436293810606003,
0.01323844213038683,
0.1259988248348236,
-0.06034265458583832,
-0.019420607015490532,
-0.014145253226161003,
0.14038437604904175,
0.304447740316391,
-0.01856905221939087,
-0.013814439997076988,
-0.022110093384981155,
0.021388787776231766,
0.10893569141626358,
0.19800719618797302,
-0.03437356278300285,
0.2551359534263611,
-0.058974795043468475,
0.0756678432226181,
-0.013180435635149479,
-0.005362013820558786,
-0.053146667778491974,
0.06074550002813339,
0.06268858164548874,
-0.06877048313617706,
-0.10191375762224197,
0.15178529918193817,
-0.14985080063343048,
0.13306055963039398,
0.14678068459033966,
-0.06057753041386604,
0.03797250986099243,
0.0007459368789568543,
0.19896264374256134,
-0.03570213168859482,
0.0984780564904213,
-0.10653308779001236,
-0.10261140763759613,
-0.14764924347400665,
0.037690844386816025,
-0.36797797679901123,
-0.1756322830915451,
0.11731542646884918,
0.14115898311138153,
0.1759258657693863,
-0.012341637164354324,
0.056479312479496,
0.0033020609989762306,
0.08296097069978714,
-0.04232487455010414,
0.1519634872674942,
0.0612073615193367,
-0.017103128135204315,
-0.15296664834022522,
-0.20328094065189362,
-0.0012039330322295427,
-0.058561209589242935,
0.055583830922842026,
-0.02269243635237217,
0.025347469374537468,
0.07746459543704987,
-0.06768939644098282,
-0.029180381447076797,
-0.02352982573211193,
-0.13262848556041718,
0.052229251712560654,
-0.04354005306959152,
0.0320255309343338,
-0.03958037868142128,
-0.022394726052880287,
-0.039987675845623016,
0.10721533745527267,
-0.22402705252170563,
-0.08517231047153473,
0.1422796994447708,
-0.03421911224722862,
0.1542559564113617,
-0.02848726324737072,
-0.12159585952758789,
-0.024955326691269875,
-0.06977712363004684,
0.10887379199266434,
-0.1419300138950348,
0.038592495024204254,
0.13747453689575195,
0.008710617199540138,
0.031119761988520622,
-0.2533661723136902,
0.050644006580114365,
-0.03556957095861435,
-0.016733208671212196,
-0.057031940668821335
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# opt-1.3b-lora-3.15M-squad-model3
This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| {"license": "other", "tags": ["generated_from_trainer"], "datasets": ["varun-v-rao/squad"], "base_model": "facebook/opt-1.3b", "model-index": [{"name": "opt-1.3b-lora-3.15M-squad-model3", "results": []}]} | question-answering | varun-v-rao/opt-1.3b-lora-3.15M-squad-model3 | [
"transformers",
"tensorboard",
"safetensors",
"opt",
"question-answering",
"generated_from_trainer",
"dataset:varun-v-rao/squad",
"base_model:facebook/opt-1.3b",
"license:other",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T07:48:03+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #opt #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-facebook/opt-1.3b #license-other #endpoints_compatible #text-generation-inference #region-us
|
# opt-1.3b-lora-3.15M-squad-model3
This model is a fine-tuned version of facebook/opt-1.3b on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
| [
"# opt-1.3b-lora-3.15M-squad-model3\n\nThis model is a fine-tuned version of facebook/opt-1.3b on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 16\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
"TAGS\n#transformers #tensorboard #safetensors #opt #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-facebook/opt-1.3b #license-other #endpoints_compatible #text-generation-inference #region-us \n",
"# opt-1.3b-lora-3.15M-squad-model3\n\nThis model is a fine-tuned version of facebook/opt-1.3b on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 16\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3",
"### Training results",
"### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
81,
42,
6,
12,
8,
3,
90,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #opt #question-answering #generated_from_trainer #dataset-varun-v-rao/squad #base_model-facebook/opt-1.3b #license-other #endpoints_compatible #text-generation-inference #region-us \n# opt-1.3b-lora-3.15M-squad-model3\n\nThis model is a fine-tuned version of facebook/opt-1.3b on the squad dataset.## Model description\n\nMore information needed## Intended uses & limitations\n\nMore information needed## Training and evaluation data\n\nMore information needed## Training procedure### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 2e-05\n- train_batch_size: 16\n- eval_batch_size: 16\n- seed: 42\n- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n- lr_scheduler_type: linear\n- num_epochs: 3### Training results### Framework versions\n\n- Transformers 4.35.2\n- Pytorch 2.1.1+cu121\n- Datasets 2.15.0\n- Tokenizers 0.15.0"
] | [
-0.10462117195129395,
0.1689022183418274,
-0.003429478732869029,
0.07321623712778091,
0.11982171982526779,
0.0021459993440657854,
0.10698521882295609,
0.13735558092594147,
-0.05435803532600403,
0.09059516340494156,
0.07163053005933762,
0.018197232857346535,
0.06677865236997604,
0.17397475242614746,
-0.04664761945605278,
-0.17438904941082,
0.01859092153608799,
-0.02731332741677761,
-0.06848699599504471,
0.09460638463497162,
0.1005498543381691,
-0.09260378777980804,
0.08339473605155945,
-0.00119278475176543,
-0.11848343908786774,
0.0440286360681057,
-0.016883159056305885,
-0.058742474764585495,
0.08314976096153259,
0.03545844927430153,
0.0712108314037323,
0.029129136353731155,
0.10113087296485901,
-0.2520751655101776,
0.006470707710832357,
0.07909846305847168,
-0.0038801184855401516,
0.072948157787323,
0.03835016116499901,
-0.0033399180974811316,
0.07343090325593948,
-0.16781480610370636,
0.1025923639535904,
0.029110560193657875,
-0.09764080494642258,
-0.18500663340091705,
-0.09871339797973633,
0.10516567528247833,
0.10408301651477814,
0.09906904399394989,
-0.016348928213119507,
0.1409418135881424,
-0.060342270880937576,
0.06685780733823776,
0.20506244897842407,
-0.2564203143119812,
-0.05668555572628975,
0.018471552059054375,
0.04989039897918701,
0.0660281628370285,
-0.09821977466344833,
0.011466068215668201,
0.05996327847242355,
0.023049023002386093,
0.08086908608675003,
-0.005839300807565451,
-0.027747953310608864,
-0.015232343226671219,
-0.12728941440582275,
-0.0421011745929718,
0.20255164802074432,
0.07616888731718063,
-0.04969380795955658,
-0.11730190366506577,
-0.039772577583789825,
-0.038956835865974426,
-0.0034533252473920584,
-0.06410567462444305,
0.020117152482271194,
-0.04862295463681221,
-0.053711213171482086,
-0.06876007467508316,
-0.08958499878644943,
-0.038752246648073196,
0.026193691417574883,
0.04186037555336952,
0.036770664155483246,
0.02202712558209896,
-0.03589129075407982,
0.08064395934343338,
-0.01325868722051382,
-0.13776540756225586,
-0.015044203959405422,
-0.012564611621201038,
-0.09545927494764328,
-0.06341460347175598,
-0.013328512199223042,
-0.028324835002422333,
0.009480619803071022,
0.154766246676445,
-0.0667608231306076,
0.06013786792755127,
-0.017486589029431343,
-0.002270682482048869,
-0.006272020284086466,
0.11316023021936417,
-0.03334594517946243,
-0.047121308743953705,
0.009510202333331108,
0.11598725616931915,
0.022637080401182175,
-0.013174369931221008,
-0.07235024869441986,
-0.01812957413494587,
0.08771412819623947,
0.07875116169452667,
-0.003023495664820075,
0.0067599862813949585,
-0.04754309728741646,
-0.029179058969020844,
0.06884702295064926,
-0.1240459531545639,
0.04918482154607773,
-0.004221267066895962,
-0.06055593490600586,
-0.08422425389289856,
0.036822471767663956,
-0.0010377486469224095,
-0.030822983011603355,
0.033746570348739624,
-0.05973165109753609,
-0.018486591055989265,
-0.049779437482357025,
-0.043632812798023224,
0.03777754306793213,
-0.054371245205402374,
-0.008000252768397331,
-0.0782909020781517,
-0.18885108828544617,
-0.03727062791585922,
0.024591078981757164,
-0.06700791418552399,
-0.05450811609625816,
-0.016246898099780083,
-0.060997627675533295,
0.0034537743777036667,
-0.02633007802069187,
0.09242226183414459,
-0.040290046483278275,
0.06179096922278404,
0.027351809665560722,
0.032571401447057724,
0.0639435276389122,
0.03940557315945625,
-0.07044073194265366,
0.05175019055604935,
-0.13230809569358826,
0.0763033926486969,
-0.1060144379734993,
0.01607309654355049,
-0.12381809949874878,
-0.08846465498209,
0.012538881972432137,
-0.021733799949288368,
0.0669320747256279,
0.1285545527935028,
-0.16470813751220703,
-0.036332402378320694,
0.15774746239185333,
-0.11033524572849274,
-0.13603612780570984,
0.12299599498510361,
-0.04667850583791733,
0.009784787893295288,
0.06220673769712448,
0.1513710767030716,
0.13227157294750214,
-0.18313205242156982,
-0.040473539382219315,
0.008769497275352478,
0.05048804357647896,
0.020192034542560577,
0.05990444868803024,
-0.007661894895136356,
0.06449194252490997,
0.007362323813140392,
-0.07728396356105804,
-0.0026254502590745687,
-0.06635694950819016,
-0.08993758261203766,
-0.050885844975709915,
-0.0843726247549057,
0.03919922187924385,
0.051262930035591125,
0.0010932828299701214,
-0.09184575825929642,
-0.1226453110575676,
0.07199807465076447,
0.1155625432729721,
-0.0425049290060997,
0.004595848731696606,
-0.07768663763999939,
0.07837359607219696,
-0.04659770056605339,
-0.026570521295070648,
-0.17768505215644836,
-0.13113577663898468,
0.029825950041413307,
-0.07212461531162262,
0.01855066977441311,
0.040553223341703415,
0.05656272545456886,
0.057991981506347656,
-0.06373700499534607,
-0.03503040969371796,
-0.10312937945127487,
0.005335986614227295,
-0.08086635917425156,
-0.17857015132904053,
-0.05085736885666847,
-0.04298144206404686,
0.1788567751646042,
-0.23449137806892395,
0.03148993104696274,
0.0275539793074131,
0.16006584465503693,
0.031146671622991562,
-0.04314533248543739,
0.003548565786331892,
0.00831630825996399,
0.004248561803251505,
-0.08908597379922867,
0.02262459322810173,
-0.0011804995592683554,
-0.07441400736570358,
-0.05188801512122154,
-0.13565415143966675,
0.09520634263753891,
0.08608944714069366,
0.07191493362188339,
-0.08700396120548248,
-0.013689808547496796,
-0.06409331411123276,
-0.027272358536720276,
-0.09034483879804611,
-0.0264707300812006,
0.18683862686157227,
0.023833440616726875,
0.10764859616756439,
-0.08410100638866425,
-0.0750223770737648,
0.011049782857298851,
-0.013086354359984398,
-0.05197698250412941,
0.08018922805786133,
0.04365198314189911,
-0.14832915365695953,
0.11659599095582962,
0.12035176157951355,
0.031522516161203384,
0.13031752407550812,
-0.05699188634753227,
-0.0891651064157486,
-0.043172843754291534,
0.033023592084646225,
-0.008195609785616398,
0.14292652904987335,
-0.07927063852548599,
0.0006720766541548073,
0.026261677965521812,
-0.0001093101964215748,
0.025208959355950356,
-0.14890487492084503,
-0.018425773829221725,
0.03210408240556717,
-0.0548393614590168,
0.0023758572060614824,
-0.022919446229934692,
0.03628213703632355,
0.0870741456747055,
0.023268863558769226,
-0.0018462555017322302,
0.02591538429260254,
-0.023397181183099747,
-0.09549979120492935,
0.16364772617816925,
-0.10131843388080597,
-0.2203362137079239,
-0.11620360612869263,
0.07511343061923981,
-0.05066371336579323,
-0.027283353731036186,
0.024054862558841705,
-0.10062440484762192,
-0.06413982063531876,
-0.09894318133592606,
-0.00010448673128848895,
-0.009081095457077026,
-0.03278180956840515,
0.06605619192123413,
0.035861462354660034,
0.11156192421913147,
-0.11494605988264084,
0.005106332711875439,
-0.010930603370070457,
-0.05691007152199745,
-0.027786295861005783,
0.04453922435641289,
0.09992972761392593,
0.06790471822023392,
-0.014491460286080837,
0.03190118446946144,
-0.036046672612428665,
0.2310154289007187,
-0.0930914357304573,
0.00988333486020565,
0.1452503353357315,
0.003369384678080678,
0.0608808808028698,
0.12929514050483704,
0.0022439344320446253,
-0.10136502981185913,
0.03658969700336456,
0.07668300718069077,
-0.01287051010876894,
-0.2447066456079483,
-0.04429694265127182,
-0.02318352647125721,
-0.04084562882781029,
0.09326086938381195,
0.05413855239748955,
0.03106609918177128,
0.04075364023447037,
-0.04047081619501114,
0.0017545599257573485,
0.009359300136566162,
0.07843993604183197,
0.09698840975761414,
0.027938837185502052,
0.0897512435913086,
-0.04568425938487053,
-0.029490917921066284,
0.07564626634120941,
-0.000854726298712194,
0.24754175543785095,
-0.01811535656452179,
0.09556718915700912,
0.04093100130558014,
0.15943670272827148,
-0.037636786699295044,
0.0036817705258727074,
0.01892033778131008,
-0.008052927441895008,
0.010018629021942616,
-0.05603906512260437,
-0.021873094141483307,
0.041761498898267746,
-0.003288819221779704,
0.03037283383309841,
-0.09663619846105576,
0.06343556940555573,
0.03627854958176613,
0.22544051706790924,
0.0658394992351532,
-0.2570863664150238,
-0.07676027715206146,
0.03118516318500042,
-0.02855793945491314,
-0.05026106908917427,
0.0018708943389356136,
0.14403732120990753,
-0.12056206911802292,
0.08945336192846298,
-0.056422729045152664,
0.08772537112236023,
-0.01933974400162697,
0.005310641136020422,
0.03466448560357094,
0.06840687245130539,
-0.001501785358414054,
0.09842371940612793,
-0.17950424551963806,
0.2153393030166626,
0.023155445232987404,
0.10176107287406921,
-0.07307811826467514,
0.042726147919893265,
0.00021122123871464282,
0.07455118745565414,
0.14735794067382812,
-0.004185840487480164,
-0.07620757818222046,
-0.1380416750907898,
-0.08727084845304489,
0.0206967331469059,
0.09276127815246582,
-0.04973118379712105,
0.07942967116832733,
-0.03489219397306442,
-0.0015539850573986769,
0.03688162565231323,
-0.007968949154019356,
-0.1523454636335373,
-0.14174631237983704,
0.01513682957738638,
-0.02934972010552883,
-0.04707388952374458,
-0.10011634230613708,
-0.09590145200490952,
-0.04478837549686432,
0.19008874893188477,
0.015968358144164085,
-0.05588845908641815,
-0.14213424921035767,
0.08369462192058563,
0.11226720362901688,
-0.07606004923582077,
0.005908234044909477,
0.03588943928480148,
0.15318182110786438,
0.011896929703652859,
-0.08830488473176956,
0.05115332454442978,
-0.07066930830478668,
-0.17678384482860565,
-0.044941578060388565,
0.17115327715873718,
0.051161523908376694,
0.03996867313981056,
0.030061936005949974,
0.011844526045024395,
0.024398641660809517,
-0.08489471673965454,
0.05211581662297249,
0.0201976727694273,
0.09315845370292664,
0.04926501214504242,
-0.03545549511909485,
-0.029605288058519363,
-0.04978999122977257,
-0.012651054188609123,
0.10498158633708954,
0.2430204451084137,
-0.08081376552581787,
0.08979859948158264,
0.07720009982585907,
-0.07613546401262283,
-0.15992814302444458,
0.05473865196108818,
0.07529769092798233,
0.005564275663346052,
0.08261987566947937,
-0.14780119061470032,
0.09200146794319153,
0.0922616720199585,
-0.026087142527103424,
0.022066915407776833,
-0.2681731581687927,
-0.12903901934623718,
0.08523567765951157,
0.10314515978097916,
-0.005919068120419979,
-0.13603945076465607,
-0.04551507532596588,
-0.029172632843255997,
-0.13337045907974243,
0.1123981848359108,
-0.13794387876987457,
0.06385090202093124,
0.004552788101136684,
0.05891262739896774,
0.026578262448310852,
-0.03761253133416176,
0.1508142501115799,
0.025152768939733505,
0.09058158099651337,
-0.0684603601694107,
0.024433352053165436,
0.13271638751029968,
-0.07023170590400696,
0.08135240525007248,
-0.039215683937072754,
0.0597941018640995,
-0.15186098217964172,
-0.027972474694252014,
-0.07583780586719513,
0.06467651575803757,
-0.07440312951803207,
-0.043284378945827484,
-0.055564988404512405,
0.07299000024795532,
0.06477783620357513,
-0.029360812157392502,
0.06297410279512405,
0.017936192452907562,
0.11658851057291031,
0.12467571347951889,
0.11514893174171448,
0.021978536620736122,
-0.10809746384620667,
0.001374159473925829,
-0.02900240756571293,
0.039973363280296326,
-0.10439462959766388,
0.04878245294094086,
0.11178729683160782,
0.02355533093214035,
0.15453991293907166,
-0.0011114344233646989,
-0.0890994444489479,
0.001226864755153656,
0.03419950604438782,
-0.11905822157859802,
-0.1827763468027115,
-0.021126095205545425,
-0.03166772797703743,
-0.15387681126594543,
0.008523772470653057,
0.11351101845502853,
-0.03928956389427185,
-0.01813371293246746,
-0.027665914967656136,
0.04158768802881241,
0.00010063761874334887,
0.14800474047660828,
0.062151949852705,
0.07153404504060745,
-0.07529310882091522,
0.11885883659124374,
0.06747721880674362,
-0.08844014257192612,
0.08223552256822586,
0.051069844514131546,
-0.0794714167714119,
-0.03587239608168602,
0.054246991872787476,
0.18132711946964264,
0.01112379226833582,
-0.05632646381855011,
-0.09667278081178665,
-0.10120166093111038,
0.05436063930392265,
0.1195899248123169,
0.0344635546207428,
-0.035380925983190536,
0.0066531323827803135,
0.01113908365368843,
-0.12629227340221405,
0.12140186876058578,
0.048293642699718475,
0.040148377418518066,
-0.14824502170085907,
0.059213753789663315,
0.004772566724568605,
0.042288295924663544,
-0.02147362008690834,
0.029653290286660194,
-0.08861930668354034,
-0.016103995963931084,
-0.15133945643901825,
-0.002253890037536621,
-0.03393324837088585,
0.008645698428153992,
-0.026900526136159897,
-0.07664360105991364,
-0.045689906924963,
0.045112814754247665,
-0.06346243619918823,
-0.05585828050971031,
0.029091855511069298,
0.051129017025232315,
-0.1854962855577469,
-0.035297274589538574,
0.030037423595786095,
-0.09250608831644058,
0.08542986959218979,
0.03940789774060249,
0.0376652367413044,
0.01705987937748432,
-0.06647886335849762,
-0.0005161741282790899,
0.0192649494856596,
0.041775304824113846,
0.05998332053422928,
-0.13428212702274323,
0.006034803111106157,
-0.01149661559611559,
0.005080296192318201,
0.03387132287025452,
0.034591227769851685,
-0.10568861663341522,
-0.01432823296636343,
-0.04447537288069725,
-0.062052156776189804,
-0.047338761389255524,
0.064582459628582,
0.10633233934640884,
0.014985400252044201,
0.1582205444574356,
-0.08717206865549088,
0.05045408010482788,
-0.22849588096141815,
-0.039513200521469116,
0.010269159451127052,
-0.015940822660923004,
-0.015120637603104115,
-0.030921095982193947,
0.0819433405995369,
-0.056032776832580566,
0.11980727314949036,
-0.00244423421099782,
0.1295870989561081,
0.05487208068370819,
-0.056686993688344955,
0.005339522380381823,
0.0160147063434124,
0.10872479528188705,
0.026604853570461273,
-0.015257745049893856,
0.09065093100070953,
-0.05042354390025139,
0.06512472033500671,
-0.007093525491654873,
0.16501514613628387,
0.1610518991947174,
-0.01058225054293871,
0.039468783885240555,
0.09359083324670792,
-0.11863250285387039,
-0.1194869726896286,
0.057413529604673386,
-0.06245395541191101,
0.08659303933382034,
-0.037942107766866684,
0.09640884399414062,
0.11312508583068848,
-0.18580812215805054,
0.05452283099293709,
-0.05962081626057625,
-0.10104350000619888,
-0.10345057398080826,
-0.07720140367746353,
-0.0824185386300087,
-0.10341745615005493,
0.034897223114967346,
-0.12814509868621826,
0.004532556515187025,
0.06344879418611526,
-0.0023741198237985373,
-0.01819094456732273,
0.1603163182735443,
-0.00720742205157876,
0.008213081397116184,
0.06443417817354202,
0.02022755891084671,
0.001872632885351777,
-0.05094955861568451,
-0.01756277307868004,
0.05996331945061684,
0.021216673776507378,
0.062462080270051956,
-0.026190135627985,
0.005570778623223305,
0.03369176760315895,
-0.005831041373312473,
-0.08628195524215698,
0.011870165355503559,
0.008206178434193134,
0.023094821721315384,
0.06740879267454147,
0.051426224410533905,
0.028295358642935753,
-0.03890681266784668,
0.23867888748645782,
-0.05363035202026367,
-0.04913885146379471,
-0.14813652634620667,
0.11345077306032181,
0.022640995681285858,
-0.001605847617611289,
0.07009958475828171,
-0.1235649585723877,
0.004300715401768684,
0.1292959600687027,
0.13754317164421082,
-0.04013208672404289,
0.0060606482438743114,
-0.02356599271297455,
-0.01049689669162035,
-0.03619249537587166,
0.08055248856544495,
0.1011756882071495,
0.024152372032403946,
-0.05380980297923088,
0.0021694127935916185,
0.0022082955110818148,
-0.040635835379362106,
-0.05731659755110741,
0.08769354224205017,
0.01650422438979149,
0.03810907155275345,
-0.026599450036883354,
0.08803234249353409,
0.026800040155649185,
-0.21802936494350433,
0.04843159392476082,
-0.18826282024383545,
-0.18244074285030365,
-0.010029924102127552,
0.08009316027164459,
-0.013132459484040737,
0.04511380195617676,
0.004302303772419691,
0.0005286175874061882,
0.14482910931110382,
-0.003975278697907925,
-0.06654395908117294,
-0.10425591468811035,
0.09201987087726593,
-0.11715620011091232,
0.235214963555336,
-0.0010307006305083632,
0.05190514773130417,
0.10492763668298721,
-0.027688583359122276,
-0.1397620290517807,
0.03194200620055199,
0.0863456055521965,
-0.021830899640917778,
0.01952522248029709,
0.15743017196655273,
-0.03361039608716965,
0.10445388406515121,
0.07973489165306091,
-0.10698791593313217,
-0.036068711429834366,
-0.061722755432128906,
-0.0044930619187653065,
-0.09023105353116989,
0.043920330703258514,
-0.07499406486749649,
0.1549375355243683,
0.1685851514339447,
-0.04828448221087456,
0.011975253000855446,
-0.06452544778585434,
0.03657878562808037,
0.05799446627497673,
0.09930766373872757,
0.009995192289352417,
-0.17714227735996246,
0.026433544233441353,
0.04378795996308327,
0.03977818414568901,
-0.26280319690704346,
-0.10072578489780426,
0.0593559704720974,
-0.050339989364147186,
-0.059607941657304764,
0.11046463996171951,
0.06376320868730545,
0.040257684886455536,
-0.04143720120191574,
-0.08391212671995163,
-0.05418500304222107,
0.14462365210056305,
-0.13733533024787903,
-0.019049420952796936
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tinystories_1layer_attn_mlp_C25k_k16_mse_weighted
This model is a fine-tuned version of [roneneldan/TinyStories-1Layer-21M](https://huggingface.co/roneneldan/TinyStories-1Layer-21M) on the roneneldan/TinyStories dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0353
- Accuracy: 0.5194
- Multicode K: 1
- Dead Code Fraction/layer0: 0.1640
- Mse/layer0: 501.8128
- Input Norm/layer0: 31.9989
- Output Norm/layer0: 22.8009
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Multicode K | Dead Code Fraction/layer0 | Mse/layer0 | Input Norm/layer0 | Output Norm/layer0 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------:|:-------------------------:|:----------:|:-----------------:|:------------------:|
| 2.8364 | 0.05 | 500 | 2.7649 | 0.4227 | 1 | 0.3619 | 634.8932 | 31.9979 | 18.0819 |
| 2.3611 | 0.1 | 1000 | 2.3705 | 0.4712 | 1 | 0.3607 | 568.7264 | 31.9979 | 20.6630 |
| 2.2395 | 0.15 | 1500 | 2.2531 | 0.4866 | 1 | 0.3266 | 550.3311 | 31.9979 | 21.3297 |
| 2.1999 | 0.2 | 2000 | 2.1908 | 0.4955 | 1 | 0.3048 | 539.0150 | 31.9980 | 21.7663 |
| 2.1688 | 0.25 | 2500 | 2.1551 | 0.5006 | 1 | 0.2949 | 530.4651 | 31.9980 | 22.0228 |
| 2.1108 | 0.3 | 3000 | 2.1269 | 0.5051 | 1 | 0.2809 | 524.9530 | 31.9981 | 22.2071 |
| 2.1045 | 0.35 | 3500 | 2.1130 | 0.5079 | 1 | 0.2735 | 523.0844 | 31.9982 | 22.3519 |
| 2.0944 | 0.4 | 4000 | 2.0996 | 0.5089 | 1 | 0.2655 | 519.8852 | 31.9983 | 22.3930 |
| 2.1314 | 0.45 | 4500 | 2.0860 | 0.5115 | 1 | 0.2567 | 517.0385 | 31.9983 | 22.4720 |
| 2.0685 | 1.02 | 5000 | 2.0770 | 0.5131 | 1 | 0.2497 | 514.3712 | 31.9984 | 22.4943 |
| 2.0496 | 1.07 | 5500 | 2.0730 | 0.5137 | 1 | 0.2381 | 513.7823 | 31.9985 | 22.5625 |
| 2.1002 | 1.12 | 6000 | 2.0667 | 0.5144 | 1 | 0.2305 | 510.7876 | 31.9986 | 22.5882 |
| 2.0723 | 1.17 | 6500 | 2.0632 | 0.5148 | 1 | 0.2206 | 510.5624 | 31.9986 | 22.6133 |
| 2.023 | 1.22 | 7000 | 2.0574 | 0.5157 | 1 | 0.2110 | 509.9878 | 31.9987 | 22.6544 |
| 2.0791 | 1.27 | 7500 | 2.0513 | 0.5168 | 1 | 0.2033 | 507.1514 | 31.9987 | 22.7018 |
| 2.0252 | 1.32 | 8000 | 2.0463 | 0.5173 | 1 | 0.1953 | 505.2723 | 31.9988 | 22.7108 |
| 2.0432 | 1.37 | 8500 | 2.0423 | 0.5183 | 1 | 0.1875 | 502.9395 | 31.9988 | 22.7562 |
| 2.0549 | 1.42 | 9000 | 2.0394 | 0.5188 | 1 | 0.1797 | 502.9016 | 31.9988 | 22.7722 |
| 2.0087 | 1.47 | 9500 | 2.0365 | 0.5193 | 1 | 0.1704 | 504.0088 | 31.9989 | 22.7990 |
| 2.0569 | 2.04 | 10000 | 2.0353 | 0.5194 | 1 | 0.1640 | 501.8128 | 31.9989 | 22.8009 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"tags": ["generated_from_trainer"], "datasets": ["roneneldan/TinyStories"], "metrics": ["accuracy"], "base_model": "roneneldan/TinyStories-1Layer-21M", "model-index": [{"name": "tinystories_1layer_attn_mlp_C25k_k16_mse_weighted", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "roneneldan/TinyStories", "type": "roneneldan/TinyStories"}, "metrics": [{"type": "accuracy", "value": 0.5193506309245984, "name": "Accuracy"}]}]}]} | null | empty-michael/tinystories_1layer_attn_mlp_C25k_k16_mse_weighted | [
"transformers",
"safetensors",
"codebook",
"generated_from_trainer",
"dataset:roneneldan/TinyStories",
"base_model:roneneldan/TinyStories-1Layer-21M",
"model-index",
"endpoints_compatible",
"region:us"
] | 2024-02-11T07:54:00+00:00 | [] | [] | TAGS
#transformers #safetensors #codebook #generated_from_trainer #dataset-roneneldan/TinyStories #base_model-roneneldan/TinyStories-1Layer-21M #model-index #endpoints_compatible #region-us
| tinystories\_1layer\_attn\_mlp\_C25k\_k16\_mse\_weighted
========================================================
This model is a fine-tuned version of roneneldan/TinyStories-1Layer-21M on the roneneldan/TinyStories dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0353
* Accuracy: 0.5194
* Multicode K: 1
* Dead Code Fraction/layer0: 0.1640
* Mse/layer0: 501.8128
* Input Norm/layer0: 31.9989
* Output Norm/layer0: 22.8009
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.005
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 6
* total\_train\_batch\_size: 96
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant\_with\_warmup
* lr\_scheduler\_warmup\_ratio: 0.05
* training\_steps: 10000
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.005\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 6\n* total\\_train\\_batch\\_size: 96\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\\_with\\_warmup\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* training\\_steps: 10000",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #safetensors #codebook #generated_from_trainer #dataset-roneneldan/TinyStories #base_model-roneneldan/TinyStories-1Layer-21M #model-index #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.005\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 6\n* total\\_train\\_batch\\_size: 96\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\\_with\\_warmup\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* training\\_steps: 10000",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
68,
150,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #codebook #generated_from_trainer #dataset-roneneldan/TinyStories #base_model-roneneldan/TinyStories-1Layer-21M #model-index #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.005\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 6\n* total\\_train\\_batch\\_size: 96\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\\_with\\_warmup\n* lr\\_scheduler\\_warmup\\_ratio: 0.05\n* training\\_steps: 10000### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.15339472889900208,
0.08991921693086624,
-0.0009632192668505013,
0.08212346583604813,
0.13430383801460266,
0.016007807105779648,
0.09814465045928955,
0.13797643780708313,
-0.11495272070169449,
0.07715222239494324,
0.12781472504138947,
0.09633030742406845,
0.040235862135887146,
0.1699984073638916,
-0.022247357293963432,
-0.28618183732032776,
-0.003860683413222432,
0.011088963598012924,
-0.17146305739879608,
0.13132476806640625,
0.10233590006828308,
-0.1291310340166092,
0.05927169695496559,
0.006248414050787687,
-0.15588076412677765,
-0.02230839803814888,
-0.013774813152849674,
-0.04070030897855759,
0.1232110857963562,
0.0091712586581707,
0.11445619910955429,
0.020419692620635033,
0.11036526411771774,
-0.20485374331474304,
0.005313780624419451,
0.0763762816786766,
0.04386530816555023,
0.09043461084365845,
0.06320080161094666,
-0.025321194902062416,
0.11733138561248779,
-0.0971016213297844,
0.07069364935159683,
0.04636581987142563,
-0.12529060244560242,
-0.27880752086639404,
-0.09836661070585251,
0.07832949608564377,
0.13174235820770264,
0.07329618185758591,
-0.02594129741191864,
0.11465885490179062,
-0.06281234323978424,
0.09618502855300903,
0.23836733400821686,
-0.25812751054763794,
-0.1065245196223259,
0.05894634127616882,
0.08306045830249786,
0.04084596410393715,
-0.12362737208604813,
-0.015972040593624115,
0.061143070459365845,
0.020697742700576782,
0.11320262402296066,
0.009626410901546478,
0.01353297010064125,
0.013417888432741165,
-0.1325666606426239,
-0.03551170602440834,
0.103788360953331,
0.07842174917459488,
-0.049107037484645844,
-0.09051522612571716,
-0.034160416573286057,
-0.2355700582265854,
-0.037600547075271606,
-0.001996194012463093,
0.03263898193836212,
-0.06113798916339874,
-0.14734062552452087,
0.028938181698322296,
-0.07918144017457962,
-0.11149296909570694,
0.04666836932301521,
0.16415522992610931,
0.037444569170475006,
-0.020827101543545723,
-0.00848030112683773,
0.13711786270141602,
0.03775310888886452,
-0.1593903750181198,
-0.011039176024496555,
0.015742212533950806,
-0.06922740489244461,
-0.03781117498874664,
-0.04449135437607765,
0.02499660849571228,
0.0009115207940340042,
0.15459029376506805,
-0.05910545215010643,
0.04530787467956543,
0.06423944979906082,
0.015651928260922432,
-0.10938549786806107,
0.1671924889087677,
-0.07648210227489471,
-0.07864914834499359,
-0.04745885729789734,
0.12868931889533997,
-0.0010446995729580522,
-0.00016910418344195932,
-0.05857810005545616,
0.02259257808327675,
0.10594919323921204,
0.05344676226377487,
-0.03304670378565788,
0.04115559160709381,
-0.04739909991621971,
-0.002204804215580225,
0.027700042352080345,
-0.07834083586931229,
0.028885774314403534,
0.004248463548719883,
-0.09978785365819931,
-0.07117632031440735,
-0.007985541597008705,
0.022140271961688995,
0.03116203472018242,
0.13433320820331573,
-0.10566822439432144,
-0.0227739866822958,
-0.1122739389538765,
-0.10610019415616989,
0.0035768591333180666,
-0.0748709961771965,
0.009464646689593792,
-0.056712958961725235,
-0.14009930193424225,
-0.05119109898805618,
0.05338577926158905,
-0.044917576014995575,
-0.05601796507835388,
-0.05512367933988571,
-0.12367893755435944,
0.028525041416287422,
0.003983249422162771,
0.16900596022605896,
-0.04528829827904701,
0.12315421551465988,
0.052357446402311325,
0.06766671687364578,
0.06280568242073059,
0.027913719415664673,
-0.0717259868979454,
0.06259603053331375,
-0.1681496948003769,
0.04236150160431862,
-0.06921140104532242,
0.09167081862688065,
-0.12272080779075623,
-0.12067101895809174,
-0.004970210138708353,
0.006776273716241121,
0.09846880286931992,
0.13640165328979492,
-0.18399843573570251,
-0.07526601105928421,
0.19474878907203674,
-0.07217820733785629,
-0.1438465118408203,
0.09623488038778305,
-0.030407151207327843,
0.040797870606184006,
0.03711822256445885,
0.12755440175533295,
0.08169279247522354,
-0.059170112013816833,
-0.017336364835500717,
-0.04204274341464043,
0.1163349449634552,
0.006413817871361971,
0.0933120921254158,
-0.015594050288200378,
0.038701970130205154,
-0.0033998710568994284,
-0.05300347879528999,
0.020677458494901657,
-0.12162106484174728,
-0.08760775625705719,
-0.026730719953775406,
-0.11616598069667816,
0.0515950582921505,
0.07263194769620895,
0.05503271520137787,
-0.11735373735427856,
-0.12796048820018768,
0.021965624764561653,
0.11745256185531616,
-0.07931577414274216,
0.007529981434345245,
-0.06712250411510468,
0.03597692400217056,
-0.03600979596376419,
-0.027017736807465553,
-0.15174220502376556,
-0.05311901867389679,
0.020680701360106468,
-0.013557471334934235,
-0.037440795451402664,
-0.032865770161151886,
0.09900454431772232,
0.07515113055706024,
-0.08157306164503098,
-0.06570117920637131,
-0.08057211339473724,
-0.00936240702867508,
-0.10561231523752213,
-0.23407651484012604,
-0.09909286350011826,
-0.028896475210785866,
0.1803467720746994,
-0.2693091332912445,
0.04491766542196274,
0.0081348717212677,
0.11881926655769348,
0.053388457745313644,
-0.05462740361690521,
-0.016498465090990067,
0.06053750216960907,
-0.030150407925248146,
-0.0883045569062233,
0.032389312982559204,
-0.01063595525920391,
-0.1194341629743576,
-0.04155580699443817,
-0.10376609116792679,
0.11893502622842789,
0.10468905419111252,
0.016748633235692978,
-0.13148078322410583,
-0.02003183774650097,
-0.09381130337715149,
-0.04219292476773262,
-0.020198944956064224,
-0.00433809170499444,
0.08469657599925995,
0.035220976918935776,
0.11459581553936005,
-0.07690704613924026,
-0.07883270829916,
0.03596893325448036,
-0.008679646998643875,
0.010587748140096664,
0.14358696341514587,
0.05020216107368469,
-0.046199899166822433,
0.12551695108413696,
0.10224002599716187,
-0.05705662816762924,
0.13827872276306152,
-0.06626547873020172,
-0.08958660066127777,
-0.02388560026884079,
0.02441415563225746,
0.04769907891750336,
0.15267203748226166,
-0.0937444195151329,
-0.01913793385028839,
0.00832806434482336,
0.006507976911962032,
0.013256112113595009,
-0.20426909625530243,
-0.040991347283124924,
0.045813534408807755,
-0.03738260269165039,
-0.03762316331267357,
-0.026569608598947525,
-0.021606341004371643,
0.08811359852552414,
0.019977673888206482,
-0.021632321178913116,
-0.0014875867636874318,
-0.003626525169238448,
-0.07041449099779129,
0.22745029628276825,
-0.06333649903535843,
-0.07575266808271408,
-0.12667427957057953,
0.04667094349861145,
-0.017813073471188545,
0.002782388124614954,
0.023848330602049828,
-0.11519540101289749,
0.001487688277848065,
-0.07981464266777039,
0.025264626368880272,
-0.022773170843720436,
0.0314364992082119,
-0.005627784878015518,
0.030874410644173622,
0.0700392946600914,
-0.11902016401290894,
0.032448992133140564,
-0.02154511585831642,
-0.06805162876844406,
0.027881154790520668,
0.02274971269071102,
0.11250507086515427,
0.15161024034023285,
0.012665756046772003,
0.01692495495080948,
-0.03828165680170059,
0.19135728478431702,
-0.11502568423748016,
-0.00875416211783886,
0.11442265659570694,
0.021176517009735107,
0.03954073414206505,
0.1299484372138977,
0.05641893297433853,
-0.09822879731655121,
0.03934057429432869,
0.049900203943252563,
-0.01810978353023529,
-0.20732402801513672,
-0.00045244963257573545,
-0.03439519926905632,
0.014638164080679417,
0.10306695103645325,
0.016529394313693047,
0.006718717515468597,
0.0707307904958725,
-0.02212502993643284,
0.002349523361772299,
-0.035150203853845596,
0.08210477232933044,
-0.022975191473960876,
0.05297553539276123,
0.12983162701129913,
-0.029483618214726448,
-0.033212944865226746,
0.013358138501644135,
-0.008872311562299728,
0.23675568401813507,
-0.03380298614501953,
0.13880838453769684,
0.05599677562713623,
0.15838740766048431,
-0.012364936992526054,
0.09905945509672165,
0.0050955465994775295,
-0.057483140379190445,
0.01868731528520584,
-0.05469686910510063,
-0.021998383104801178,
0.04171958565711975,
-0.014098790474236012,
0.08979521691799164,
-0.1406000256538391,
0.02264062687754631,
0.05183183401823044,
0.31632763147354126,
0.09920214116573334,
-0.33336395025253296,
-0.128712996840477,
0.008587433956563473,
-0.051371388137340546,
-0.041193973273038864,
0.004800915252417326,
0.1439770609140396,
-0.100239597260952,
0.03641724959015846,
-0.08590281009674072,
0.079796701669693,
-0.026779279112815857,
0.0021062272135168314,
0.08802364766597748,
0.07182154804468155,
-0.02234402485191822,
0.06074158474802971,
-0.23143504559993744,
0.32643213868141174,
-0.0031592862214893103,
0.10447713732719421,
-0.04784008115530014,
0.017070043832063675,
0.024811727926135063,
0.012763502076268196,
0.08773570507764816,
-0.012826701626181602,
-0.05374351516366005,
-0.2087976038455963,
-0.05684389919042587,
0.024379746988415718,
0.14952021837234497,
-0.12857051193714142,
0.14571037888526917,
-0.02138660103082657,
-0.01789451204240322,
0.06444413959980011,
-0.05163352191448212,
-0.0810876190662384,
-0.07206708937883377,
0.006968638394027948,
-0.03906073793768883,
0.04560086876153946,
-0.12714587152004242,
-0.11287805438041687,
-0.03134592995047569,
0.15255635976791382,
-0.08510298281908035,
-0.02899283356964588,
-0.13455204665660858,
0.09085555374622345,
0.15808559954166412,
-0.06644390523433685,
0.06017174944281578,
0.0172736719250679,
0.11516199260950089,
0.025304242968559265,
0.018382161855697632,
0.10836195200681686,
-0.08987192809581757,
-0.253560870885849,
-0.06381815671920776,
0.15760499238967896,
0.048482950776815414,
0.056377965956926346,
-0.026598406955599785,
0.03765464574098587,
-0.007853164337575436,
-0.08283054828643799,
0.0487864688038826,
-0.034771986305713654,
0.060485340654850006,
0.008079096674919128,
-0.030054204165935516,
0.07047510147094727,
-0.05339223891496658,
-0.05558958277106285,
0.10244306176900864,
0.3198263347148895,
-0.10500287264585495,
-0.029517201706767082,
0.04366598278284073,
-0.022617464885115623,
-0.14606547355651855,
0.07514612376689911,
0.1157805323600769,
0.029615066945552826,
0.01514627505093813,
-0.1804713010787964,
0.08789702504873276,
0.08951110392808914,
-0.027430735528469086,
0.12110710889101028,
-0.31368327140808105,
-0.1334642767906189,
0.06514885276556015,
0.12830780446529388,
-0.033500127494335175,
-0.17427408695220947,
-0.05392834171652794,
-0.008915766142308712,
-0.13896019756793976,
0.07133607566356659,
-0.06482220441102982,
0.10959289968013763,
-0.007649483624845743,
0.034427739679813385,
0.02526588924229145,
-0.0709942951798439,
0.13658617436885834,
-0.006115116644650698,
0.09700268507003784,
-0.010811947286128998,
-0.039075762033462524,
0.06448063254356384,
-0.06809961795806885,
-0.015536635182797909,
-0.08314855396747589,
0.04915868490934372,
-0.10565405339002609,
-0.02239316888153553,
-0.10451376438140869,
0.03253955394029617,
-0.07540231198072433,
-0.0772554874420166,
-0.0275651253759861,
0.07174781709909439,
0.03332174941897392,
-0.016642361879348755,
0.11111550033092499,
-0.018163423985242844,
0.21256640553474426,
0.0792488381266594,
0.0826559066772461,
-0.008521472103893757,
-0.026853490620851517,
0.023637626320123672,
-0.012644881382584572,
0.05125732347369194,
-0.16333113610744476,
0.012222419492900372,
0.1413702815771103,
0.07410035282373428,
0.1215306967496872,
0.07258816808462143,
-0.048453837633132935,
0.0019348679343238473,
0.08203668892383575,
-0.0987635999917984,
-0.11076540499925613,
-0.008346705697476864,
-0.020512107759714127,
-0.18376190960407257,
0.07513419538736343,
0.08449860662221909,
-0.06524224579334259,
-0.014842960052192211,
-0.016538454219698906,
0.014515683054924011,
-0.04157708212733269,
0.23862844705581665,
0.06750774383544922,
0.11102157831192017,
-0.07934597134590149,
0.07045666873455048,
0.01823309436440468,
-0.11996663361787796,
0.00019930239068344235,
0.07502277195453644,
-0.06480048596858978,
-0.007769497577100992,
0.05125139281153679,
0.08000633120536804,
-0.004966347478330135,
-0.02527078054845333,
-0.14787507057189941,
-0.11281109601259232,
0.0524032898247242,
0.15096545219421387,
0.05901110917329788,
0.03804507479071617,
-0.004880952183157206,
0.05522382631897926,
-0.14088450372219086,
0.11872578412294388,
0.08948507905006409,
0.0988345742225647,
-0.1469143182039261,
0.20455937087535858,
-0.014661397784948349,
-0.00034059022436849773,
0.005749499890953302,
0.043136171996593475,
-0.11873777955770493,
0.005735558923333883,
-0.08470376580953598,
-0.06902153044939041,
-0.04808344319462776,
-0.01618267595767975,
-0.0033065902534872293,
-0.04876784235239029,
-0.06095356121659279,
0.011787374503910542,
-0.11718010157346725,
-0.05802455171942711,
0.005293445661664009,
0.041479773819446564,
-0.1098460927605629,
0.0026520593091845512,
0.0482855848968029,
-0.10989856719970703,
0.0795823261141777,
0.01404417585581541,
0.05446021631360054,
0.020916931331157684,
-0.08008100092411041,
0.04297870025038719,
0.0042982944287359715,
-0.04279138892889023,
0.03958924487233162,
-0.1298050880432129,
-0.008960171602666378,
-0.0631682500243187,
0.04900290444493294,
0.007919734343886375,
0.036296989768743515,
-0.13711890578269958,
-0.01096887607127428,
-0.012377659790217876,
-0.04395781457424164,
-0.06167364493012428,
0.03811201825737953,
0.0757618248462677,
0.0071898517198860645,
0.1591157466173172,
-0.06139776483178139,
0.033961959183216095,
-0.2338079959154129,
-0.01542175654321909,
-0.020661333575844765,
-0.08551274985074997,
-0.07992885261774063,
-0.010132494382560253,
0.08913056552410126,
-0.0675683543086052,
0.06632517278194427,
-0.05607030913233757,
0.0741630420088768,
0.036859601736068726,
-0.10794132947921753,
0.046778373420238495,
0.050975602120161057,
0.2264328896999359,
0.038399748504161835,
-0.02844359539449215,
0.0529160276055336,
0.041690658777952194,
0.054130494594573975,
0.092880018055439,
0.2034008949995041,
0.15340423583984375,
-0.01804833486676216,
0.09992422163486481,
0.03252040967345238,
-0.11638739705085754,
-0.15156765282154083,
0.05963265523314476,
-0.033149540424346924,
0.0923367366194725,
-0.035112712532281876,
0.19091354310512543,
0.1267763078212738,
-0.20328876376152039,
0.025902394205331802,
-0.05949348956346512,
-0.08532047271728516,
-0.08127928525209427,
-0.014501789584755898,
-0.06922497600317001,
-0.16514693200588226,
0.01754084601998329,
-0.12034344673156738,
0.01708432286977768,
0.0954287126660347,
0.02088792808353901,
0.018373604863882065,
0.19248007237911224,
0.03615707904100418,
0.04620688781142235,
0.09235508739948273,
0.028486572206020355,
-0.0032911200542002916,
-0.038139160722494125,
-0.09584295749664307,
0.006548183038830757,
-0.05058646574616432,
0.0419778935611248,
-0.08325482159852982,
-0.11810990422964096,
0.05137559026479721,
0.0441209077835083,
-0.10720405727624893,
0.021400470286607742,
0.002409745939075947,
0.07494824379682541,
0.04482876881957054,
0.00889412872493267,
0.017552191391587257,
-0.03235520422458649,
0.27574747800827026,
-0.11793553084135056,
-0.06748993694782257,
-0.1406562626361847,
0.27042821049690247,
0.020570479333400726,
-0.023512963205575943,
0.019536850973963737,
-0.10959932953119278,
0.008355648256838322,
0.17880208790302277,
0.15842044353485107,
-0.024114388972520828,
-0.020340748131275177,
0.030418643727898598,
-0.019866202026605606,
-0.06240140274167061,
0.08115362375974655,
0.1008048728108406,
0.039997801184654236,
-0.083701953291893,
-0.04073162004351616,
-0.022415097802877426,
-0.07462933659553528,
-0.008116887882351875,
0.10482316464185715,
0.031216397881507874,
0.003964508883655071,
-0.045454174280166626,
0.10240349918603897,
-0.022215496748685837,
-0.15138743817806244,
0.09646319597959518,
-0.20689496397972107,
-0.178932324051857,
-0.04105285182595253,
0.052487488836050034,
0.0022783151362091303,
0.0895145982503891,
0.012857229448854923,
-0.0286068394780159,
0.06482104957103729,
0.004758426453918219,
-0.02044825069606304,
-0.14190469682216644,
0.08339375257492065,
-0.09447850286960602,
0.2380523830652237,
-0.06595432758331299,
-0.01321840938180685,
0.1487276256084442,
0.017430217936635017,
-0.10487156361341476,
0.03522251918911934,
0.10012956708669662,
-0.1020372286438942,
0.03123970702290535,
0.17663998901844025,
-0.039591655135154724,
0.10723689943552017,
0.031154228374361992,
-0.16637711226940155,
0.027605561539530754,
-0.07446365803480148,
-0.04458502680063248,
-0.09321468323469162,
-0.01508199144154787,
-0.030362986028194427,
0.14000838994979858,
0.2530459761619568,
-0.07235826551914215,
0.009065661579370499,
-0.05984238535165787,
0.025071201846003532,
0.06670401245355606,
0.09801637381315231,
-0.03316769748926163,
-0.29057955741882324,
0.030503060668706894,
0.050674814730882645,
-0.014061796478927135,
-0.24345287680625916,
-0.07520127296447754,
0.05350595712661743,
-0.06461866199970245,
-0.054678257554769516,
0.09449811279773712,
0.0972905233502388,
0.05778117850422859,
-0.046184051781892776,
-0.07808055728673935,
-0.06929885596036911,
0.19073081016540527,
-0.170563206076622,
-0.08274345099925995
] |
null | null | null | # Model Card for Mixtral-8x7B
The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.
For full details of this model please read our [release blog post](https://mistral.ai/news/mixtral-of-experts/).
## Warning
This repo contains weights that are compatible with [vLLM](https://github.com/vllm-project/vllm) serving of the model as well as Hugging Face [transformers](https://github.com/huggingface/transformers) library. It is based on the original Mixtral [torrent release](magnet:?xt=urn:btih:5546272da9065eddeb6fcd7ffddeef5b75be79a7&dn=mixtral-8x7b-32kseqlen&tr=udp%3A%2F%http://2Fopentracker.i2p.rocks%3A6969%2Fannounce&tr=http%3A%2F%http://2Ftracker.openbittorrent.com%3A80%2Fannounce), but the file format and parameter names are different. Please note that model cannot (yet) be instantiated with HF.
## Run the model
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "mistralai/Mixtral-8x7B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
text = "Hello my name is"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
By default, transformers will load the model in full precision. Therefore you might be interested to further reduce down the memory requirements to run the model through the optimizations we offer in HF ecosystem:
### In half-precision
Note `float16` precision only works on GPU devices
<details>
<summary> Click to expand </summary>
```diff
+ import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "mistralai/Mixtral-8x7B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
+ model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16).to(0)
text = "Hello my name is"
+ inputs = tokenizer(text, return_tensors="pt").to(0)
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
</details>
### Lower precision using (8-bit & 4-bit) using `bitsandbytes`
<details>
<summary> Click to expand </summary>
```diff
+ import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "mistralai/Mixtral-8x7B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
+ model = AutoModelForCausalLM.from_pretrained(model_id, load_in_4bit=True)
text = "Hello my name is"
+ inputs = tokenizer(text, return_tensors="pt").to(0)
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
</details>
### Load the model with Flash Attention 2
<details>
<summary> Click to expand </summary>
```diff
+ import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "mistralai/Mixtral-8x7B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
+ model = AutoModelForCausalLM.from_pretrained(model_id, use_flash_attention_2=True)
text = "Hello my name is"
+ inputs = tokenizer(text, return_tensors="pt").to(0)
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
</details>
## Notice
Mixtral-8x7B is a pretrained base model and therefore does not have any moderation mechanisms.
# The Mistral AI Team
Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Louis Ternon, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed. | {"language": ["fr", "it", "de", "es", "en"], "license": "apache-2.0", "tags": ["moe"]} | null | casualjim/mixtral-8x7B-v0.1-awq-gguf | [
"gguf",
"moe",
"fr",
"it",
"de",
"es",
"en",
"license:apache-2.0",
"region:us"
] | 2024-02-11T07:58:39+00:00 | [] | [
"fr",
"it",
"de",
"es",
"en"
] | TAGS
#gguf #moe #fr #it #de #es #en #license-apache-2.0 #region-us
| # Model Card for Mixtral-8x7B
The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.
For full details of this model please read our release blog post.
## Warning
This repo contains weights that are compatible with vLLM serving of the model as well as Hugging Face transformers library. It is based on the original Mixtral torrent release, but the file format and parameter names are different. Please note that model cannot (yet) be instantiated with HF.
## Run the model
By default, transformers will load the model in full precision. Therefore you might be interested to further reduce down the memory requirements to run the model through the optimizations we offer in HF ecosystem:
### In half-precision
Note 'float16' precision only works on GPU devices
<details>
<summary> Click to expand </summary>
</details>
### Lower precision using (8-bit & 4-bit) using 'bitsandbytes'
<details>
<summary> Click to expand </summary>
</details>
### Load the model with Flash Attention 2
<details>
<summary> Click to expand </summary>
</details>
## Notice
Mixtral-8x7B is a pretrained base model and therefore does not have any moderation mechanisms.
# The Mistral AI Team
Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Louis Ternon, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed. | [
"# Model Card for Mixtral-8x7B\nThe Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.\n\nFor full details of this model please read our release blog post.",
"## Warning\nThis repo contains weights that are compatible with vLLM serving of the model as well as Hugging Face transformers library. It is based on the original Mixtral torrent release, but the file format and parameter names are different. Please note that model cannot (yet) be instantiated with HF.",
"## Run the model\n\n\n\n\nBy default, transformers will load the model in full precision. Therefore you might be interested to further reduce down the memory requirements to run the model through the optimizations we offer in HF ecosystem:",
"### In half-precision\n\nNote 'float16' precision only works on GPU devices\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>",
"### Lower precision using (8-bit & 4-bit) using 'bitsandbytes'\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>",
"### Load the model with Flash Attention 2\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>",
"## Notice\nMixtral-8x7B is a pretrained base model and therefore does not have any moderation mechanisms.",
"# The Mistral AI Team\nAlbert Jiang, Alexandre Sablayrolles, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Louis Ternon, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed."
] | [
"TAGS\n#gguf #moe #fr #it #de #es #en #license-apache-2.0 #region-us \n",
"# Model Card for Mixtral-8x7B\nThe Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.\n\nFor full details of this model please read our release blog post.",
"## Warning\nThis repo contains weights that are compatible with vLLM serving of the model as well as Hugging Face transformers library. It is based on the original Mixtral torrent release, but the file format and parameter names are different. Please note that model cannot (yet) be instantiated with HF.",
"## Run the model\n\n\n\n\nBy default, transformers will load the model in full precision. Therefore you might be interested to further reduce down the memory requirements to run the model through the optimizations we offer in HF ecosystem:",
"### In half-precision\n\nNote 'float16' precision only works on GPU devices\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>",
"### Lower precision using (8-bit & 4-bit) using 'bitsandbytes'\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>",
"### Load the model with Flash Attention 2\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>",
"## Notice\nMixtral-8x7B is a pretrained base model and therefore does not have any moderation mechanisms.",
"# The Mistral AI Team\nAlbert Jiang, Alexandre Sablayrolles, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Louis Ternon, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed."
] | [
30,
76,
69,
46,
41,
42,
31,
27,
125
] | [
"passage: TAGS\n#gguf #moe #fr #it #de #es #en #license-apache-2.0 #region-us \n# Model Card for Mixtral-8x7B\nThe Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.\n\nFor full details of this model please read our release blog post.## Warning\nThis repo contains weights that are compatible with vLLM serving of the model as well as Hugging Face transformers library. It is based on the original Mixtral torrent release, but the file format and parameter names are different. Please note that model cannot (yet) be instantiated with HF.## Run the model\n\n\n\n\nBy default, transformers will load the model in full precision. Therefore you might be interested to further reduce down the memory requirements to run the model through the optimizations we offer in HF ecosystem:### In half-precision\n\nNote 'float16' precision only works on GPU devices\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>### Lower precision using (8-bit & 4-bit) using 'bitsandbytes'\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>### Load the model with Flash Attention 2\n\n<details>\n<summary> Click to expand </summary>\n\n\n</details>## Notice\nMixtral-8x7B is a pretrained base model and therefore does not have any moderation mechanisms.# The Mistral AI Team\nAlbert Jiang, Alexandre Sablayrolles, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Louis Ternon, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed."
] | [
-0.053205665200948715,
0.09699436277151108,
-0.0032410956919193268,
0.10824763774871826,
0.07167351245880127,
0.009042196907103062,
0.020660508424043655,
0.08300064504146576,
0.05609273165464401,
0.09466198086738586,
-0.023217862471938133,
-0.03151916712522507,
0.05340719223022461,
0.1007184162735939,
0.036369115114212036,
-0.18032291531562805,
0.056164681911468506,
-0.03669347986578941,
-0.10270105302333832,
0.02068588137626648,
0.10500773787498474,
-0.08646776527166367,
0.10779213160276413,
0.015724990516901016,
-0.03750361502170563,
0.028277931734919548,
-0.04263928160071373,
0.013048051856458187,
0.05120724439620972,
0.13032746315002441,
-0.024887455627322197,
0.016909891739487648,
0.04244774580001831,
-0.15066096186637878,
0.028529981151223183,
0.06874149292707443,
-0.03244243189692497,
0.040544334799051285,
0.07047324627637863,
0.036824781447649,
0.15072330832481384,
-0.10102489590644836,
0.04044545441865921,
0.03535020723938942,
-0.0593096949160099,
-0.09475182741880417,
-0.11730105429887772,
0.09335265308618546,
0.05580935999751091,
0.026423323899507523,
-0.006464811507612467,
0.07164104282855988,
-0.039442725479602814,
0.012580420821905136,
0.12374874949455261,
-0.1805085837841034,
-0.06076369062066078,
-0.01792001537978649,
0.08750774711370468,
0.04759789630770683,
-0.09866486489772797,
0.03832496702671051,
0.06301593780517578,
0.00299224816262722,
0.07560621947050095,
-0.0380229689180851,
0.09762363135814667,
-0.05202725902199745,
-0.09133073687553406,
-0.02354639768600464,
0.1320461481809616,
0.03869650140404701,
-0.06700611114501953,
-0.09242551773786545,
-0.05803583934903145,
0.007741724140942097,
-0.03603053092956543,
-0.02428453415632248,
0.03960902988910675,
0.008244580589234829,
0.08858846127986908,
-0.07997781783342361,
-0.08121588826179504,
-0.015011453069746494,
-0.05120353028178215,
0.20989416539669037,
0.036476992070674896,
0.01002742350101471,
0.03328155726194382,
0.037915248423814774,
-0.07603076100349426,
-0.07680763304233551,
-0.06966716051101685,
-0.04852587729692459,
-0.12573568522930145,
-0.007841580547392368,
-0.04475252330303192,
-0.014480991289019585,
0.049296703189611435,
0.253116250038147,
-0.06519754976034164,
0.060976024717092514,
0.0537814199924469,
-0.03612221032381058,
0.06973470002412796,
0.06509386003017426,
-0.09046325832605362,
-0.11590451747179031,
0.057373519986867905,
-0.023691410198807716,
0.05552747845649719,
-0.03826424852013588,
-0.03671679645776749,
-0.04201138764619827,
-0.03812431916594505,
0.000664853781927377,
0.048434942960739136,
0.004310910124331713,
-0.058205295354127884,
-0.08110268414020538,
0.23104146122932434,
-0.0959308072924614,
0.08300980180501938,
0.03183571249246597,
0.006008489057421684,
0.05170024186372757,
0.011636494658887386,
-0.03311808034777641,
-0.05406321957707405,
0.07400225102901459,
-0.0948924794793129,
-0.03755867853760719,
-0.037599582225084305,
-0.05465812608599663,
0.04212930053472519,
0.002453447552397847,
0.0027416155207902193,
-0.10053341090679169,
-0.024631552398204803,
-0.055486034601926804,
0.04508192092180252,
-0.06918705254793167,
-0.06479910016059875,
0.05868590995669365,
0.008983357809484005,
0.018900632858276367,
0.04257701337337494,
0.05492563545703888,
-0.034503448754549026,
0.014857927337288857,
-0.04017152637243271,
0.07950664311647415,
-0.08524180948734283,
0.03229731693863869,
-0.006313529796898365,
0.048918403685092926,
-0.13117076456546783,
0.08036526292562485,
-0.09250440448522568,
0.025660812854766846,
-0.09916815161705017,
-0.039014168083667755,
-0.02730504423379898,
0.006192085333168507,
0.04768417403101921,
0.09920543432235718,
-0.044200655072927475,
-0.03956226259469986,
0.08946248888969421,
-0.1277969479560852,
-0.01710686646401882,
0.1686883419752121,
-0.003009828506037593,
-0.05723022669553757,
0.06822869926691055,
0.0562966912984848,
0.20427276194095612,
-0.09181101620197296,
-0.040494855493307114,
0.00752235809341073,
-0.00676086125895381,
0.029201500117778778,
0.10175716876983643,
-0.024898046627640724,
-0.03834006190299988,
0.018568722531199455,
-0.03274892270565033,
-0.03851375728845596,
-0.002164290053769946,
-0.027791747823357582,
-0.0145753538236022,
-0.04268397018313408,
0.029819441959261894,
-0.02183937467634678,
-0.02847353368997574,
-0.00824301689863205,
-0.07464846223592758,
-0.001529881963506341,
0.13914266228675842,
-0.039401520043611526,
0.056886591017246246,
-0.0613061860203743,
0.11590497940778732,
0.0016086387913674116,
-0.0003695949271786958,
-0.11593806743621826,
0.04238646849989891,
0.08339530229568481,
-0.16121932864189148,
0.058509379625320435,
0.004935062024742365,
0.06265751272439957,
0.03276519477367401,
-0.05788412317633629,
0.0382780022919178,
-0.03126998618245125,
-0.016028394922614098,
-0.02413087524473667,
-0.15088321268558502,
-0.033409979194402695,
-0.04622751846909523,
0.15107916295528412,
-0.06892390549182892,
-0.01757102459669113,
0.13747349381446838,
0.13974341750144958,
-0.022968890145421028,
-0.06065094843506813,
-0.022772155702114105,
-0.032863665372133255,
-0.006087507586926222,
-0.04182296618819237,
-0.01074968185275793,
0.05852675437927246,
-0.04954569414258003,
0.017279477789998055,
-0.0629914179444313,
-0.06910474598407745,
0.07810021936893463,
0.10091162472963333,
-0.049423132091760635,
-0.05514271557331085,
0.019105281680822372,
-0.052480217069387436,
-0.02722400240600109,
-0.08210877329111099,
0.1356794536113739,
0.027470707893371582,
0.05086638778448105,
-0.08469434082508087,
-0.03542754054069519,
0.04449452832341194,
0.02011510543525219,
-0.034107696264982224,
0.04663249850273132,
0.06277725845575333,
-0.07917200028896332,
0.023468848317861557,
0.011104322038590908,
-0.0006561951595358551,
0.11130215972661972,
-0.011837461963295937,
-0.08444584161043167,
-0.04663494601845741,
0.017277810722589493,
0.014335889369249344,
0.10433360189199448,
-0.09437296539545059,
0.04299367219209671,
0.025978153571486473,
-0.021137433126568794,
0.024585235863924026,
-0.06296373158693314,
0.07340694963932037,
0.02903810888528824,
0.014370166696608067,
0.06233995407819748,
0.002283434383571148,
-0.06298960745334625,
0.02379966340959072,
0.04443475976586342,
0.07243505120277405,
-0.014076535589993,
-0.027828775346279144,
-0.061284348368644714,
0.1419108510017395,
-0.10346698015928268,
-0.17010077834129333,
-0.16741938889026642,
0.04750276356935501,
-0.09927531331777573,
-0.005437689833343029,
0.04162735864520073,
-0.03200904279947281,
-0.12302132695913315,
-0.051434051245450974,
-0.00660377973690629,
-0.0009066322818398476,
-0.008978184312582016,
0.055240023881196976,
-0.04619116336107254,
0.033326879143714905,
-0.12112797796726227,
-0.008209516294300556,
0.02837134525179863,
-0.04026705026626587,
-0.015475137159228325,
0.0035991037730127573,
0.08148889988660812,
0.06402785331010818,
-0.011465177871286869,
-0.017333686351776123,
0.038687534630298615,
0.2151208221912384,
-0.05979038402438164,
0.09558932483196259,
0.13248376548290253,
0.009562392719089985,
0.0826725885272026,
0.11006740480661392,
0.029053445905447006,
-0.0576351173222065,
0.021425548940896988,
0.02742394059896469,
-0.024525322020053864,
-0.17269253730773926,
-0.08233144134283066,
-0.057364095002412796,
-0.08548635244369507,
0.10081994533538818,
0.048199620097875595,
0.00385119765996933,
0.07305627316236496,
-0.08353172987699509,
0.07482431828975677,
0.03416453301906586,
0.06145738437771797,
0.14385293424129486,
0.01798146404325962,
0.01863834634423256,
-0.06412333995103836,
-0.009110741317272186,
0.1770927608013153,
-0.013702096417546272,
0.12414956092834473,
-0.009518764913082123,
0.23321856558322906,
0.02817816473543644,
0.04441939294338226,
-0.00376632041297853,
0.07341805845499039,
-0.04412323608994484,
0.026231329888105392,
-0.040027886629104614,
-0.05867209658026695,
0.0006392750074155629,
0.0537986122071743,
0.07550252228975296,
-0.02230236679315567,
-0.03601747006177902,
-0.00419361749663949,
0.050632935017347336,
0.16249778866767883,
-0.023131638765335083,
-0.08888042718172073,
-0.06089326739311218,
0.021539026871323586,
-0.03810219466686249,
-0.06984434276819229,
0.0035484828986227512,
0.11031126976013184,
-0.07795480638742447,
0.07175293564796448,
0.009539935737848282,
0.07000603526830673,
-0.04284311458468437,
-0.028872476890683174,
0.007969269528985023,
0.12357288599014282,
0.0035184433218091726,
0.044789478182792664,
-0.08442825824022293,
0.011358587071299553,
0.0033856574445962906,
0.07263123244047165,
-0.03404664620757103,
0.05850372835993767,
0.06559557467699051,
0.09713494777679443,
0.08943315595388412,
0.04459800571203232,
-0.12302190810441971,
-0.013376263901591301,
-0.0946984514594078,
-0.003563350299373269,
0.03488559275865555,
-0.08644670993089676,
0.05117614567279816,
-0.06853599846363068,
-0.04025401175022125,
-0.05573940649628639,
0.014310971833765507,
-0.060402337461709976,
-0.19271567463874817,
0.06563323736190796,
-0.10014549642801285,
0.012055352330207825,
-0.08073855936527252,
-0.04904840886592865,
-0.03854763135313988,
0.09846463799476624,
-0.05008130520582199,
-0.06952013075351715,
-0.14570914208889008,
-0.03539320454001427,
0.13747403025627136,
-0.0950448215007782,
0.1079743430018425,
-0.020746514201164246,
0.13050445914268494,
-0.04727764427661896,
-0.05297210067510605,
0.00940573588013649,
-0.05057484284043312,
-0.13504961133003235,
-0.004627534653991461,
0.12653233110904694,
0.03831852227449417,
0.029776200652122498,
0.02992206998169422,
0.017681466415524483,
-0.02269662357866764,
-0.14295907318592072,
-0.06604546308517456,
0.03980220854282379,
-0.0085514597594738,
0.04291065037250519,
-0.007359293755143881,
-0.08893751353025436,
-0.013764647766947746,
-0.039248667657375336,
-0.021243512630462646,
0.22309598326683044,
-0.06799118220806122,
0.1081293448805809,
0.19067463278770447,
-0.05400455743074417,
-0.21109366416931152,
-0.08460839092731476,
0.0149191003292799,
-0.020755531266331673,
0.006869468372315168,
-0.13893087208271027,
0.07416423410177231,
0.045422524213790894,
0.007938645780086517,
0.039078403264284134,
-0.20378482341766357,
-0.1071784719824791,
-0.006535111460834742,
0.06588325649499893,
0.044061921536922455,
-0.09119480103254318,
-0.04709519445896149,
-0.09032320976257324,
-0.140106663107872,
0.10367324948310852,
-0.032577209174633026,
0.052533891052007675,
-0.005800133571028709,
-0.06598667800426483,
0.016204476356506348,
-0.010771269910037518,
0.20716838538646698,
-0.024950943887233734,
0.04510236158967018,
-0.03358970209956169,
-0.003469207789748907,
0.042805254459381104,
-0.03299015760421753,
0.06645569205284119,
-0.041810642927885056,
0.018501579761505127,
-0.06164748966693878,
-0.05713491886854172,
-0.03307688608765602,
0.0560542568564415,
-0.07636713236570358,
-0.009186160750687122,
-0.10622788965702057,
0.06350574642419815,
0.06839393824338913,
-0.008598234504461288,
-0.05008595809340477,
0.0005680651520378888,
-0.07185608148574829,
0.1598639339208603,
0.11014424264431,
-0.019572369754314423,
-0.10303544253110886,
-0.0223833080381155,
-0.03240708261728287,
0.0841953381896019,
-0.11017577350139618,
0.08699586987495422,
0.08069321513175964,
0.022662289440631866,
0.08779971301555634,
-0.022174427285790443,
-0.13272114098072052,
-0.0246039517223835,
0.09099080413579941,
-0.07770534604787827,
-0.2058427631855011,
-0.040995221585035324,
-0.0700179859995842,
-0.06634501367807388,
-0.07611886411905289,
0.110318623483181,
-0.025359731167554855,
-0.0626293271780014,
0.017752664163708687,
0.0423193983733654,
-0.015679048374295235,
0.10832983255386353,
0.0441308431327343,
0.0009073052788153291,
-0.11699430644512177,
0.1022530272603035,
0.07280179858207703,
-0.1183030977845192,
0.005658905487507582,
0.13644297420978546,
-0.07156390696763992,
-0.08510560542345047,
-0.0169094018638134,
0.03728097304701805,
-0.04340529814362526,
-0.04771341383457184,
-0.0053037432953715324,
-0.10200788080692291,
0.0004920350038446486,
0.05398121476173401,
0.05208269879221916,
0.020554479211568832,
0.024513019248843193,
0.03731367364525795,
-0.0684904232621193,
0.0771203264594078,
0.08869326859712601,
0.02059527486562729,
-0.05620921775698662,
-0.008162308484315872,
-0.0038306100759655237,
-0.000017719938114169054,
-0.0062814876437187195,
-0.011408897116780281,
-0.09919612854719162,
-0.0855117216706276,
-0.1805226057767868,
0.06974956393241882,
-0.08219082653522491,
0.02681221440434456,
0.016832400113344193,
-0.018867673352360725,
-0.028820570558309555,
0.04358826205134392,
-0.05423928052186966,
-0.0603863000869751,
-0.011562327854335308,
0.07502338290214539,
-0.10470578074455261,
-0.019522463902831078,
0.09569466859102249,
-0.08531684428453445,
0.08876316994428635,
0.015994751825928688,
0.020662009716033936,
0.024607418105006218,
-0.0005894831265322864,
-0.00869564339518547,
-0.07283195108175278,
0.04164121299982071,
-0.0034027399960905313,
-0.18777506053447723,
0.01946941763162613,
0.0011854767799377441,
0.003033705987036228,
-0.04149045795202255,
0.04618733003735542,
-0.08958956599235535,
0.0035909286234527826,
-0.05412352457642555,
-0.08252719044685364,
-0.053419675678014755,
0.01597505249083042,
0.10322864353656769,
0.045394472777843475,
0.09661898016929626,
-0.037089794874191284,
-0.007442360743880272,
-0.1178371012210846,
0.009957881644368172,
0.0005001762183383107,
-0.030713336542248726,
-0.10142804682254791,
-0.05593444034457207,
0.054065998643636703,
0.043109893798828125,
0.09700517356395721,
-0.02861044369637966,
-0.00953948125243187,
0.007873191498219967,
0.01910209469497204,
-0.08803793042898178,
0.04096105322241783,
0.1153239831328392,
-0.02280437760055065,
0.01761818490922451,
-0.04081302508711815,
-0.020861076191067696,
0.010153017938137054,
0.08054342120885849,
0.05053069069981575,
0.09701620787382126,
0.07789395749568939,
0.04219076782464981,
-0.002221109811216593,
-0.022065820172429085,
-0.05423012375831604,
0.06799989193677902,
-0.0331227071583271,
0.025567475706338882,
-0.06562776863574982,
0.008226372301578522,
0.05466707795858383,
-0.18889862298965454,
0.12034538388252258,
-0.010763765312731266,
-0.045676104724407196,
-0.04554678872227669,
-0.13420452177524567,
-0.07032028585672379,
-0.08776812255382538,
-0.022321904078125954,
-0.11008354276418686,
0.04689914360642433,
0.027493512257933617,
0.014030114747583866,
-0.030223442241549492,
0.11957599967718124,
-0.1481178253889084,
-0.06817187368869781,
0.040702272206544876,
0.043684620410203934,
-0.00902571715414524,
0.10151640325784683,
-0.014400134794414043,
0.007821263745427132,
0.030486909672617912,
0.03554796054959297,
0.06129777058959007,
0.07708526402711868,
0.01816503331065178,
0.01648428477346897,
-0.07245441526174545,
0.01100968848913908,
-0.03146139159798622,
0.008872989565134048,
0.17305110394954681,
0.025998013094067574,
-0.03275517001748085,
-0.008937316946685314,
0.13972604274749756,
-0.027466781437397003,
-0.08199982345104218,
-0.17237263917922974,
0.07418276369571686,
-0.004493188112974167,
0.012308950535953045,
0.06502891331911087,
-0.08865860104560852,
-0.017038589343428612,
0.18078073859214783,
0.006961312610656023,
-0.009799547493457794,
0.021308844909071922,
0.054266173392534256,
-0.0020445194095373154,
0.033552732318639755,
0.08484109491109848,
-0.01627473160624504,
0.14004865288734436,
-0.022304976359009743,
0.09470699727535248,
0.0022520616184920073,
-0.005228437017649412,
-0.09177307039499283,
0.09942571818828583,
-0.03944128379225731,
0.011311773210763931,
-0.045898087322711945,
0.01671776734292507,
0.04222939908504486,
-0.23869040608406067,
0.07178951054811478,
-0.04716353863477707,
-0.06993689388036728,
-0.019312696531414986,
-0.06153000146150589,
0.06267986446619034,
0.06968739628791809,
0.02571861445903778,
0.0016302979784086347,
0.21381893754005432,
0.0036748715210705996,
-0.11026524007320404,
-0.04490983858704567,
0.1306685507297516,
-0.07096171379089355,
0.22644102573394775,
0.01164458878338337,
0.04120960086584091,
0.06597474217414856,
0.0014065128052607179,
-0.14525902271270752,
-0.05414559692144394,
0.015385547652840614,
-0.10020549595355988,
0.03356156125664711,
0.11234243214130402,
-0.01056302897632122,
-0.018125763162970543,
0.025652429088950157,
0.03467953950166702,
0.01947690360248089,
0.04962693154811859,
0.05418343469500542,
-0.04542974755167961,
0.08777966350317001,
-0.1662350296974182,
0.17294113337993622,
0.1336032897233963,
-0.017719943076372147,
-0.026052039116621017,
-0.04943249374628067,
0.04717356339097023,
0.02438097633421421,
0.14923687279224396,
-0.01967909000813961,
-0.15272720158100128,
0.02504216693341732,
-0.03052339144051075,
0.09113788604736328,
-0.13581499457359314,
-0.06755626201629639,
-0.03164055943489075,
0.02292829193174839,
-0.019329240545630455,
0.1134205162525177,
0.04013156518340111,
-0.003424395341426134,
-0.021380003541707993,
-0.12854911386966705,
-0.05485546961426735,
0.06030001491308212,
-0.03710034862160683,
-0.019122254103422165
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 300STEPS_5e7rate_Meditron_7B_SFT
This model is a fine-tuned version of [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3127
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2096 | 0.1 | 50 | 1.1770 |
| 0.7177 | 0.2 | 100 | 0.6260 |
| 0.3357 | 0.29 | 150 | 0.3221 |
| 0.3191 | 0.39 | 200 | 0.3142 |
| 0.3195 | 0.49 | 250 | 0.3128 |
| 0.3195 | 0.59 | 300 | 0.3127 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.0.0+cu117
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "llama2", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "epfl-llm/meditron-7b", "model-index": [{"name": "300STEPS_5e7rate_Meditron_7B_SFT", "results": []}]} | text-generation | tsavage68/300STEPS_5e7rate_Meditron_7B_SFT_zeroshot | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"sft",
"generated_from_trainer",
"base_model:epfl-llm/meditron-7b",
"license:llama2",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T08:10:06+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #trl #sft #generated_from_trainer #base_model-epfl-llm/meditron-7b #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| 300STEPS\_5e7rate\_Meditron\_7B\_SFT
====================================
This model is a fine-tuned version of epfl-llm/meditron-7b on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3127
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-07
* train\_batch\_size: 4
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 300
### Training results
### Framework versions
* Transformers 4.37.2
* Pytorch 2.0.0+cu117
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: 100\n* training\\_steps: 300",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.0.0+cu117\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #safetensors #llama #text-generation #trl #sft #generated_from_trainer #base_model-epfl-llm/meditron-7b #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: 100\n* training\\_steps: 300",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.0.0+cu117\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
82,
145,
4,
33
] | [
"passage: TAGS\n#transformers #safetensors #llama #text-generation #trl #sft #generated_from_trainer #base_model-epfl-llm/meditron-7b #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: 100\n* training\\_steps: 300### Training results### Framework versions\n\n\n* Transformers 4.37.2\n* Pytorch 2.0.0+cu117\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.12741594016551971,
0.09850389510393143,
-0.0028650823514908552,
0.07260210067033768,
0.1247701421380043,
0.018045108765363693,
0.11013483256101608,
0.1415514498949051,
-0.07641405612230301,
0.09812198579311371,
0.14702199399471283,
0.12265659868717194,
0.04934026300907135,
0.1684885025024414,
-0.022092744708061218,
-0.31485262513160706,
-0.00910679530352354,
-0.014323091134428978,
-0.15719085931777954,
0.13538594543933868,
0.08263944834470749,
-0.11984634399414062,
0.05175004154443741,
-0.03272094577550888,
-0.1129075139760971,
-0.03328421339392662,
-0.02930998057126999,
-0.04426509886980057,
0.12283647805452347,
0.002560058142989874,
0.08845365792512894,
0.04484504461288452,
0.10454866290092468,
-0.24524831771850586,
0.011319121345877647,
0.05345930531620979,
0.0317365936934948,
0.08533984422683716,
0.06900249421596527,
-0.05279230698943138,
0.10195096582174301,
-0.09923240542411804,
0.08072471618652344,
0.033322568982839584,
-0.11949319392442703,
-0.22801852226257324,
-0.09891646355390549,
0.06353148818016052,
0.15594016015529633,
0.07938476651906967,
-0.023242710158228874,
0.06935252994298935,
-0.0855141282081604,
0.07928682118654251,
0.2681751251220703,
-0.2779768705368042,
-0.08097048103809357,
0.05075898393988609,
0.0810452252626419,
0.05019589886069298,
-0.1332215517759323,
-0.010727421380579472,
0.026660168543457985,
0.00746888667345047,
0.15760691463947296,
-0.00034494363353587687,
0.10369366407394409,
0.013274624943733215,
-0.14874553680419922,
-0.045497361570596695,
0.10092215985059738,
0.07771893590688705,
-0.030400384217500687,
-0.12181201577186584,
-0.032399702817201614,
-0.23527929186820984,
-0.0439077652990818,
-0.005426399875432253,
0.02963264472782612,
-0.04809088259935379,
-0.09806160628795624,
-0.0002258390886709094,
-0.07166595757007599,
-0.10241753607988358,
0.0627119317650795,
0.15825556218624115,
0.04257899895310402,
-0.04987605661153793,
0.03803649917244911,
0.1588330864906311,
0.08299950510263443,
-0.14965905249118805,
0.006032305303961039,
0.025465795770287514,
-0.08187591284513474,
-0.02888600528240204,
-0.013447229750454426,
0.008960481733083725,
0.010534142144024372,
0.18298175930976868,
-0.014664490707218647,
0.05074460431933403,
0.07715390622615814,
0.03789330646395683,
-0.10605835914611816,
0.1377006620168686,
-0.07282959669828415,
-0.10106036812067032,
-0.03915674239397049,
0.15146701037883759,
0.013881558552384377,
-0.011343407444655895,
-0.0778876394033432,
0.022854208946228027,
0.09532888233661652,
0.07510250061750412,
-0.023152489215135574,
0.02997162565588951,
-0.08235179632902145,
-0.00974641926586628,
0.03439261391758919,
-0.09906242787837982,
0.0373387411236763,
0.003374788211658597,
-0.06112297251820564,
-0.04775890335440636,
-0.0003196748439222574,
0.012219890020787716,
0.0020610899664461613,
0.14782120287418365,
-0.07568690180778503,
-0.024224113672971725,
-0.0935201346874237,
-0.0871717557311058,
0.012258430011570454,
-0.09829611331224442,
-0.003362600924447179,
-0.0577504001557827,
-0.14842435717582703,
-0.06172903627157211,
0.06514300405979156,
-0.06191574037075043,
-0.06512794643640518,
-0.07988356798887253,
-0.10820196568965912,
0.02964327298104763,
-0.008801396936178207,
0.15800011157989502,
-0.048335328698158264,
0.12984293699264526,
-0.007634472101926804,
0.07983318716287613,
0.0932343453168869,
0.051724765449762344,
-0.046166375279426575,
0.0690317377448082,
-0.17923934757709503,
0.06700566411018372,
-0.07089445739984512,
0.0719258114695549,
-0.12911567091941833,
-0.09693647921085358,
-0.0401885062456131,
0.003914088010787964,
0.08560533821582794,
0.15678176283836365,
-0.16030572354793549,
-0.08219955116510391,
0.19593441486358643,
-0.05298306420445442,
-0.11173152923583984,
0.11031106114387512,
-0.030504316091537476,
0.023102236911654472,
0.024466929957270622,
0.14252910017967224,
0.0897769182920456,
-0.08586375415325165,
0.018878214061260223,
-0.037109095603227615,
0.08728563785552979,
0.015691354870796204,
0.09775210171937943,
-0.03832457587122917,
0.044376190751791,
-0.008924524299800396,
-0.07384813576936722,
0.045821238309144974,
-0.09385364502668381,
-0.08114632964134216,
-0.0024891754146665335,
-0.09084803611040115,
0.06544610857963562,
0.043986596167087555,
0.02879481203854084,
-0.088516965508461,
-0.1226075142621994,
0.003212838666513562,
0.09962384402751923,
-0.0847962498664856,
0.01839989423751831,
-0.03886173292994499,
0.06070750951766968,
-0.014322553761303425,
-0.002131173387169838,
-0.14734549820423126,
-0.03205515816807747,
0.026393495500087738,
0.01427229680120945,
-0.009854482486844063,
-0.02800826169550419,
0.0821133702993393,
0.0669487863779068,
-0.07826784998178482,
-0.08994761109352112,
-0.05295321345329285,
-0.008535969071090221,
-0.10920707881450653,
-0.24383197724819183,
-0.07245943695306778,
-0.0380638986825943,
0.18023967742919922,
-0.24564743041992188,
0.04817740246653557,
0.005494129378348589,
0.12212292850017548,
0.04585590586066246,
-0.046940792351961136,
0.009894536808133125,
0.05494360625743866,
-0.026297500357031822,
-0.09462399035692215,
0.03986155241727829,
-0.0141174690797925,
-0.13048726320266724,
-0.016523411497473717,
-0.12737521529197693,
0.13290686905384064,
0.09636446088552475,
0.02313869073987007,
-0.135185107588768,
-0.09690730273723602,
-0.06662452965974808,
-0.03926524892449379,
-0.037259459495544434,
-0.0033028102479875088,
0.111782506108284,
0.0458219051361084,
0.12309655547142029,
-0.07731113582849503,
-0.0738346055150032,
0.0264907069504261,
-0.00835647527128458,
0.006783034652471542,
0.15930111706256866,
0.064702607691288,
-0.05464078485965729,
0.12362463027238846,
0.13950319588184357,
-0.04280376434326172,
0.1370640993118286,
-0.048246871680021286,
-0.0915515199303627,
-0.03700767084956169,
0.06302163004875183,
0.04252375289797783,
0.12609654664993286,
-0.08522440493106842,
-0.01132356096059084,
0.007724669761955738,
0.018002226948738098,
-0.0056838346645236015,
-0.2059142142534256,
-0.051215700805187225,
0.048386670649051666,
-0.05666917562484741,
0.02056986466050148,
-0.019815780222415924,
-0.030390452593564987,
0.0988985002040863,
0.026635922491550446,
-0.049634531140327454,
0.007211210671812296,
-0.008568433113396168,
-0.08302919566631317,
0.22282782196998596,
-0.08465231209993362,
-0.12099066376686096,
-0.11876170337200165,
0.021518738940358162,
0.0030524025205522776,
0.0049694739282131195,
0.026056911796331406,
-0.08943156152963638,
-0.0017472567269578576,
-0.0802486464381218,
0.005751187913119793,
-0.03161995857954025,
0.03045228309929371,
-0.029961146414279938,
0.022447509691119194,
0.02869960106909275,
-0.07725705951452255,
0.017443137243390083,
-0.018128912895917892,
-0.04661126807332039,
0.04681044816970825,
0.018612481653690338,
0.10920727998018265,
0.1651037186384201,
0.027919424697756767,
0.019475895911455154,
-0.04760797321796417,
0.1342950016260147,
-0.12777650356292725,
0.01876291260123253,
0.10814470797777176,
0.026478130370378494,
0.05752311646938324,
0.1418326050043106,
0.048705000430345535,
-0.09428254514932632,
0.04167582467198372,
0.039503030478954315,
-0.030045075342059135,
-0.21468444168567657,
-0.001986777875572443,
-0.04789311811327934,
0.0037252018228173256,
0.1275523602962494,
0.04031684622168541,
0.01417162362486124,
0.05949863791465759,
-0.02668728306889534,
-0.010107751935720444,
0.01574820466339588,
0.0809895321726799,
-0.0014857992064207792,
0.02260063961148262,
0.11461152881383896,
-0.013889959082007408,
-0.04807208850979805,
0.01035996712744236,
0.018050111830234528,
0.24134404957294464,
-0.014190583489835262,
0.1429888755083084,
0.050394851714372635,
0.15014983713626862,
-0.007805132307112217,
0.08178379386663437,
0.02817276492714882,
-0.04263322055339813,
-0.0010824608616530895,
-0.05445333942770958,
-0.022802378982305527,
0.05559740215539932,
0.03231463581323624,
0.056969571858644485,
-0.11885816603899002,
0.01923844777047634,
0.038890544325113297,
0.31627774238586426,
0.07921090722084045,
-0.2981487214565277,
-0.07342351973056793,
0.017629418522119522,
-0.054533157497644424,
-0.03213534504175186,
0.021041786298155785,
0.12975850701332092,
-0.11211026459932327,
0.046801552176475525,
-0.0900329053401947,
0.07271663844585419,
-0.06694323569536209,
-0.00847157184034586,
0.05499548092484474,
0.07913057506084442,
-0.029498692601919174,
0.05507289618253708,
-0.2735711336135864,
0.3126218914985657,
-0.007194052450358868,
0.0702659860253334,
-0.046235356479883194,
0.019451145082712173,
0.02744336612522602,
0.017574910074472427,
0.13091713190078735,
-0.008599585853517056,
-0.025463223457336426,
-0.18533113598823547,
-0.0971447080373764,
-0.006944060325622559,
0.14414209127426147,
-0.14024874567985535,
0.1280996948480606,
-0.024974800646305084,
-0.03504454344511032,
0.042291492223739624,
-0.07736717909574509,
-0.05851585045456886,
-0.09791846573352814,
0.011833298951387405,
-0.04567280411720276,
0.06766756623983383,
-0.10992835462093353,
-0.09966129809617996,
-0.04179602861404419,
0.14853227138519287,
-0.1248759925365448,
-0.03139207884669304,
-0.15135975182056427,
0.0746426209807396,
0.1349850445985794,
-0.0730464830994606,
0.05222947522997856,
0.01883816346526146,
0.09555020928382874,
-0.0005233233096078038,
0.018361777067184448,
0.11873175948858261,
-0.0800296887755394,
-0.24884463846683502,
-0.07389982044696808,
0.18281005322933197,
0.03819669783115387,
0.06455840915441513,
-0.025479517877101898,
0.026421738788485527,
0.0017222316237166524,
-0.0912151113152504,
0.07669685781002045,
0.021984172984957695,
0.05965665355324745,
0.035175204277038574,
-0.05672163888812065,
0.07718106359243393,
-0.05932086706161499,
-0.06399737298488617,
0.13075199723243713,
0.3205716013908386,
-0.10304462164640427,
0.04384198784828186,
0.054973289370536804,
-0.04089431092143059,
-0.1797589510679245,
0.017191771417856216,
0.09964828938245773,
0.04367858171463013,
0.023659026250243187,
-0.19282332062721252,
0.03667255491018295,
0.09845677018165588,
-0.02513091266155243,
0.09864502400159836,
-0.3401578664779663,
-0.13050104677677155,
0.06659843027591705,
0.1271580308675766,
-0.023166777566075325,
-0.1756766438484192,
-0.06301277875900269,
-0.005158114712685347,
-0.052614714950323105,
0.04810052365064621,
-0.021495843306183815,
0.12786884605884552,
-0.0169546939432621,
-0.006622683722525835,
0.022656003013253212,
-0.06644990295171738,
0.129377543926239,
0.0027241832576692104,
0.08469202369451523,
-0.01680188812315464,
-0.011484705843031406,
0.01433976087719202,
-0.07816258072853088,
0.01683814823627472,
-0.11230281740427017,
0.02206573076546192,
-0.10673293471336365,
-0.028537580743432045,
-0.08266938477754593,
0.029392970725893974,
-0.0629163309931755,
-0.06915201991796494,
-0.02550249919295311,
0.05048326402902603,
0.0676533579826355,
-0.004817458800971508,
0.10491495579481125,
-0.034995611757040024,
0.1584337204694748,
0.08424487709999084,
0.10835842788219452,
0.002571981633082032,
-0.08372843265533447,
-0.01217639073729515,
-0.01905406266450882,
0.04223334416747093,
-0.1497015357017517,
-0.0038149787578731775,
0.1342032551765442,
0.06009463593363762,
0.14499571919441223,
0.06656719744205475,
-0.059547096490859985,
-0.007368647027760744,
0.07873056083917618,
-0.09314844757318497,
-0.11935264617204666,
-0.01152541022747755,
-0.008490431122481823,
-0.15005743503570557,
0.03535490855574608,
0.09259029477834702,
-0.05777553468942642,
-0.01134013757109642,
0.00396198034286499,
0.02710060030221939,
-0.020040804520249367,
0.21218843758106232,
0.06290268898010254,
0.10192174464464188,
-0.07943008840084076,
0.06936021894216537,
0.031169181689620018,
-0.1165156438946724,
0.015134594403207302,
0.10063063353300095,
-0.08636028319597244,
-0.02101558819413185,
0.05467942729592323,
0.06679235398769379,
0.0018938322318717837,
-0.0018627858953550458,
-0.12008114159107208,
-0.12578020989894867,
0.07233497500419617,
0.11450593173503876,
0.04291507601737976,
0.023835208266973495,
-0.023277433589100838,
0.04260920360684395,
-0.12334094941616058,
0.11576999723911285,
0.07804029434919357,
0.08637988567352295,
-0.13856220245361328,
0.15317663550376892,
-0.003149806521832943,
-0.0033396107610315084,
-0.005118206143379211,
0.031271688640117645,
-0.12269080430269241,
0.006771422922611237,
-0.036467045545578,
-0.06589683145284653,
-0.060367483645677567,
-0.022863727062940598,
-0.012239614501595497,
-0.04062582924962044,
-0.012119624763727188,
-0.0034237904474139214,
-0.10766726732254028,
-0.05819287151098251,
-0.014139068312942982,
0.04751940444111824,
-0.10124258697032928,
-0.03254622593522072,
0.03312371298670769,
-0.12175795435905457,
0.09043680131435394,
0.011232167482376099,
0.04248955845832825,
0.0024571269750595093,
-0.10318196564912796,
0.04450288414955139,
0.029680533334612846,
-0.03114723600447178,
0.02325173281133175,
-0.14131034910678864,
-0.018128499388694763,
-0.06988698244094849,
0.014766084961593151,
0.018311606720089912,
-0.003477801103144884,
-0.14431644976139069,
0.017540263012051582,
-0.051795508712530136,
-0.05902788043022156,
-0.07149294018745422,
0.05878405645489693,
0.06375385075807571,
-0.0029746065847575665,
0.15098047256469727,
-0.06839364022016525,
0.06241406872868538,
-0.22404681146144867,
-0.011757726781070232,
-0.01475842110812664,
-0.07224101573228836,
-0.0856861099600792,
-0.03008555993437767,
0.08787327259778976,
-0.05163848400115967,
0.06383806467056274,
-0.04541989788413048,
0.030911503359675407,
0.024192562326788902,
-0.09429162740707397,
0.08780107647180557,
0.05149731785058975,
0.16742867231369019,
0.0507473349571228,
-0.04380491375923157,
0.03899473324418068,
0.03664100170135498,
0.06404199451208115,
0.0564127154648304,
0.17423851788043976,
0.1366899609565735,
0.011516342870891094,
0.08749748766422272,
0.024878675118088722,
-0.12257251888513565,
-0.15130668878555298,
0.09615778177976608,
-0.02765195444226265,
0.09085787087678909,
-0.02539910562336445,
0.21446391940116882,
0.1327817589044571,
-0.2118476778268814,
0.032113272696733475,
-0.019446570426225662,
-0.08834438771009445,
-0.0889567956328392,
-0.07745968550443649,
-0.06739244610071182,
-0.16042274236679077,
0.0008732428541406989,
-0.10189256817102432,
0.019731732085347176,
0.0696137472987175,
0.024479852989315987,
0.042783256620168686,
0.15679924190044403,
0.07214702665805817,
0.02676902897655964,
0.10105504840612411,
0.037631191313266754,
0.007521997671574354,
-0.04362339898943901,
-0.09660140424966812,
0.0057919141836464405,
-0.07815412431955338,
0.03667832538485527,
-0.06674142926931381,
-0.09397725760936737,
0.05687037855386734,
0.03080284222960472,
-0.10031397640705109,
0.025179801508784294,
-0.0007485286914743483,
0.06741739064455032,
0.08365658670663834,
0.018886448815464973,
-0.020992591977119446,
-0.03367489576339722,
0.2586420476436615,
-0.10306842625141144,
-0.04234177991747856,
-0.10784175992012024,
0.24968168139457703,
0.031039506196975708,
-0.0021565048955380917,
0.010356469079852104,
-0.08104424923658371,
0.02843593619763851,
0.1778223067522049,
0.1698121577501297,
-0.041037656366825104,
-0.006013466510921717,
0.028024818748235703,
-0.014468141831457615,
-0.027330076321959496,
0.07249283790588379,
0.11306264996528625,
0.05378512665629387,
-0.07698214054107666,
-0.018462561070919037,
-0.028051286935806274,
-0.07565131038427353,
-0.043726783245801926,
0.07578924298286438,
0.05197261646389961,
0.004447197541594505,
-0.03077450767159462,
0.1155337318778038,
-0.02941960282623768,
-0.13239361345767975,
0.07930393517017365,
-0.19663400948047638,
-0.17101746797561646,
-0.05279412493109703,
0.02547675557434559,
0.012355254031717777,
0.07373787462711334,
0.012640801258385181,
-0.02674451842904091,
0.08202152699232101,
0.005229004193097353,
-0.047881998121738434,
-0.08645816147327423,
0.06319905817508698,
-0.06424005329608917,
0.19032441079616547,
-0.0538657121360302,
-0.012029753066599369,
0.13287849724292755,
0.024889180436730385,
-0.08351490646600723,
0.04376265034079552,
0.0909499004483223,
-0.08015445619821548,
0.054465051740407944,
0.16261695325374603,
-0.029426272958517075,
0.10069803893566132,
0.039415836334228516,
-0.12573958933353424,
0.030875520780682564,
-0.10293074697256088,
-0.06575413793325424,
-0.0805295780301094,
0.015141037292778492,
-0.019963795319199562,
0.14841963350772858,
0.2316417247056961,
-0.06678065657615662,
0.006391462404280901,
-0.043896544724702835,
0.009909952990710735,
0.06094213202595711,
0.10538031905889511,
-0.014200427569448948,
-0.24626684188842773,
0.01391279324889183,
0.03849618136882782,
-0.0009229384595528245,
-0.25505462288856506,
-0.10087557882070541,
0.025069531053304672,
-0.05125712975859642,
-0.0920988991856575,
0.09663048386573792,
0.05840654671192169,
0.060611337423324585,
-0.043629907071590424,
-0.10486147552728653,
-0.05021354928612709,
0.18876522779464722,
-0.177406907081604,
-0.052291691303253174
] |
null | null | transformers |
## Exllama v2 Quantizations of Hercules-2.5-Mistral-7B
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.13">turboderp's ExLlamaV2 v0.0.13</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
Original model: https://huggingface.co/Locutusque/Hercules-2.5-Mistral-7B
| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
| [8_0](https://huggingface.co/bartowski/Hercules-2.5-Mistral-7B-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| [6_5](https://huggingface.co/bartowski/Hercules-2.5-Mistral-7B-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
| [5_0](https://huggingface.co/bartowski/Hercules-2.5-Mistral-7B-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB | 9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
| [4_25](https://huggingface.co/bartowski/Hercules-2.5-Mistral-7B-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
| [3_5](https://huggingface.co/bartowski/Hercules-2.5-Mistral-7B-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
## Download instructions
With git:
```shell
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Hercules-2.5-Mistral-7B-exl2 Hercules-2.5-Mistral-7B-exl2-6_5
```
With huggingface hub (credit to TheBloke for instructions):
```shell
pip3 install huggingface-hub
```
To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Hercules-2.5-Mistral-7B-exl2`:
```shell
mkdir Hercules-2.5-Mistral-7B-exl2
huggingface-cli download bartowski/Hercules-2.5-Mistral-7B-exl2 --local-dir Hercules-2.5-Mistral-7B-exl2 --local-dir-use-symlinks False
```
To download from a different branch, add the `--revision` parameter:
Linux:
```shell
mkdir Hercules-2.5-Mistral-7B-exl2-6_5
huggingface-cli download bartowski/Hercules-2.5-Mistral-7B-exl2 --revision 6_5 --local-dir Hercules-2.5-Mistral-7B-exl2-6_5 --local-dir-use-symlinks False
```
Windows (which apparently doesn't like _ in folders sometimes?):
```shell
mkdir Hercules-2.5-Mistral-7B-exl2-6.5
huggingface-cli download bartowski/Hercules-2.5-Mistral-7B-exl2 --revision 6_5 --local-dir Hercules-2.5-Mistral-7B-exl2-6.5 --local-dir-use-symlinks False
```
Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski | {"license": "apache-2.0", "library_name": "transformers", "tags": ["not-for-all-audiences", "chemistry", "math", "code", "physics"], "datasets": ["Locutusque/hercules-v2.0", "Locutusque/hercules-v2.5"], "base_model": "mistralai/Mistral-7B-v0.1", "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | text-generation | bartowski/Hercules-2.5-Mistral-7B-exl2 | [
"transformers",
"not-for-all-audiences",
"chemistry",
"math",
"code",
"physics",
"text-generation",
"dataset:Locutusque/hercules-v2.0",
"dataset:Locutusque/hercules-v2.5",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2024-02-11T08:16:01+00:00 | [] | [] | TAGS
#transformers #not-for-all-audiences #chemistry #math #code #physics #text-generation #dataset-Locutusque/hercules-v2.0 #dataset-Locutusque/hercules-v2.5 #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #endpoints_compatible #region-us
| Exllama v2 Quantizations of Hercules-2.5-Mistral-7B
---------------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.13 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
Each branch contains an individual bits per weight, with the main one containing only the URL for further conversions.
Original model: URL
Download instructions
---------------------
With git:
With huggingface hub (credit to TheBloke for instructions):
To download the 'main' (only useful if you only care about URL) branch to a folder called 'Hercules-2.5-Mistral-7B-exl2':
To download from a different branch, add the '--revision' parameter:
Linux:
Windows (which apparently doesn't like \_ in folders sometimes?):
Want to support my work? Visit my ko-fi page here: URL
| [] | [
"TAGS\n#transformers #not-for-all-audiences #chemistry #math #code #physics #text-generation #dataset-Locutusque/hercules-v2.0 #dataset-Locutusque/hercules-v2.5 #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #endpoints_compatible #region-us \n"
] | [
95
] | [
"passage: TAGS\n#transformers #not-for-all-audiences #chemistry #math #code #physics #text-generation #dataset-Locutusque/hercules-v2.0 #dataset-Locutusque/hercules-v2.5 #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #endpoints_compatible #region-us \n"
] | [
-0.07732938230037689,
0.1512831598520279,
-0.0064833397045731544,
0.04614569991827011,
0.047237180173397064,
0.038243234157562256,
0.14181634783744812,
0.13351689279079437,
0.09784574061632156,
0.027980251237750053,
0.12878859043121338,
0.04529160261154175,
-0.020123595371842384,
0.08300136774778366,
-0.059907734394073486,
-0.19888819754123688,
0.03972103074193001,
0.035193175077438354,
-0.1410599648952484,
0.08874759078025818,
0.0811493992805481,
-0.03977905958890915,
0.08797888457775116,
-0.05838833004236221,
-0.013800629414618015,
0.02323899418115616,
0.04076868295669556,
-0.09525768458843231,
0.10696635395288467,
0.03680853545665741,
0.10557330399751663,
0.1277543604373932,
-0.053808312863111496,
-0.17531971633434296,
0.044505003839731216,
0.007931023836135864,
-0.03864777460694313,
0.09301215410232544,
-0.037191618233919144,
-0.0655236467719078,
0.07726350426673889,
-0.03319316357374191,
0.005366652272641659,
0.08971726894378662,
-0.14679792523384094,
-0.06460797786712646,
-0.08763711154460907,
-0.037111736834049225,
-0.011530459858477116,
0.04516081511974335,
0.026837488636374474,
0.0909067764878273,
-0.013520479202270508,
0.04009232670068741,
0.28398221731185913,
-0.27360156178474426,
-0.04507879912853241,
0.12329843640327454,
0.12112436443567276,
0.10509784519672394,
-0.014892950654029846,
0.08050630241632462,
0.040018241852521896,
0.0037879461888223886,
-0.003665435593575239,
-0.07086160778999329,
-0.013474809937179089,
0.052811987698078156,
-0.05969637259840965,
0.02740289643406868,
0.2756890058517456,
0.004767941776663065,
-0.010079197585582733,
0.016235211864113808,
-0.13359762728214264,
0.018852267414331436,
-0.043988510966300964,
-0.04846083000302315,
0.04974693804979324,
0.04171654209494591,
0.020570920780301094,
-0.043051306158304214,
-0.08072301745414734,
-0.0553734190762043,
-0.07534665614366531,
0.08333892375230789,
-0.0724157840013504,
0.04505600035190582,
-0.11958375573158264,
0.06924255192279816,
-0.09792353957891464,
-0.13808467984199524,
-0.043340109288692474,
-0.12339358031749725,
0.0770331621170044,
-0.0024030739441514015,
-0.014734460972249508,
-0.04088470712304115,
0.13908663392066956,
0.15364708006381989,
0.0529034323990345,
0.04741649329662323,
0.0400017686188221,
0.044093064963817596,
-0.004179495852440596,
-0.02110227756202221,
-0.00003799194018938579,
-0.15027326345443726,
0.06560979783535004,
0.044187527149915695,
0.04706468805670738,
-0.048925481736660004,
-0.03418029844760895,
-0.1299426555633545,
-0.01464111264795065,
0.07619994878768921,
0.11496230214834213,
0.01788308285176754,
-0.0699891522526741,
-0.005004979204386473,
0.1539212167263031,
-0.048709526658058167,
-0.02140597067773342,
0.017370982095599174,
-0.004972111899405718,
0.16068986058235168,
0.05154044181108475,
0.019845949485898018,
0.03514032065868378,
-0.037763211876153946,
-0.11598803848028183,
-0.030757712200284004,
-0.049195192754268646,
-0.017289185896515846,
0.07895203679800034,
0.00046135755837894976,
0.04493505880236626,
-0.09661892056465149,
-0.13044115900993347,
0.033417150378227234,
0.0890224426984787,
-0.06473620980978012,
-0.01317634992301464,
0.01032471377402544,
-0.04735095053911209,
0.05188215151429176,
-0.00823981873691082,
-0.053025342524051666,
-0.0681198388338089,
0.04325750097632408,
0.015492849051952362,
0.12010340392589569,
-0.09363877773284912,
0.023452766239643097,
-0.09664569050073624,
0.06727201491594315,
-0.2077203094959259,
0.012738046236336231,
-0.1095748022198677,
0.08915236592292786,
-0.12135287374258041,
-0.038749516010284424,
0.029529675841331482,
-0.024445926770567894,
0.0506109893321991,
0.24913184344768524,
-0.18299634754657745,
-0.059883855283260345,
0.09559563547372818,
-0.10397157073020935,
-0.23462063074111938,
0.04836437851190567,
0.011660460382699966,
0.04095766693353653,
0.06341636925935745,
0.11422858387231827,
0.04853612184524536,
-0.0636495053768158,
-0.04531143605709076,
0.07229593396186829,
0.03118913620710373,
-0.04527534544467926,
0.09724241495132446,
0.029059942811727524,
-0.03508433327078819,
0.05492829158902168,
-0.03314320743083954,
0.004561503883451223,
-0.04286836460232735,
-0.08920310437679291,
-0.07496602833271027,
-0.033146750181913376,
0.08415249735116959,
-0.007964001968502998,
0.07117699831724167,
-0.04575904831290245,
-0.0530274361371994,
0.06835485249757767,
0.0685817077755928,
-0.035565368831157684,
0.0569697767496109,
-0.04304688051342964,
0.14986512064933777,
-0.028457345440983772,
0.0237613283097744,
-0.12486818432807922,
-0.03736420348286629,
-0.018665077164769173,
-0.007456925231963396,
-0.006479489617049694,
0.02763555198907852,
0.10231005400419235,
-0.024640608578920364,
-0.0837978944182396,
0.0054891686886549,
-0.014380870386958122,
0.04893529787659645,
-0.020628442987799644,
-0.1906968057155609,
-0.005846185609698296,
-0.06263978779315948,
0.07649114727973938,
-0.1297753006219864,
0.05305910483002663,
0.07351374626159668,
0.07059400528669357,
0.023803383111953735,
0.018836764618754387,
-0.0014849453000351787,
-0.037399765104055405,
-0.04386145621538162,
-0.02186182327568531,
0.04651559889316559,
-0.02454972080886364,
-0.11409231275320053,
-0.025738032534718513,
-0.04487122595310211,
0.18833811581134796,
0.16115650534629822,
-0.13446974754333496,
0.04566748067736626,
-0.03691732883453369,
-0.0020908797159790993,
0.01814740151166916,
0.08084852248430252,
0.021137740463018417,
-0.0457039549946785,
0.019065482541918755,
0.03947459161281586,
-0.03517914563417435,
0.045218776911497116,
0.02296753041446209,
-0.0701785683631897,
-0.039383966475725174,
0.06238313764333725,
0.05655420199036598,
-0.03193759545683861,
0.11683037132024765,
0.2795186936855316,
-0.04095688834786415,
0.09150022268295288,
-0.004709630738943815,
-0.05199955776333809,
-0.010043168440461159,
-0.06867048144340515,
0.0017239105654880404,
0.05891478806734085,
-0.17822180688381195,
0.00527958245947957,
0.05298459902405739,
-0.02406555972993374,
0.04106178134679794,
-0.06352506577968597,
-0.06749090552330017,
0.0018180581973865628,
-0.014766817912459373,
-0.14649143815040588,
0.03181843459606171,
-0.059457603842020035,
0.11340948194265366,
0.005484338384121656,
-0.018748998641967773,
0.0460786446928978,
-0.006669389549642801,
-0.08861900866031647,
0.18668603897094727,
-0.09021059423685074,
-0.045934051275253296,
-0.10499744117259979,
0.010613764636218548,
-0.03835935890674591,
-0.007850917056202888,
0.04822693392634392,
-0.06176496297121048,
-0.030475541949272156,
-0.04670381546020508,
0.0934348851442337,
0.015508458018302917,
0.02516464702785015,
-0.00008579817949794233,
0.0463457889854908,
-0.006831974256783724,
-0.11664189398288727,
-0.022770274430513382,
0.008595111779868603,
-0.05499481409788132,
0.0880713015794754,
-0.11221525073051453,
0.08547166734933853,
0.11934638023376465,
0.023458870127797127,
-0.006203862372785807,
-0.017398426309227943,
0.22373352944850922,
-0.0784200057387352,
0.06792695820331573,
0.1993219256401062,
0.06995029002428055,
0.04752911999821663,
0.14000891149044037,
0.07001261413097382,
-0.05672250688076019,
0.010199496522545815,
-0.035297151654958725,
-0.07307461649179459,
-0.2764846086502075,
-0.05429026484489441,
-0.08257370442152023,
0.06659357249736786,
-0.043508779257535934,
0.021280596032738686,
0.09257595986127853,
0.09359858930110931,
0.001701389322988689,
-0.013646368868649006,
0.017307311296463013,
0.05209064856171608,
0.17984865605831146,
0.04039086773991585,
0.09071579575538635,
-0.07368221879005432,
0.020706648007035255,
0.10651890188455582,
0.10784201323986053,
0.18069663643836975,
0.055136021226644516,
0.17204278707504272,
0.03116593509912491,
0.04308636859059334,
0.08413976430892944,
0.09048011898994446,
0.0291500985622406,
-0.017512142658233643,
-0.05123128741979599,
-0.06888579577207565,
-0.031010756269097328,
0.06733129173517227,
-0.08697669953107834,
-0.0475875586271286,
-0.035863712430000305,
-0.020989926531910896,
0.09389976412057877,
0.14352771639823914,
0.038335107266902924,
-0.18047280609607697,
-0.07255341857671738,
0.14886625111103058,
0.03998613357543945,
-0.03824789077043533,
0.04375451058149338,
-0.03512278571724892,
-0.03652578964829445,
0.11196934431791306,
-0.07299952954053879,
0.07195407897233963,
0.09002436697483063,
0.03603000566363335,
-0.004661198705434799,
-0.0773312970995903,
-0.001481171464547515,
0.050954751670360565,
-0.26934295892715454,
0.20904844999313354,
0.0173940509557724,
0.0076441168785095215,
-0.008616345003247261,
0.018695659935474396,
0.01971212960779667,
0.23777128756046295,
0.1503746658563614,
0.015838120132684708,
0.034688856452703476,
-0.023913590237498283,
-0.06865198910236359,
0.08428139984607697,
0.0011148584308102727,
-0.029751114547252655,
0.017773497849702835,
-0.008473332040011883,
-0.00887873861938715,
0.04497412592172623,
0.08965643495321274,
-0.12281230837106705,
-0.12026208639144897,
0.10480927675962448,
-0.09679620712995529,
0.016797391697764397,
-0.04255882278084755,
-0.08601821213960648,
0.055839188396930695,
0.11548802256584167,
-0.03776425123214722,
-0.05990784242749214,
-0.09062524139881134,
-0.10649941116571426,
0.1515190601348877,
-0.07224627584218979,
0.04403197765350342,
-0.04043963551521301,
-0.013856367208063602,
-0.029281100258231163,
-0.17538517713546753,
0.17478033900260925,
-0.06987644731998444,
-0.1146465390920639,
-0.034097928553819656,
0.08369385451078415,
-0.03242255374789238,
0.08478168398141861,
-0.017975661903619766,
0.07313285768032074,
-0.09097109735012054,
-0.09654556959867477,
-0.00037942963535897434,
0.0050788684748113155,
-0.018580764532089233,
-0.06730115413665771,
0.03614291548728943,
-0.06090817227959633,
0.04415685310959816,
0.020289728417992592,
0.10059280693531036,
0.326931357383728,
-0.05821361392736435,
0.09568464010953903,
0.20101982355117798,
-0.07178565114736557,
-0.2064809948205948,
0.011923864483833313,
-0.14677686989307404,
-0.04910421371459961,
-0.03258209675550461,
-0.2050144523382187,
0.1586703509092331,
0.04934999346733093,
-0.034829966723918915,
0.11538617312908173,
-0.20220044255256653,
-0.10056440532207489,
0.06675278395414352,
0.015303140506148338,
0.2894269526004791,
-0.1983281672000885,
-0.05755871906876564,
-0.0804617777466774,
-0.2863004207611084,
0.13907040655612946,
-0.16806082427501678,
0.058746278285980225,
-0.04833342880010605,
0.01788199320435524,
0.0024103536270558834,
-0.07693501561880112,
0.19207285344600677,
-0.0006176164606586099,
0.01617475226521492,
-0.02425547130405903,
-0.14456422626972198,
0.15620355308055878,
-0.025523455813527107,
0.02218484878540039,
-0.05959729105234146,
0.03156918287277222,
-0.041778989136219025,
-0.01948131062090397,
-0.06603638827800751,
0.10256589949131012,
-0.03402592986822128,
-0.0828687846660614,
-0.07034209370613098,
0.013822716660797596,
0.011862336657941341,
-0.006531357299536467,
0.24615193903446198,
-0.03167450428009033,
0.12425438314676285,
0.12459714710712433,
0.1676122099161148,
-0.19696874916553497,
0.03382636234164238,
0.09065458178520203,
-0.03421735391020775,
0.06482980400323868,
-0.2694282829761505,
0.04061346873641014,
0.13551318645477295,
-0.0008151844376698136,
0.009245635941624641,
0.084944948554039,
-0.011103227734565735,
0.034788452088832855,
0.07498990744352341,
-0.19173292815685272,
-0.10053329169750214,
-0.030745940282940865,
-0.004515413194894791,
-0.08767702430486679,
0.10999948531389236,
0.1309131681919098,
-0.04093846306204796,
-0.03275146707892418,
-0.011572127230465412,
0.036790043115615845,
-0.07350358366966248,
0.0849946141242981,
0.07320687919855118,
0.026080511510372162,
-0.07588326185941696,
0.015795962885022163,
0.013425351120531559,
-0.15913279354572296,
-0.05103309825062752,
0.08327428996562958,
-0.08915979415178299,
-0.0996110588312149,
-0.04555858299136162,
0.03535888344049454,
-0.13132573664188385,
0.02199857495725155,
-0.14614103734493256,
-0.10406185686588287,
0.02280936762690544,
0.14537350833415985,
0.08662296831607819,
0.049159906804561615,
-0.04601385444402695,
-0.0008047518786042929,
0.05504252389073372,
0.0075948815792799,
-0.024788618087768555,
0.04867459833621979,
-0.06550639122724533,
-0.06209448724985123,
-0.03996846824884415,
0.035242363810539246,
-0.07676289230585098,
-0.01646704412996769,
-0.09587186574935913,
-0.0020580796990543604,
-0.16207018494606018,
-0.014652857556939125,
-0.14966480433940887,
-0.01888202130794525,
-0.06333266198635101,
-0.07001478224992752,
-0.07744855433702469,
-0.008110608905553818,
-0.0734742283821106,
0.015426491387188435,
-0.04167066141963005,
0.07687050849199295,
-0.1468396931886673,
0.01694307290017605,
0.07700228691101074,
-0.08297617733478546,
0.08164283633232117,
0.07076526433229446,
-0.032898444682359695,
0.04092170298099518,
-0.19141776859760284,
-0.020374534651637077,
0.0465383417904377,
0.046632070094347,
0.0052992068231105804,
-0.06990507990121841,
-0.01585528813302517,
0.03899689391255379,
0.06218396872282028,
0.0129935871809721,
0.01747099868953228,
-0.07451661676168442,
-0.021017568185925484,
-0.021954575553536415,
-0.11277399212121964,
-0.03494030609726906,
-0.002055267570540309,
0.22018209099769592,
0.00776692433282733,
0.11964350193738937,
0.0024380271788686514,
0.005566124338656664,
-0.18295250833034515,
0.020806116983294487,
0.013499850407242775,
-0.11299793422222137,
-0.08753079921007156,
-0.01945633813738823,
0.020704353228211403,
-0.030850214883685112,
0.16580142080783844,
-0.06928947567939758,
0.022888874635100365,
0.06388469785451889,
0.0781359001994133,
0.06079971790313721,
0.07576960325241089,
0.2363360971212387,
0.10363373905420303,
0.022127635776996613,
-0.030535593628883362,
0.056685708463191986,
0.0181756429374218,
0.07085628062486649,
0.13503174483776093,
0.1173914223909378,
-0.004828890785574913,
0.08945956081151962,
-0.019448963925242424,
0.04538121819496155,
-0.033837150782346725,
-0.003489386523142457,
0.005813009105622768,
0.020981701090931892,
-0.0361030213534832,
0.09574887156486511,
0.1501796841621399,
-0.06754966825246811,
0.020909307524561882,
-0.11499521136283875,
-0.07606009393930435,
-0.13553942739963531,
-0.03570529818534851,
-0.082177072763443,
-0.1786739081144333,
-0.03558589145541191,
-0.12712439894676208,
0.007752143777906895,
0.08538009226322174,
0.0016390187665820122,
-0.02348216064274311,
0.07570856064558029,
0.08303987234830856,
-0.0012083150213584304,
0.04841425269842148,
0.009985515847802162,
-0.051305897533893585,
-0.01772909425199032,
-0.013629075139760971,
-0.03507551923394203,
0.011478671804070473,
-0.06198690086603165,
0.058778315782547,
-0.05900457501411438,
0.029022227972745895,
-0.07093971222639084,
-0.11569253355264664,
-0.04448946192860603,
0.0382467657327652,
-0.029303178191184998,
0.08831974118947983,
0.0008535427041351795,
0.002510905498638749,
0.07397060096263885,
0.24836035072803497,
-0.06503524631261826,
-0.06072644516825676,
-0.08625444769859314,
0.028108417987823486,
-0.019565246999263763,
0.0966164693236351,
-0.007526500150561333,
-0.06188803166151047,
-0.04696369171142578,
0.08520015329122543,
0.2992563247680664,
-0.051420073956251144,
0.013511016964912415,
0.019842438399791718,
0.030953997746109962,
0.01357771921902895,
0.07432780414819717,
0.060488007962703705,
0.09500753879547119,
-0.1268080323934555,
-0.0021114267874509096,
-0.06083226948976517,
-0.03700859099626541,
-0.07017937302589417,
0.10213437676429749,
0.04013289511203766,
-0.02518591471016407,
-0.032441381365060806,
0.10026980936527252,
-0.09939154237508774,
0.030681710690259933,
-0.04258620738983154,
-0.21914678812026978,
-0.06405933201313019,
-0.06918274611234665,
0.07600124925374985,
-0.021234551444649696,
0.05696303769946098,
-0.029021523892879486,
-0.05544739216566086,
0.1287028193473816,
0.05068892613053322,
-0.17283868789672852,
-0.06088785082101822,
0.17304888367652893,
-0.08446439355611801,
0.10913210362195969,
-0.007347309961915016,
0.010317502543330193,
0.10062152147293091,
0.026589473709464073,
-0.0893416479229927,
0.013834756799042225,
0.10681646317243576,
-0.03597446531057358,
-0.031381770968437195,
-0.01979798823595047,
-0.007165839429944754,
0.05881521478295326,
0.07084488868713379,
-0.05127027630805969,
0.008145048283040524,
0.10494167357683182,
-0.07177775353193283,
-0.05332951992750168,
-0.0011734131257981062,
-0.0777285173535347,
0.05418164283037186,
0.016511032357811928,
-0.07036522775888443,
-0.02211977168917656,
-0.042294859886169434,
0.029908396303653717,
0.051896557211875916,
-0.0199428778141737,
-0.09061268717050552,
-0.11606571078300476,
-0.04820697009563446,
0.04834450036287308,
0.07186243683099747,
-0.12792035937309265,
-0.06463374942541122,
-0.0824485570192337,
0.071622334420681,
-0.08675002306699753,
0.04146530479192734,
0.07853518426418304,
-0.03245309367775917,
-0.013186758384108543,
-0.11769034713506699,
0.007818696089088917,
0.1207231730222702,
-0.12072550505399704,
-0.09643393754959106
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# classification-vit
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1143
- F1: 0.8957
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3758 | 1.0 | 238 | 0.2390 | 0.7505 |
| 0.2044 | 2.0 | 476 | 0.1605 | 0.8798 |
| 0.133 | 3.0 | 714 | 0.1221 | 0.8957 |
| 0.0942 | 4.0 | 952 | 0.1143 | 0.8957 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "classification-vit", "results": []}]} | image-classification | akashmaggon/classification-vit | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"base_model:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T08:17:02+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| classification-vit
==================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1143
* F1: 0.8957
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 4\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 4\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
75,
112,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 4\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.10316942632198334,
0.11641054600477219,
-0.0033045627642422915,
0.09384892880916595,
0.1079195886850357,
-0.011310691945254803,
0.17146718502044678,
0.1376083493232727,
-0.11201780289411545,
0.07011754810810089,
0.13649404048919678,
0.10814400762319565,
0.04561545327305794,
0.17442797124385834,
-0.06114177033305168,
-0.23479045927524567,
0.05628830939531326,
0.033363841474056244,
-0.018047746270895004,
0.11615002900362015,
0.08101430535316467,
-0.13539785146713257,
0.10406908392906189,
0.03560619801282883,
-0.17794562876224518,
-0.006812417414039373,
0.023519441485404968,
-0.07785408943891525,
0.10359177738428116,
0.029752438887953758,
0.10401270538568497,
0.04782801866531372,
0.0701015368103981,
-0.16162803769111633,
0.011805652640759945,
0.0785147100687027,
-0.011246277950704098,
0.09160882234573364,
0.05619412660598755,
-0.004212026484310627,
0.0474558100104332,
-0.0808398425579071,
0.07068100571632385,
0.020499711856245995,
-0.1215563490986824,
-0.2728251814842224,
-0.11364836990833282,
0.05361965298652649,
0.09807267785072327,
0.06397081166505814,
-0.002233479404821992,
0.18602214753627777,
-0.02683902718126774,
0.09763481467962265,
0.22712232172489166,
-0.30837875604629517,
-0.07130113244056702,
0.006872483063489199,
0.03939839452505112,
0.0715695321559906,
-0.09191514551639557,
-0.002654844429343939,
0.039952460676431656,
0.02521367557346821,
0.13225595653057098,
0.001413075253367424,
-0.01824980042874813,
-0.028073661029338837,
-0.12777873873710632,
-0.05576064810156822,
0.14581908285617828,
0.06677445024251938,
-0.06023336946964264,
-0.05895795673131943,
-0.06718148291110992,
-0.16799461841583252,
-0.06458130478858948,
0.0026942919939756393,
0.0546749122440815,
-0.03450103849172592,
-0.092351034283638,
-0.007034029811620712,
-0.08352914452552795,
-0.06484192609786987,
-0.04465961828827858,
0.13933207094669342,
0.055594898760318756,
0.023145975545048714,
-0.04666687175631523,
0.07228206843137741,
-0.06382200121879578,
-0.1592392772436142,
-0.017590316012501717,
0.013051638379693031,
0.013599085621535778,
-0.04684377834200859,
-0.01835004612803459,
-0.11880577355623245,
0.02047385647892952,
0.14740274846553802,
-0.10396233201026917,
0.08166838437318802,
-0.052609801292419434,
0.044668667018413544,
-0.10470341145992279,
0.18199795484542847,
-0.036419954150915146,
0.041715532541275024,
0.03382732346653938,
0.09338505566120148,
0.07739970833063126,
-0.012945104390382767,
-0.11001121252775192,
0.04350252076983452,
0.12159671634435654,
0.022322623059153557,
-0.0384209118783474,
0.07614509016275406,
-0.04829425737261772,
-0.005187928676605225,
0.08466613292694092,
-0.08182919025421143,
0.0452859029173851,
-0.004843289032578468,
-0.05485163629055023,
-0.05986012890934944,
0.03296642750501633,
0.0102456109598279,
-0.005106830038130283,
0.08820713311433792,
-0.08265938609838486,
0.02193859964609146,
-0.0762043222784996,
-0.1302172988653183,
0.03298277035355568,
-0.09124036133289337,
0.011175192892551422,
-0.1198335736989975,
-0.11951924860477448,
-0.0012716463534161448,
0.059089623391628265,
-0.04007190093398094,
-0.02006428688764572,
-0.033384669572114944,
-0.09788131713867188,
0.04214330017566681,
-0.009737880900502205,
0.03677428886294365,
-0.07741260528564453,
0.08666190505027771,
0.0453830324113369,
0.08126235008239746,
-0.051373325288295746,
0.028112754225730896,
-0.09476536512374878,
0.060322657227516174,
-0.2531941533088684,
0.023947367444634438,
-0.07472072541713715,
0.10739339143037796,
-0.10641173273324966,
-0.09088312834501266,
0.014290674589574337,
-0.02826787903904915,
0.09432492405176163,
0.09170009195804596,
-0.169189915060997,
-0.050548672676086426,
0.17861168086528778,
-0.1141132265329361,
-0.15086591243743896,
0.13186034560203552,
-0.03167246654629707,
-0.0003080212336499244,
0.052448537200689316,
0.21329933404922485,
0.06947033107280731,
-0.12804901599884033,
-0.01439097709953785,
-0.06380964070558548,
0.036044538021087646,
-0.039616659283638,
0.06554953753948212,
0.01331856194883585,
0.04131089150905609,
0.0064531294628977776,
-0.02490086294710636,
0.04352867975831032,
-0.07977979630231857,
-0.08193820714950562,
-0.060503456741571426,
-0.07407252490520477,
0.024962328374385834,
0.04727409407496452,
0.05318504571914673,
-0.1369725614786148,
-0.11257897317409515,
0.03686995059251785,
0.07207483053207397,
-0.06865337491035461,
0.03570491820573807,
-0.1258402019739151,
0.1291092187166214,
-0.07881190627813339,
-0.002098998986184597,
-0.14192381501197815,
-0.04308968782424927,
0.040157854557037354,
-0.03962131589651108,
0.010315004736185074,
-0.08380434662103653,
0.07855000346899033,
0.07771944254636765,
-0.0536775141954422,
-0.05578520894050598,
-0.025353064760565758,
0.01789381168782711,
-0.10549894720315933,
-0.21680496633052826,
-0.023125723004341125,
-0.03609912469983101,
0.09092066437005997,
-0.1815589964389801,
0.04432836174964905,
0.08930503576993942,
0.13324519991874695,
0.06748755276203156,
-0.02056998945772648,
-0.004032460507005453,
0.05041007697582245,
-0.03544384241104126,
-0.08699952811002731,
0.05223795399069786,
0.022827893495559692,
-0.06299898028373718,
0.0032758754678070545,
-0.14509320259094238,
0.18105585873126984,
0.14763294160366058,
-0.010323389433324337,
-0.06893054395914078,
-0.0018119652522727847,
-0.03604700416326523,
-0.025770995765924454,
-0.02826479636132717,
0.030036477372050285,
0.113848976790905,
0.00909610465168953,
0.14590054750442505,
-0.1038687452673912,
-0.02428358793258667,
0.06312756985425949,
-0.03908035159111023,
-0.02675793319940567,
0.08207672834396362,
0.05315088853240013,
-0.15845917165279388,
0.13685347139835358,
0.17171187698841095,
-0.06986721605062485,
0.11147404462099075,
-0.06386668980121613,
-0.04964245483279228,
-0.02489006333053112,
0.0246156994253397,
0.04182978346943855,
0.14724460244178772,
-0.1037353128194809,
-0.016349472105503082,
0.01307374332100153,
0.011448468081653118,
-0.012339417822659016,
-0.20794488489627838,
0.0026152662467211485,
0.030263520777225494,
-0.05670632794499397,
-0.03829832375049591,
-0.017865769565105438,
0.004615099634975195,
0.0941317081451416,
0.01473444327712059,
-0.07387208193540573,
0.03760525584220886,
0.01762969233095646,
-0.060054656118154526,
0.17533107101917267,
-0.10250156372785568,
-0.1691296398639679,
-0.12425258010625839,
-0.05927906185388565,
-0.06395886838436127,
0.008940942585468292,
0.07594051957130432,
-0.09077031910419464,
-0.06572995334863663,
-0.1152849793434143,
-0.04268810153007507,
0.03914601355791092,
0.032830700278282166,
0.03488169610500336,
0.0025963434018194675,
0.11449287831783295,
-0.09557546675205231,
-0.015080372802913189,
-0.010357055813074112,
0.004742943216115236,
0.06192911043763161,
0.025947200134396553,
0.113187275826931,
0.09496165812015533,
-0.049984972923994064,
0.030039358884096146,
-0.026821311563253403,
0.22599275410175323,
-0.08042410016059875,
-0.009942514821887016,
0.13065050542354584,
-0.002556669292971492,
0.07725263386964798,
0.1482653170824051,
0.048098258674144745,
-0.10627450048923492,
0.003674115287140012,
0.02017856203019619,
-0.03482907637953758,
-0.1865386813879013,
-0.006381448358297348,
-0.030212443321943283,
-0.0052392990328371525,
0.1183900386095047,
0.05333702638745308,
0.026985449716448784,
0.06471484899520874,
0.0016958157066255808,
0.05526858568191528,
0.0053986418060958385,
0.11177188158035278,
0.10657533258199692,
0.057281218469142914,
0.13152973353862762,
-0.05848287045955658,
-0.026957103982567787,
0.03344147279858589,
0.009422692470252514,
0.21362178027629852,
0.015977662056684494,
0.14786779880523682,
0.04924148693680763,
0.18545888364315033,
0.045215025544166565,
0.042897503823041916,
-0.016619931906461716,
-0.03178132697939873,
-0.004946755710989237,
-0.052942462265491486,
-0.019719237461686134,
0.03346029296517372,
-0.06661318987607956,
0.04003465548157692,
-0.09237074851989746,
0.03202362731099129,
0.06271372735500336,
0.2894669473171234,
0.041763126850128174,
-0.3893508315086365,
-0.09718871116638184,
0.01239275187253952,
-0.036272913217544556,
-0.05619073659181595,
0.011458291672170162,
0.1077754870057106,
-0.03781438618898392,
0.08790817856788635,
-0.09118364751338959,
0.09450151771306992,
-0.03757266327738762,
0.025585873052477837,
0.06853493303060532,
0.08479101210832596,
-0.012646125629544258,
0.03655971214175224,
-0.2418171465396881,
0.268809050321579,
0.03227341175079346,
0.07950769364833832,
-0.042397309094667435,
0.012043800204992294,
0.030607033520936966,
0.12321475893259048,
0.07039150595664978,
-0.014717967249453068,
-0.11139079928398132,
-0.17900148034095764,
-0.09973224997520447,
0.013058092445135117,
0.09157940000295639,
0.020654117688536644,
0.10859251767396927,
-0.017595918849110603,
-0.015061105601489544,
0.04989852383732796,
-0.0502183735370636,
-0.09450045973062515,
-0.08117680996656418,
0.002066797809675336,
0.04763035476207733,
0.021827079355716705,
-0.09991450607776642,
-0.09548653662204742,
-0.09459579735994339,
0.15533101558685303,
0.00934232771396637,
-0.04389260336756706,
-0.11339578032493591,
0.038818467408418655,
0.06237441301345825,
-0.0724930688738823,
0.05464532598853111,
-0.02364722453057766,
0.13316689431667328,
0.017617717385292053,
-0.06488208472728729,
0.13114383816719055,
-0.05615058168768883,
-0.18146733939647675,
-0.0571451373398304,
0.09741736948490143,
-0.010447567328810692,
0.03509329631924629,
0.004494107328355312,
0.03634162247180939,
0.0008081242558546364,
-0.06136227026581764,
0.046605441719293594,
-0.01114262081682682,
0.06689153611660004,
-0.044253453612327576,
0.00017043932166416198,
0.003431588178500533,
-0.06693346053361893,
-0.02224000170826912,
0.1174146831035614,
0.2809112071990967,
-0.09182656556367874,
0.02711580879986286,
0.04408234730362892,
-0.034578531980514526,
-0.17774063348770142,
0.04136112332344055,
0.03415713831782341,
-0.011824247427284718,
0.00003714042031788267,
-0.13941943645477295,
0.03687448427081108,
0.08968554437160492,
-0.03952866420149803,
0.09591672569513321,
-0.25953933596611023,
-0.13094468414783478,
0.09601633250713348,
0.16216875612735748,
0.06243179365992546,
-0.16435621678829193,
-0.05136524513363838,
-0.023158784955739975,
-0.10773323476314545,
0.10611876100301743,
-0.12597906589508057,
0.09405314922332764,
-0.01709926873445511,
0.05285080522298813,
0.0060283103957772255,
-0.06053806468844414,
0.13665451109409332,
-0.06125927343964577,
0.11642594635486603,
-0.07709953933954239,
0.024776404723525047,
0.09757695347070694,
-0.0890849381685257,
0.049160443246364594,
-0.08912287652492523,
0.045637860894203186,
-0.05279098451137543,
-0.004895087797194719,
-0.052030667662620544,
0.010471143759787083,
-0.025008171796798706,
-0.01697392202913761,
-0.06452816724777222,
0.022285815328359604,
0.037013523280620575,
-0.021723154932260513,
0.22848030924797058,
0.029490360990166664,
0.12771503627300262,
0.15169267356395721,
0.08729974925518036,
-0.1273583471775055,
-0.026981042698025703,
0.009978984482586384,
-0.04227360337972641,
0.07859841734170914,
-0.173181414604187,
0.0561620332300663,
0.1109294667840004,
-0.0028077764436602592,
0.11971880495548248,
0.05257716402411461,
-0.055134862661361694,
0.032983824610710144,
0.07884114235639572,
-0.16172438859939575,
-0.13652651011943817,
0.008430169895291328,
0.06929544359445572,
-0.09725601971149445,
0.07763976603746414,
0.12471160292625427,
-0.08172594755887985,
-0.0062938109040260315,
0.008837317116558552,
0.02789347432553768,
-0.008748278021812439,
0.16331903636455536,
0.04596487432718277,
0.051693134009838104,
-0.09625754505395889,
0.09011467546224594,
0.05555056780576706,
-0.1208103597164154,
0.032273586839437485,
0.06747855246067047,
-0.1060863584280014,
-0.03500235080718994,
0.050575267523527145,
0.16360019147396088,
-0.014747259207069874,
-0.07328677177429199,
-0.15831591188907623,
-0.12511597573757172,
0.06405068933963776,
0.19615456461906433,
0.06299249827861786,
0.0007364485063590109,
0.0033466380555182695,
0.004628617316484451,
-0.1088477373123169,
0.10525628924369812,
0.02858138456940651,
0.10450093448162079,
-0.18794551491737366,
0.08715320378541946,
0.004932991228997707,
0.01634438894689083,
-0.017934268340468407,
0.034070517867803574,
-0.11633501946926117,
0.002525811083614826,
-0.13158158957958221,
0.033352240920066833,
-0.04728180542588234,
0.016407262533903122,
-0.0024273053277283907,
-0.055973730981349945,
-0.07107122242450714,
0.023760665208101273,
-0.1069486141204834,
-0.0298903975635767,
0.03632611781358719,
0.037132490426301956,
-0.11805635690689087,
-0.026534562930464745,
0.017344404011964798,
-0.08368746936321259,
0.07084339112043381,
0.0220330823212862,
0.00405111676082015,
0.02591457962989807,
-0.07656896114349365,
0.0011744198855012655,
0.08077152073383331,
-0.0007789391092956066,
0.052562929689884186,
-0.11421902477741241,
-0.014059021137654781,
0.009541370905935764,
0.008431265130639076,
0.015130155719816685,
0.12549415230751038,
-0.11572317034006119,
-0.0134909488260746,
-0.013802344910800457,
-0.052632078528404236,
-0.051150064915418625,
0.06058454141020775,
0.11323964595794678,
-0.00446440139785409,
0.20364943146705627,
-0.09679780900478363,
-0.010684482753276825,
-0.19427205622196198,
0.006121438462287188,
-0.001717740553431213,
-0.14708980917930603,
-0.08780355006456375,
-0.021740516647696495,
0.0580424927175045,
-0.07877090573310852,
0.100193552672863,
0.01303296722471714,
0.017075680196285248,
0.055258188396692276,
-0.04095316305756569,
-0.02755451202392578,
0.036594703793525696,
0.15771445631980896,
0.0110158147290349,
-0.03034970536828041,
0.05511721223592758,
0.003957425244152546,
0.09651301056146622,
0.05952657386660576,
0.14026319980621338,
0.15506136417388916,
0.006438927724957466,
0.11219869554042816,
0.06343228369951248,
-0.028660720214247704,
-0.16731518507003784,
0.09023985266685486,
-0.0686870738863945,
0.13653287291526794,
-0.014957458712160587,
0.1626344472169876,
0.15350498259067535,
-0.1334460824728012,
0.020744098350405693,
-0.04895756393671036,
-0.07594970613718033,
-0.09024005383253098,
-0.09714939445257187,
-0.11073093861341476,
-0.18117408454418182,
0.006057261489331722,
-0.09413857012987137,
0.03439883142709732,
0.05169998109340668,
0.005806271452456713,
-0.0045999581925570965,
0.16535046696662903,
0.028116067871451378,
0.021973742172122,
0.05849543958902359,
0.004059528931975365,
-0.06752216815948486,
-0.028822246938943863,
-0.09688674658536911,
0.0407920703291893,
-0.017849953845143318,
0.03155674412846565,
-0.005873419344425201,
-0.005166263785213232,
0.05121698975563049,
-0.0013749791542068124,
-0.11735949665307999,
0.02170795015990734,
0.022880936041474342,
0.03718551620841026,
0.014279204420745373,
0.013278300873935223,
0.017441214993596077,
-0.001823627040721476,
0.18293625116348267,
-0.07129120826721191,
-0.04081319272518158,
-0.11985094845294952,
0.20385274291038513,
-0.002001015702262521,
-0.020230039954185486,
0.018131479620933533,
-0.08358588069677353,
0.018204346299171448,
0.1739436388015747,
0.14459799230098724,
-0.020168418064713478,
-0.000674621609505266,
-0.042376842349767685,
-0.018144823610782623,
-0.05508001148700714,
0.0912148728966713,
0.10977702587842941,
-0.041694480925798416,
-0.06206655502319336,
-0.042897846549749374,
-0.06131098419427872,
-0.003958418965339661,
-0.049873583018779755,
0.04194403067231178,
0.012572440318763256,
0.013609282672405243,
-0.06932629644870758,
0.06059567257761955,
-0.00734880194067955,
-0.06019306927919388,
0.07225506752729416,
-0.18699760735034943,
-0.14841321110725403,
-0.0018450752831995487,
0.1081879734992981,
-0.019907966256141663,
0.03361636400222778,
-0.019250357523560524,
0.004964017774909735,
0.056398626416921616,
-0.023017721250653267,
-0.05913501977920532,
-0.10445082187652588,
0.07082100212574005,
-0.14632226526737213,
0.24436713755130768,
-0.02706972323358059,
0.012766879983246326,
0.13372376561164856,
0.026768773794174194,
-0.1173144206404686,
0.06845077127218246,
0.03614962846040726,
-0.0783485472202301,
0.0043882583267986774,
0.12358058989048004,
-0.02655993029475212,
0.11980777233839035,
0.043790243566036224,
-0.0965784341096878,
-0.015225968323647976,
-0.10015781968832016,
-0.0449240617454052,
-0.03832332789897919,
-0.02408369444310665,
-0.05619753897190094,
0.11650054901838303,
0.16563387215137482,
-0.03662571683526039,
-0.002868142444640398,
-0.0518210344016552,
0.03079894557595253,
0.08040116727352142,
-0.020136035978794098,
-0.02838851325213909,
-0.2527414560317993,
0.026370929554104805,
0.06907382607460022,
0.00005455176506075077,
-0.24560318887233734,
-0.09099876880645752,
-0.003938044421374798,
-0.03132856264710426,
-0.09202730655670166,
0.09115362912416458,
0.126018688082695,
0.05101125314831734,
-0.07293751090765,
-0.06470790505409241,
-0.06478957086801529,
0.16443824768066406,
-0.11833421885967255,
-0.07624749094247818
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# codet5p-220m-v23
This model is a fine-tuned version of [Salesforce/codet5p-220m](https://huggingface.co/Salesforce/codet5p-220m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0889
- Bleu Score: 0.0014
- Gen Len: 14.6449
## Model description
trained,
- on: chathuranga-jayanath/context-5-finmath-times4j-html-mavendoxia-wro4j-guava-supercsv-len-10000-prompt-1
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:----------:|:-------:|
| 0.1539 | 1.0 | 3752 | 0.1106 | 0.0014 | 14.617 |
| 0.085 | 2.0 | 7504 | 0.0905 | 0.0014 | 14.6366 |
| 0.0558 | 3.0 | 11256 | 0.0889 | 0.0014 | 14.6449 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "base_model": "Salesforce/codet5p-220m", "model-index": [{"name": "codet5p-220m-v23", "results": []}]} | text2text-generation | chathuranga-jayanath/codet5p-220m-v23 | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:Salesforce/codet5p-220m",
"license:bsd-3-clause",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T08:17:21+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-Salesforce/codet5p-220m #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| codet5p-220m-v23
================
This model is a fine-tuned version of Salesforce/codet5p-220m on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0889
* Bleu Score: 0.0014
* Gen Len: 14.6449
Model description
-----------------
trained,
* on: chathuranga-jayanath/context-5-finmath-times4j-html-mavendoxia-wro4j-guava-supercsv-len-10000-prompt-1
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 2e-05
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP
### Training results
### Framework versions
* Transformers 4.38.0.dev0
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 10\n* eval\\_batch\\_size: 10\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-Salesforce/codet5p-220m #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 10\n* eval\\_batch\\_size: 10\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
86,
113,
4,
38
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-Salesforce/codet5p-220m #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 10\n* eval\\_batch\\_size: 10\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3\n* mixed\\_precision\\_training: Native AMP### Training results### Framework versions\n\n\n* Transformers 4.38.0.dev0\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.13779756426811218,
0.13373605906963348,
-0.0024200831539928913,
0.08876177668571472,
0.12957341969013214,
0.02082160674035549,
0.15829750895500183,
0.11585669219493866,
-0.06889481097459793,
0.08006215840578079,
0.13330784440040588,
0.11272196471691132,
0.05826100334525108,
0.1889565885066986,
-0.061090536415576935,
-0.2008703052997589,
0.0365065298974514,
0.04811323434114456,
-0.046173401176929474,
0.14473071694374084,
0.09022606164216995,
-0.12279605120420456,
0.07358057796955109,
0.0017769676633179188,
-0.1708497554063797,
-0.04379229620099068,
0.006416019517928362,
-0.062167320400476456,
0.12254545837640762,
0.027291355654597282,
0.13469597697257996,
0.0633612722158432,
0.08225887268781662,
-0.15433759987354279,
0.012987268157303333,
0.05891851708292961,
-0.007275049574673176,
0.0975109413266182,
0.0702543556690216,
0.008994624018669128,
0.06400444358587265,
-0.07706640660762787,
0.055653367191553116,
0.01469026692211628,
-0.11535527557134628,
-0.18486100435256958,
-0.10297531634569168,
0.09784301370382309,
0.08078403770923615,
0.08064768463373184,
-0.0018179448088631034,
0.11188679188489914,
-0.03220684453845024,
0.09009820967912674,
0.2051077038049698,
-0.2992987036705017,
-0.05276916176080704,
-0.009011693298816681,
0.04721551015973091,
0.08086321502923965,
-0.0792098343372345,
-0.04779062047600746,
0.040022898465394974,
0.03700398653745651,
0.1341889649629593,
0.001958281733095646,
-0.0056917364709079266,
-0.028724756091833115,
-0.14700493216514587,
-0.08967653661966324,
0.1334381401538849,
0.040661152452230453,
-0.046717822551727295,
-0.07347368448972702,
-0.08019766956567764,
-0.19920751452445984,
-0.020475972443819046,
0.0035849714186042547,
0.006384135689586401,
-0.0317019559442997,
-0.06083320826292038,
-0.014457013458013535,
-0.10265648365020752,
-0.0741901695728302,
-0.021514330059289932,
0.1356344223022461,
0.05424865335226059,
0.009467631578445435,
-0.006447705905884504,
0.11263054609298706,
0.04779331013560295,
-0.15396782755851746,
0.00568004883825779,
0.008354256860911846,
0.0019862232729792595,
-0.014227108098566532,
-0.03315358981490135,
-0.05529055744409561,
0.014830095693469048,
0.10502326488494873,
-0.08371981978416443,
0.02867651917040348,
0.009940912947058678,
0.041042543947696686,
-0.10390755534172058,
0.15262249112129211,
-0.05000573769211769,
-0.007291346322745085,
0.037532366812229156,
0.1350422203540802,
0.0518651083111763,
-0.0227616298943758,
-0.10938207805156708,
-0.020257726311683655,
0.1552720069885254,
0.03470216691493988,
-0.018968675285577774,
0.052914660423994064,
-0.07327722758054733,
-0.029297910630702972,
0.1003890335559845,
-0.09999895840883255,
-0.0033470571506768465,
0.02019667997956276,
-0.04265429824590683,
-0.04576728120446205,
0.04101458936929703,
-0.006835345644503832,
-0.03725433722138405,
0.07067538797855377,
-0.08421749621629715,
-0.019425295293331146,
-0.07979250699281693,
-0.12170571833848953,
0.028450319543480873,
-0.09404466301202774,
-0.012315437197685242,
-0.10963406413793564,
-0.17188473045825958,
-0.03013746067881584,
0.007233117241412401,
-0.016063565388321877,
-0.08034593611955643,
-0.04633677378296852,
-0.09259197115898132,
0.02584260329604149,
-0.033703651279211044,
0.08014719933271408,
-0.050938233733177185,
0.13356199860572815,
0.023280175402760506,
0.05310191586613655,
-0.02905191481113434,
0.04970104992389679,
-0.07424484193325043,
0.05222050100564957,
-0.12410830706357956,
0.06080874055624008,
-0.051186397671699524,
0.03167162463068962,
-0.09121014922857285,
-0.1075039803981781,
0.0103678023442626,
-0.025130273774266243,
0.10235628485679626,
0.11315994709730148,
-0.14755086600780487,
-0.05909912660717964,
0.20371423661708832,
-0.11251507699489594,
-0.13014915585517883,
0.1136702224612236,
-0.02569439262151718,
-0.011645668186247349,
0.04250083118677139,
0.14153282344341278,
0.10137402266263962,
-0.06855176389217377,
-0.01998733915388584,
-0.022177301347255707,
0.0736098513007164,
-0.08452151715755463,
0.10517558455467224,
-0.0010998949874192476,
-0.009012434631586075,
0.012214750051498413,
-0.07732469588518143,
0.053290821611881256,
-0.09171531349420547,
-0.0786391943693161,
-0.036239154636859894,
-0.08098144829273224,
0.0729069858789444,
0.04785960540175438,
0.04014228656888008,
-0.08442489057779312,
-0.11022211611270905,
0.03845132514834404,
0.0974932461977005,
-0.10135918855667114,
0.011962588876485825,
-0.0759492814540863,
0.12446665018796921,
-0.09786982834339142,
-0.018909193575382233,
-0.17559944093227386,
-0.07032561302185059,
0.03437618538737297,
-0.030073992908000946,
-0.010585957206785679,
-0.020045282319188118,
0.05961093679070473,
0.09278056025505066,
-0.03509828820824623,
-0.07379648834466934,
-0.0720643624663353,
-0.0058400449343025684,
-0.10197856277227402,
-0.18250150978565216,
-0.06714252382516861,
-0.02461038902401924,
0.16713178157806396,
-0.19476456940174103,
0.04088572785258293,
0.019490007311105728,
0.10303223133087158,
0.01777762360870838,
-0.030700020492076874,
-0.012542899698019028,
0.08131959289312363,
-0.034460749477148056,
-0.06471682339906693,
0.07354363054037094,
0.03336265683174133,
-0.09875130653381348,
0.03191719576716423,
-0.15581101179122925,
0.14490748941898346,
0.120319664478302,
0.011418936774134636,
-0.0663311704993248,
-0.017195288091897964,
-0.06546343863010406,
-0.03827231004834175,
-0.017170816659927368,
-0.009308387525379658,
0.12357324361801147,
0.023621702566742897,
0.15339235961437225,
-0.09764479845762253,
-0.04505039006471634,
0.031004128977656364,
-0.003036595182493329,
0.0032858250197023153,
0.1118868738412857,
0.06443572044372559,
-0.08957168459892273,
0.14602325856685638,
0.13339905440807343,
-0.05411071702837944,
0.12203177809715271,
-0.060672320425510406,
-0.08159288018941879,
-0.026602478697896004,
0.037560224533081055,
0.031098177656531334,
0.10100845247507095,
-0.08751317858695984,
0.004337991587817669,
0.039923567324876785,
-0.0026278633158653975,
0.02163061499595642,
-0.2219129055738449,
-0.010428216308355331,
0.02969323843717575,
-0.0670284777879715,
-0.015854408964514732,
-0.005479797720909119,
0.014259257353842258,
0.10011737793684006,
0.006321742665022612,
-0.050058428198099136,
0.043298058211803436,
-0.0006238180212676525,
-0.09243357181549072,
0.20481453835964203,
-0.07852957397699356,
-0.1845611184835434,
-0.15934431552886963,
0.004901846870779991,
-0.04262511804699898,
0.005776914767920971,
0.045629825443029404,
-0.041632555425167084,
-0.040300436317920685,
-0.09182366728782654,
-0.011019156314432621,
0.0198961291462183,
0.02414509281516075,
0.02171710692346096,
-0.014118250459432602,
0.06823340803384781,
-0.10611513257026672,
-0.006909212563186884,
-0.009346425533294678,
-0.03864063322544098,
0.05341261252760887,
0.028731247410178185,
0.10800919681787491,
0.1492387056350708,
-0.02288123406469822,
0.005109474528580904,
-0.03281919285655022,
0.1957511007785797,
-0.05140358954668045,
-0.03043113835155964,
0.15174484252929688,
-0.03182589262723923,
0.07670628279447556,
0.14277614653110504,
0.03054547868669033,
-0.0673152282834053,
0.00569837586954236,
-0.014704041182994843,
-0.031087152659893036,
-0.23512206971645355,
-0.04636182263493538,
-0.04887690022587776,
-0.007576064672321081,
0.10547539591789246,
0.02581629902124405,
0.011929590255022049,
0.07245537638664246,
-0.02465052716434002,
0.06671811640262604,
-0.0112958624958992,
0.08268020302057266,
0.11784961074590683,
0.052591823041439056,
0.13494326174259186,
-0.03800411894917488,
-0.03057991713285446,
0.031522221863269806,
-0.0035026429686695337,
0.21949002146720886,
-0.05890924856066704,
0.20351846516132355,
0.05686390772461891,
0.19057630002498627,
0.04068000614643097,
0.09190241992473602,
-0.002719268901273608,
0.013869216665625572,
0.0016624925192445517,
-0.048954810947179794,
-0.08147165179252625,
0.001011995947919786,
-0.03955557197332382,
0.05934019386768341,
-0.12301711738109589,
0.02021929621696472,
0.008124747313559055,
0.2736395299434662,
0.055736590176820755,
-0.37930595874786377,
-0.10922154784202576,
-0.004711238667368889,
-0.009796908125281334,
-0.05327369645237923,
-0.0009027914493344724,
0.1346946656703949,
-0.08669107407331467,
0.029723765328526497,
-0.08167357742786407,
0.08062434196472168,
-0.07289807498455048,
0.004558877553790808,
0.05269169062376022,
0.07858818024396896,
0.008372282609343529,
0.06392501294612885,
-0.2474234253168106,
0.25601497292518616,
-0.004826725926250219,
0.06060367822647095,
-0.05585119128227234,
0.011056429706513882,
0.008215080015361309,
0.02154342271387577,
0.06802620738744736,
-0.013409927487373352,
-0.01144319772720337,
-0.18801066279411316,
-0.13061876595020294,
0.015066486783325672,
0.07917536050081253,
-0.036102719604969025,
0.12282473593950272,
-0.03512300178408623,
-0.003358826506882906,
0.038024213165044785,
-0.02555571310222149,
-0.05029061809182167,
-0.0982925072312355,
0.035667575895786285,
0.011024369858205318,
0.03999581187963486,
-0.10282709449529648,
-0.12787623703479767,
-0.06340926885604858,
0.14919103682041168,
-0.08912046253681183,
-0.0808221772313118,
-0.11182878166437149,
0.07196102291345596,
0.10217397660017014,
-0.09958615154027939,
0.05692107975482941,
-0.0105867525562644,
0.13371697068214417,
0.0031094772275537252,
-0.06002817302942276,
0.06833069771528244,
-0.05939428135752678,
-0.2227315753698349,
-0.04290153458714485,
0.1556721180677414,
0.0044678631238639355,
0.04829428717494011,
-0.005313560366630554,
0.016008855774998665,
-0.01985633745789528,
-0.08105889707803726,
0.0011469086166471243,
0.03945678099989891,
0.0734979510307312,
0.013024704530835152,
-0.02907373011112213,
-0.02643895521759987,
-0.04786790907382965,
-0.026238154619932175,
0.1609523445367813,
0.2582481801509857,
-0.08738487213850021,
0.034197378903627396,
0.04734542593359947,
-0.047260068356990814,
-0.19212207198143005,
-0.02475971169769764,
0.10315913707017899,
0.038653161376714706,
-0.002430184278637171,
-0.12408515810966492,
0.032983824610710144,
0.07841596752405167,
-0.02787824161350727,
0.08964911103248596,
-0.3057618737220764,
-0.13522425293922424,
0.08451779186725616,
0.16335272789001465,
0.08941381424665451,
-0.16076014935970306,
-0.06436970084905624,
-0.005696985870599747,
-0.1681404411792755,
0.1454605758190155,
-0.05561050772666931,
0.10266566276550293,
-0.034402456134557724,
0.05592617392539978,
0.013706143945455551,
-0.06976451724767685,
0.1263100802898407,
-0.02322421222925186,
0.046848393976688385,
-0.05153907090425491,
0.002771918661892414,
0.08944495022296906,
-0.06457448750734329,
0.027378790080547333,
-0.06411299854516983,
0.0589534193277359,
-0.09620806574821472,
-0.030440792441368103,
-0.09221632033586502,
0.019992703571915627,
-0.04661655053496361,
-0.03042503446340561,
-0.006343476939946413,
0.024511775001883507,
0.04802266135811806,
-0.015270437113940716,
0.11166924983263016,
0.026281988248229027,
0.13552498817443848,
0.13869601488113403,
0.08228157460689545,
-0.011539432220160961,
-0.03873547539114952,
-0.03847072273492813,
-0.03883569687604904,
0.04841390252113342,
-0.11221566051244736,
0.022840339690446854,
0.13325117528438568,
0.027812903746962547,
0.13077767193317413,
0.06319954246282578,
-0.05495596304535866,
0.018753714859485626,
0.07060378789901733,
-0.1624351292848587,
-0.12919498980045319,
-0.0155141307041049,
0.002104388317093253,
-0.14552098512649536,
0.03290347754955292,
0.12285247445106506,
-0.06839682906866074,
-0.0265676137059927,
-0.009958352893590927,
0.00825574155896902,
-0.012676716782152653,
0.1800408661365509,
0.06395751982927322,
0.07269208878278732,
-0.09821292012929916,
0.06357046961784363,
0.06434974819421768,
-0.10552196949720383,
0.017150284722447395,
0.05840388685464859,
-0.11135785281658173,
-0.029416631907224655,
0.039896752685308456,
0.12254972755908966,
-0.039402782917022705,
-0.05879506468772888,
-0.12959285080432892,
-0.12392017245292664,
0.07796080410480499,
0.14828675985336304,
0.06708675622940063,
0.057771846652030945,
-0.0044893743470311165,
-0.005466497968882322,
-0.11606459319591522,
0.11600985378026962,
0.06231192871928215,
0.08681734651327133,
-0.13885317742824554,
0.15674802660942078,
-0.001385037088766694,
0.04393070936203003,
-0.012522176839411259,
0.03863510116934776,
-0.09201028198003769,
-0.018670212477445602,
-0.1305149793624878,
0.034022729843854904,
-0.0434945672750473,
-0.006202314514666796,
-0.0201072059571743,
-0.04971371591091156,
-0.0428510420024395,
0.03154706209897995,
-0.08790510892868042,
-0.04987426474690437,
-0.0023371537681668997,
0.04196067526936531,
-0.12301121652126312,
-0.025165298953652382,
0.019578294828534126,
-0.09458678215742111,
0.09409039467573166,
0.036303795874118805,
0.027156073600053787,
0.031420379877090454,
-0.06701675057411194,
0.016520168632268906,
0.045216187834739685,
0.01630394719541073,
0.03529823198914528,
-0.10783030092716217,
0.010175289586186409,
0.008342013694345951,
-0.01316917035728693,
0.009883519262075424,
0.09551727026700974,
-0.12951898574829102,
-0.005263886880129576,
-0.009443774819374084,
-0.012576029635965824,
-0.07414007931947708,
0.05436202883720398,
0.06262826174497604,
0.033036574721336365,
0.17999866604804993,
-0.08610810339450836,
0.03606320917606354,
-0.21539461612701416,
-0.005624387413263321,
-0.018595809116959572,
-0.0905936062335968,
-0.11125500500202179,
-0.03761429712176323,
0.07167482376098633,
-0.04078787565231323,
0.08302046358585358,
-0.03626421466469765,
0.05929188057780266,
0.015543907880783081,
-0.009001149795949459,
0.02288714237511158,
0.030058683827519417,
0.207766592502594,
0.011532342061400414,
-0.03668976202607155,
0.04290136322379112,
0.0044495235197246075,
0.06412237137556076,
0.054532118141651154,
0.16670900583267212,
0.14633876085281372,
0.018675031140446663,
0.07890347391366959,
0.05713338404893875,
-0.03956249728798866,
-0.1530119925737381,
0.03219139575958252,
-0.0472528450191021,
0.09532000124454498,
-0.0017437365604564548,
0.23139651119709015,
0.09011777490377426,
-0.17233909666538239,
0.017936458811163902,
-0.01645093783736229,
-0.08069125562906265,
-0.08104760199785233,
-0.08176015317440033,
-0.08632122725248337,
-0.12061171233654022,
0.001961363945156336,
-0.11786726862192154,
0.002505590207874775,
0.09820009768009186,
0.012984594330191612,
-0.01773933507502079,
0.1383277028799057,
0.0681169405579567,
0.00006143064820207655,
0.05086026340723038,
0.021677087992429733,
0.007936841808259487,
-0.050823502242565155,
-0.09463169425725937,
0.03055695630609989,
0.009045355021953583,
0.0661669597029686,
-0.03179500997066498,
-0.02230708859860897,
0.049544546753168106,
0.005042423028498888,
-0.1089903712272644,
0.019848400726914406,
0.018000071868300438,
0.06685265898704529,
0.08069398999214172,
0.014472385868430138,
0.017642850056290627,
-0.011267242953181267,
0.17770880460739136,
-0.049257516860961914,
-0.08440890163183212,
-0.10189788788557053,
0.18184520304203033,
0.018901357427239418,
-0.038215745240449905,
0.06638239324092865,
-0.07986452430486679,
0.01992497779428959,
0.17229841649532318,
0.13966749608516693,
-0.055623773485422134,
-0.001786411739885807,
0.017552820965647697,
-0.011184095405042171,
-0.02368215098977089,
0.11315252631902695,
0.11520113795995712,
0.08439955115318298,
-0.08064579963684082,
-0.039370473474264145,
-0.05711738020181656,
0.008972756564617157,
-0.02516217902302742,
0.04891929402947426,
-0.010161971673369408,
-0.00937666092067957,
-0.039461828768253326,
0.04008778929710388,
-0.03463826701045036,
-0.09724616259336472,
0.0303109809756279,
-0.20050495862960815,
-0.17133966088294983,
-0.02805136889219284,
0.07871469110250473,
-0.0091116763651371,
0.04042781516909599,
-0.012259450741112232,
0.017544575035572052,
0.11595313996076584,
-0.02706797793507576,
-0.06837541610002518,
-0.02114999108016491,
0.0586809404194355,
-0.0805828645825386,
0.18484774231910706,
-0.032798342406749725,
0.07169673591852188,
0.12363125383853912,
0.05966503545641899,
-0.12369316816329956,
0.06615492701530457,
0.05577096343040466,
-0.04686210677027702,
0.05160561576485634,
0.11309510469436646,
-0.026846271008253098,
0.04850611090660095,
0.0383341945707798,
-0.1295527219772339,
-0.002029344905167818,
-0.05233810096979141,
-0.04065756872296333,
-0.04649371653795242,
-0.028234630823135376,
-0.04111403226852417,
0.14175033569335938,
0.18065720796585083,
-0.056597404181957245,
-0.015401811338961124,
-0.05177503451704979,
0.010330215096473694,
0.053069695830345154,
0.09244292229413986,
-0.005192238837480545,
-0.2380513846874237,
0.007596343755722046,
0.03128780424594879,
0.01907315105199814,
-0.28368672728538513,
-0.07439219206571579,
-0.01805877313017845,
-0.061144180595874786,
-0.1204967275261879,
0.10541916638612747,
0.055893756449222565,
0.053338274359703064,
-0.047264158725738525,
0.0021007873583585024,
-0.08661775290966034,
0.1622275710105896,
-0.15295499563217163,
-0.09236615896224976
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | null | neimp/code-search-net-tokenizer | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | 2024-02-11T08:19:27+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
26,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.08389580249786377,
0.19830818474292755,
-0.0013316317927092314,
0.02313883788883686,
0.11396584659814835,
0.01961737498641014,
0.053626976907253265,
0.14538456499576569,
0.0060051376931369305,
0.10656800121068954,
0.066679947078228,
0.09131570905447006,
0.09678101539611816,
0.20042605698108673,
0.04371999576687813,
-0.17659740149974823,
0.010636410675942898,
-0.06930278241634369,
-0.010073255747556686,
0.11651819199323654,
0.141214057803154,
-0.10151198506355286,
0.07627976685762405,
-0.03319970890879631,
-0.02870541252195835,
-0.0070160143077373505,
-0.07769215852022171,
-0.05755697935819626,
0.07573003321886063,
0.054863471537828445,
0.04207949340343475,
-0.0008347301045432687,
0.08447454124689102,
-0.2674994468688965,
0.013753628358244896,
0.07452993094921112,
0.010659529827535152,
0.05990942195057869,
0.07833302766084671,
-0.04036625102162361,
0.12881849706172943,
-0.06320446729660034,
0.13035163283348083,
0.0906217098236084,
-0.0681561604142189,
-0.24378153681755066,
-0.08239314705133438,
0.06505522131919861,
0.12533815205097198,
0.07694927603006363,
-0.02823091857135296,
0.16422191262245178,
-0.07247646898031235,
0.019290022552013397,
0.09481704235076904,
-0.1151006743311882,
-0.060644298791885376,
0.08318385481834412,
0.14101974666118622,
0.10340547561645508,
-0.1255619376897812,
-0.012289565056562424,
0.04275871813297272,
0.045979104936122894,
0.07389909774065018,
0.011339850723743439,
0.1143413558602333,
0.05629947781562805,
-0.13526225090026855,
-0.05700986459851265,
0.14547574520111084,
0.023872992023825645,
-0.057064127177000046,
-0.2138909548521042,
-0.002902575535699725,
-0.07730814069509506,
-0.011685127392411232,
-0.06846728920936584,
0.0291305985301733,
-0.01194276288151741,
0.060226380825042725,
-0.0496203787624836,
-0.09797755628824234,
-0.046314824372529984,
0.1015089675784111,
0.054820988327264786,
0.011354796588420868,
-0.01489334274083376,
0.03576440364122391,
0.13432876765727997,
0.04213530570268631,
-0.10012737661600113,
-0.07065672427415848,
-0.0701170489192009,
-0.09620913118124008,
-0.03947552293539047,
0.04272124543786049,
0.020167991518974304,
0.042202774435281754,
0.2283228635787964,
0.024096308276057243,
0.05459817871451378,
0.029667891561985016,
0.0026177873369306326,
0.03211980313062668,
0.1073630079627037,
-0.041210614144802094,
-0.188126802444458,
-0.03292805701494217,
0.0931866466999054,
-0.009821015410125256,
-0.028658604249358177,
-0.033444397151470184,
0.035014089196920395,
0.08379437029361725,
0.11821532249450684,
0.08875755965709686,
-0.012828069739043713,
-0.037612639367580414,
-0.03493109717965126,
0.2115669697523117,
-0.14141373336315155,
0.045799970626831055,
-0.022097334265708923,
-0.018195297569036484,
-0.06905751675367355,
0.030103791505098343,
0.01831657998263836,
-0.003142025787383318,
0.06966056674718857,
-0.061253178864717484,
-0.05794486775994301,
-0.11518853157758713,
-0.045523155480623245,
0.04711875319480896,
-0.024105608463287354,
-0.024469668045639992,
-0.07765042781829834,
-0.11219723522663116,
-0.06417357176542282,
0.06612563133239746,
-0.04156653955578804,
-0.03974827378988266,
0.005308232270181179,
-0.07131324708461761,
0.008387917652726173,
0.008993842639029026,
0.12122467905282974,
-0.030063031241297722,
0.05833350867033005,
-0.002476902212947607,
0.05916252359747887,
0.10643328726291656,
0.03227818012237549,
-0.08492200076580048,
0.057466037571430206,
-0.20633617043495178,
0.08371785283088684,
-0.11420095711946487,
0.034276340156793594,
-0.17048145830631256,
-0.024183684960007668,
0.008447963744401932,
0.023597201332449913,
0.023726604878902435,
0.1338067352771759,
-0.2097422182559967,
-0.016196569427847862,
0.14133213460445404,
-0.09649793803691864,
-0.12422871589660645,
0.07990546524524689,
-0.03459475561976433,
0.1747698187828064,
0.038475677371025085,
-0.019652999937534332,
0.09909367561340332,
-0.15559963881969452,
-0.05852397903800011,
-0.026064254343509674,
-0.008927824907004833,
0.08823978155851364,
0.07542291283607483,
-0.05844951793551445,
0.02285866066813469,
0.02562655322253704,
-0.04727208614349365,
-0.0268824752420187,
-0.05256075784564018,
-0.10127434879541397,
-0.023140445351600647,
-0.09642518311738968,
0.026515161618590355,
0.000058677000197349116,
-0.07310442626476288,
-0.028560271486639977,
-0.17347893118858337,
-0.02563360333442688,
0.10103316605091095,
0.004820956848561764,
-0.007559072691947222,
-0.08540112525224686,
0.022149885073304176,
-0.05362366884946823,
-0.006164622958749533,
-0.16996455192565918,
-0.03558015450835228,
0.051895126700401306,
-0.14917676150798798,
0.015460150316357613,
-0.07327745854854584,
0.07047311216592789,
0.02098717913031578,
-0.05859505757689476,
-0.03108096309006214,
0.0007694467785768211,
0.004292082041501999,
-0.06229274719953537,
-0.1903683841228485,
-0.058886781334877014,
-0.041500482708215714,
0.15720732510089874,
-0.24841000139713287,
0.0300158578902483,
0.03247617185115814,
0.13185922801494598,
0.007058668415993452,
-0.06344027817249298,
0.02096918225288391,
-0.04676475748419762,
-0.050621338188648224,
-0.06898977607488632,
-0.009901339188218117,
-0.014539826661348343,
-0.031393732875585556,
0.012980648316442966,
-0.14970256388187408,
-0.060514215379953384,
0.09452559798955917,
0.11224991828203201,
-0.14555825293064117,
0.00204002158716321,
-0.0460561066865921,
-0.07002599537372589,
-0.07487804442644119,
-0.0761631652712822,
0.07739497721195221,
0.044650159776210785,
0.049250341951847076,
-0.06317461282014847,
-0.06234706938266754,
0.023210179060697556,
0.005524294450879097,
-0.019023682922124863,
0.0948529988527298,
0.074309803545475,
-0.09122881293296814,
0.07973480224609375,
0.08461450785398483,
0.04414684325456619,
0.086973637342453,
0.005991141777485609,
-0.11396963149309158,
-0.03062884695827961,
0.037754856050014496,
0.024159027263522148,
0.15351562201976776,
-0.08692087233066559,
0.030462130904197693,
0.052177220582962036,
-0.03854219615459442,
0.03157065063714981,
-0.0923321321606636,
0.025362705811858177,
0.021495236083865166,
-0.006555700208991766,
0.05864228308200836,
-0.018769768998026848,
-0.01403577346354723,
0.06336429715156555,
0.05677810311317444,
0.044270504266023636,
0.02595379762351513,
-0.02093072421848774,
-0.1278371512889862,
0.16537296772003174,
-0.09028079360723495,
-0.2540280222892761,
-0.17074446380138397,
0.015454737469553947,
0.03706491366028786,
-0.021728800609707832,
0.039588842540979385,
-0.06286025792360306,
-0.10237989574670792,
-0.09417891502380371,
0.0029635571409016848,
0.023925531655550003,
-0.058347854763269424,
-0.0817074254155159,
0.060779985040426254,
0.04047083482146263,
-0.13689260184764862,
0.0349188968539238,
0.06170675903558731,
-0.03042641654610634,
0.0018567070364952087,
0.07321398705244064,
0.12743599712848663,
0.14838241040706635,
-0.006730219814926386,
-0.012446845881640911,
0.035035960376262665,
0.229813352227211,
-0.1490442156791687,
0.10630457103252411,
0.14053207635879517,
-0.021705523133277893,
0.06635113060474396,
0.1461038440465927,
0.023231739178299904,
-0.07546708732843399,
0.04147516191005707,
0.04027445614337921,
-0.04228919371962547,
-0.2589097023010254,
-0.05694316700100899,
-0.00946022942662239,
-0.07043391466140747,
0.09718906134366989,
0.09238530695438385,
0.11972260475158691,
0.0337289460003376,
-0.05568677559494972,
-0.025771914049983025,
-0.003401360474526882,
0.114128477871418,
-0.027640055865049362,
-0.004564122296869755,
0.07965842634439468,
-0.05878787487745285,
0.011684526689350605,
0.09941446036100388,
0.019347423687577248,
0.17601320147514343,
0.02533329278230667,
0.10681075602769852,
0.06725578010082245,
0.09347675740718842,
-0.0015635732561349869,
0.034774236381053925,
0.05337131395936012,
0.022044572979211807,
0.010453542694449425,
-0.09408048540353775,
-0.012431944720447063,
0.13713060319423676,
0.019816776737570763,
0.009031654335558414,
0.008926562033593655,
-0.01010479498654604,
0.03131420537829399,
0.20501568913459778,
0.0009575071162544191,
-0.22537250816822052,
-0.09500737488269806,
0.059459153562784195,
-0.06931101530790329,
-0.143676295876503,
-0.02094252221286297,
0.030270220711827278,
-0.17292405664920807,
0.016790566965937614,
-0.0316389761865139,
0.09112390875816345,
-0.07145322859287262,
-0.028050832450389862,
0.06891903281211853,
0.07569212466478348,
-0.012108199298381805,
0.07973295450210571,
-0.19069278240203857,
0.12254468351602554,
0.03037673607468605,
0.08605273067951202,
-0.11708726733922958,
0.07849059253931046,
-0.0019813794642686844,
-0.014807495288550854,
0.17999744415283203,
-0.014062200672924519,
-0.0586031936109066,
-0.08878950774669647,
-0.08704045414924622,
-0.011727320961654186,
0.10361312329769135,
-0.09322915226221085,
0.09586969763040543,
-0.02775636687874794,
-0.03705112263560295,
0.012418309226632118,
-0.10469507426023483,
-0.1636953055858612,
-0.18679304420948029,
0.06244563311338425,
-0.07802703976631165,
0.012347841635346413,
-0.11227322369813919,
-0.06334327906370163,
-0.01575082167983055,
0.23160123825073242,
-0.16648635268211365,
-0.07049825042486191,
-0.1498587429523468,
-0.03997112438082695,
0.17463743686676025,
-0.042160745710134506,
0.06849376112222672,
-0.021383514627814293,
0.1873992383480072,
-0.008081548847258091,
-0.013158116489648819,
0.06569221615791321,
-0.09637628495693207,
-0.16879262030124664,
-0.05748843029141426,
0.14160962402820587,
0.10863390564918518,
0.05731578543782234,
-0.0038195757661014795,
0.013171887956559658,
-0.03383830562233925,
-0.09896382689476013,
0.013824623078107834,
0.13817466795444489,
0.0034514935687184334,
0.00682973163202405,
-0.03995988517999649,
-0.07027145475149155,
-0.05825701728463173,
-0.07912654429674149,
0.057147104293107986,
0.187900573015213,
-0.09512355923652649,
0.1602867990732193,
0.12431421875953674,
-0.06468851119279861,
-0.2306901067495346,
0.03996593505144119,
0.04701630026102066,
0.007666614837944508,
0.022401191294193268,
-0.19138796627521515,
0.09788824617862701,
0.0009011493530124426,
-0.06807263940572739,
0.14616990089416504,
-0.16564498841762543,
-0.1461436152458191,
0.08002161979675293,
0.025075770914554596,
-0.22560662031173706,
-0.14821304380893707,
-0.1037549376487732,
-0.03735695406794548,
-0.13707835972309113,
0.048581719398498535,
0.02614329755306244,
0.019834673032164574,
0.025222565978765488,
0.005338077899068594,
0.029657263308763504,
-0.07272187620401382,
0.1870686560869217,
-0.020297454670071602,
0.0072362530045211315,
-0.050640691071748734,
-0.04617878794670105,
0.09227550774812698,
-0.06150037795305252,
0.11741586774587631,
0.018679620698094368,
0.018796883523464203,
-0.1431548148393631,
-0.049209367483854294,
-0.060803934931755066,
0.04456847906112671,
-0.07284719496965408,
-0.09393193572759628,
-0.04137463867664337,
0.08888561278581619,
0.07211937010288239,
-0.032792408019304276,
-0.0027768779546022415,
-0.07569456845521927,
0.09405932575464249,
0.184477761387825,
0.17357055842876434,
0.009977072477340698,
-0.07020942866802216,
0.024555526673793793,
-0.042279548943042755,
0.03349342197179794,
-0.24652716517448425,
0.03456863760948181,
0.066053606569767,
0.03803660348057747,
0.08509242534637451,
-0.016836483031511307,
-0.1781480610370636,
-0.04086102172732353,
0.08498652279376984,
-0.06206206604838371,
-0.19876568019390106,
-0.02703288197517395,
0.08424776047468185,
-0.20383712649345398,
-0.032998621463775635,
0.041543323546648026,
-0.03834589570760727,
-0.02396267279982567,
-0.002415500348433852,
0.06396626681089401,
-0.008327016606926918,
0.12156640738248825,
0.06747189164161682,
0.10266115516424179,
-0.09284433722496033,
0.08920657634735107,
0.10416955500841141,
-0.09140542894601822,
0.03545991703867912,
0.10264154523611069,
-0.05670900270342827,
-0.04460543021559715,
0.033935222774744034,
0.05925208330154419,
-0.028357384726405144,
-0.06409841030836105,
-0.000502707262057811,
-0.0359574519097805,
0.04993389546871185,
0.08058220148086548,
0.036113787442445755,
-0.01202210783958435,
0.06544706225395203,
0.028145326301455498,
-0.11693570017814636,
0.10949387401342392,
0.04405685141682625,
0.04509059712290764,
-0.07182393968105316,
-0.012280966155230999,
0.015999672934412956,
0.032540347427129745,
-0.019734015688300133,
-0.014576527290046215,
-0.03146412968635559,
-0.007561005651950836,
-0.1553635597229004,
-0.02064543403685093,
-0.06516171246767044,
0.006067827809602022,
0.022207623347640038,
-0.03830232471227646,
-0.012014663778245449,
0.01381110493093729,
-0.07979435473680496,
-0.07571027427911758,
-0.01700955256819725,
0.08539021760225296,
-0.1381402313709259,
0.006627439055591822,
0.07182712107896805,
-0.10980239510536194,
0.07347989827394485,
-0.0048679932951927185,
0.017079560086131096,
0.010923396795988083,
-0.11654401570558548,
0.04386281594634056,
-0.005810429807752371,
0.01551580335944891,
0.022556742653250694,
-0.171111062169075,
0.011553828604519367,
-0.038553636521101,
-0.03114982508122921,
0.011926400475203991,
-0.025060230866074562,
-0.11875922232866287,
0.08676479011774063,
-0.028097305446863174,
-0.037512701004743576,
-0.03292486071586609,
0.06296087801456451,
0.08736220002174377,
-0.011740099638700485,
0.09667140990495682,
-0.025766119360923767,
0.04818311333656311,
-0.1756584197282791,
-0.01910574547946453,
-0.050167568027973175,
0.02537350542843342,
-0.01759655587375164,
-0.0070639788173139095,
0.055272240191698074,
-0.004191063344478607,
0.20991376042366028,
-0.03921036794781685,
0.1548677533864975,
0.05199402943253517,
-0.009925156831741333,
0.010884369723498821,
0.05032730847597122,
0.06423956155776978,
0.031145188957452774,
0.00853167474269867,
0.04660189896821976,
-0.004552975296974182,
-0.020357951521873474,
-0.13699717819690704,
0.02791593410074711,
0.16117429733276367,
0.061918217688798904,
0.0392887257039547,
0.03704594820737839,
-0.1422400325536728,
-0.09538721293210983,
0.10306388139724731,
-0.0331864058971405,
0.014331420883536339,
-0.08317886292934418,
0.17621558904647827,
0.12328410148620605,
-0.1574767529964447,
0.0577850341796875,
-0.07234696298837662,
-0.05066767707467079,
-0.1024852767586708,
-0.11832084506750107,
-0.06293155997991562,
-0.06027044355869293,
-0.004747506696730852,
-0.042489297688007355,
0.05734556168317795,
0.026751231402158737,
-0.003270963439717889,
-0.006759525276720524,
0.12665949761867523,
-0.0249644722789526,
-0.004145825747400522,
0.04152364656329155,
0.0326087586581707,
0.019319625571370125,
-0.05872373282909393,
0.017997145652770996,
0.018602589145302773,
0.022180357947945595,
0.06835069507360458,
0.0260987039655447,
-0.059317342936992645,
0.044286735355854034,
0.00319746439345181,
-0.11313364654779434,
0.018146557733416557,
-0.00002245741598017048,
-0.05020225793123245,
0.13557326793670654,
0.04076748713850975,
0.01548024732619524,
-0.029270920902490616,
0.24342355132102966,
-0.07199113070964813,
-0.08681939542293549,
-0.13965600728988647,
0.11511493474245071,
-0.023563209921121597,
0.03755274787545204,
0.016542524099349976,
-0.12659503519535065,
0.011511262506246567,
0.18531471490859985,
0.12824349105358124,
0.012459068559110165,
-0.007656481582671404,
0.05736639350652695,
-0.0007639875984750688,
-0.05985576659440994,
0.05051197111606598,
0.0664999932050705,
0.16097788512706757,
-0.09069112688302994,
0.0652846097946167,
-0.008405503816902637,
-0.0831485390663147,
-0.027498632669448853,
0.11705785244703293,
-0.022675158455967903,
0.02148384228348732,
-0.03778035193681717,
0.11204422265291214,
-0.052532415837049484,
-0.2719486355781555,
0.02952493168413639,
-0.09503202140331268,
-0.13993041217327118,
-0.02591860294342041,
0.041448429226875305,
-0.03349510580301285,
0.01577647216618061,
0.06254769116640091,
-0.045389387756586075,
0.18837277591228485,
0.025987716391682625,
-0.08679025620222092,
-0.07755549252033234,
0.05874146893620491,
-0.08695939928293228,
0.2789687216281891,
0.003863075515255332,
0.04782010242342949,
0.12108923494815826,
-0.03053574077785015,
-0.18664880096912384,
0.014769754372537136,
0.11989909410476685,
-0.09114406257867813,
0.07780203968286514,
0.18139931559562683,
-0.005561648402363062,
0.12649618089199066,
0.04705416411161423,
-0.03877115994691849,
0.03976387158036232,
-0.02721380814909935,
-0.03821522742509842,
-0.12209630757570267,
0.05661242455244064,
-0.0612691193819046,
0.15957388281822205,
0.1158948540687561,
-0.05964287370443344,
0.001120698289014399,
-0.06126941740512848,
0.06300627440214157,
0.014774397015571594,
0.12115653604269028,
0.018452486023306847,
-0.2023056596517563,
0.05087360367178917,
-0.03283824771642685,
0.08166342973709106,
-0.254973828792572,
-0.08186668157577515,
0.07622263580560684,
-0.019022729247808456,
-0.04275642707943916,
0.12311509251594543,
0.06101066991686821,
0.03676839917898178,
-0.03853875398635864,
-0.08537755906581879,
-0.01412904355674982,
0.15376435220241547,
-0.14123432338237762,
-0.029574336484074593
] |
null | null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
| {"library_name": "transformers", "tags": []} | text2text-generation | sinking8/text_summarizer_finetuned | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2024-02-11T08:27:08+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Downstream Use [optional]
### Out-of-Scope Use
## Bias, Risks, and Limitations
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
## Training Details
### Training Data
### Training Procedure
#### Preprocessing [optional]
#### Training Hyperparameters
- Training regime:
#### Speeds, Sizes, Times [optional]
## Evaluation
### Testing Data, Factors & Metrics
#### Testing Data
#### Factors
#### Metrics
### Results
#### Summary
## Model Examination [optional]
## Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type:
- Hours used:
- Cloud Provider:
- Compute Region:
- Carbon Emitted:
## Technical Specifications [optional]
### Model Architecture and Objective
### Compute Infrastructure
#### Hardware
#### Software
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Model Card Authors [optional]
## Model Card Contact
| [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
"TAGS\n#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Downstream Use [optional]",
"### Out-of-Scope Use",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.",
"## How to Get Started with the Model\n\nUse the code below to get started with the model.",
"## Training Details",
"### Training Data",
"### Training Procedure",
"#### Preprocessing [optional]",
"#### Training Hyperparameters\n\n- Training regime:",
"#### Speeds, Sizes, Times [optional]",
"## Evaluation",
"### Testing Data, Factors & Metrics",
"#### Testing Data",
"#### Factors",
"#### Metrics",
"### Results",
"#### Summary",
"## Model Examination [optional]",
"## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:",
"## Technical Specifications [optional]",
"### Model Architecture and Objective",
"### Compute Infrastructure",
"#### Hardware",
"#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Model Card Authors [optional]",
"## Model Card Contact"
] | [
58,
6,
3,
82,
28,
3,
4,
9,
9,
10,
42,
20,
3,
4,
5,
9,
11,
13,
3,
12,
5,
4,
5,
3,
4,
9,
53,
9,
8,
6,
3,
14,
8,
7,
9,
4
] | [
"passage: TAGS\n#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Downstream Use [optional]### Out-of-Scope Use## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.## How to Get Started with the Model\n\nUse the code below to get started with the model.## Training Details### Training Data### Training Procedure#### Preprocessing [optional]#### Training Hyperparameters\n\n- Training regime:#### Speeds, Sizes, Times [optional]## Evaluation### Testing Data, Factors & Metrics#### Testing Data#### Factors#### Metrics### Results#### Summary## Model Examination [optional]## Environmental Impact\n\n\n\nCarbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).\n\n- Hardware Type: \n- Hours used: \n- Cloud Provider: \n- Compute Region: \n- Carbon Emitted:## Technical Specifications [optional]### Model Architecture and Objective### Compute Infrastructure#### Hardware#### Software\n\n\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Model Card Authors [optional]## Model Card Contact"
] | [
-0.053328532725572586,
0.16120538115501404,
-0.005120371468365192,
0.022602224722504616,
0.09686747193336487,
0.013199392706155777,
0.07261143624782562,
0.11177206039428711,
-0.020693831145763397,
0.1128523200750351,
0.0323781855404377,
0.09778297692537308,
0.11381756514310837,
0.15530984103679657,
-0.0018252237932756543,
-0.23414164781570435,
0.051169246435165405,
-0.12603329122066498,
-0.039110470563173294,
0.11734651774168015,
0.14655858278274536,
-0.10434788465499878,
0.07780920714139938,
-0.029932111501693726,
-0.010786613449454308,
-0.030950399115681648,
-0.06109464541077614,
-0.04963193088769913,
0.05158040300011635,
0.07096312940120697,
0.06875279545783997,
0.009741154499351978,
0.09293358027935028,
-0.2676756680011749,
0.021060682833194733,
0.07436702400445938,
-0.0019205488497391343,
0.07644513249397278,
0.05394738167524338,
-0.07786445319652557,
0.08801496773958206,
-0.053122974932193756,
0.14802159368991852,
0.08166222274303436,
-0.09144649654626846,
-0.19256246089935303,
-0.08630277216434479,
0.10201671719551086,
0.17971307039260864,
0.050409309566020966,
-0.02338344417512417,
0.10295069962739944,
-0.08843041211366653,
0.012706292793154716,
0.059160783886909485,
-0.06515879184007645,
-0.05482804775238037,
0.0630323737859726,
0.08173035830259323,
0.0787791833281517,
-0.12468571215867996,
-0.018215585500001907,
0.011311499401926994,
0.00691694812849164,
0.08102929592132568,
0.022060219198465347,
0.14176861941814423,
0.03922285884618759,
-0.1292058527469635,
-0.047744158655405045,
0.10315844416618347,
0.04381343349814415,
-0.04969092458486557,
-0.24839195609092712,
-0.028692634776234627,
-0.03409173712134361,
-0.029329892247915268,
-0.041139665991067886,
0.04428756237030029,
-0.010770969092845917,
0.08322557806968689,
-0.008045176975429058,
-0.07979845255613327,
-0.03690612316131592,
0.06324487924575806,
0.05645342543721199,
0.024454401805996895,
-0.008984005078673363,
0.006743076257407665,
0.1175178587436676,
0.10636600106954575,
-0.12631633877754211,
-0.05289403349161148,
-0.06528059393167496,
-0.0853288322687149,
-0.04429693520069122,
0.03338160738348961,
0.04351643845438957,
0.04334709793329239,
0.24920088052749634,
0.011966975405812263,
0.05556565150618553,
0.03878911957144737,
0.011687099933624268,
0.06360286474227905,
0.11270952969789505,
-0.05845928564667702,
-0.09383665025234222,
-0.033332064747810364,
0.09301437437534332,
0.008503437042236328,
-0.0402098223567009,
-0.06047673895955086,
0.06078295037150383,
0.015703821554780006,
0.12211526930332184,
0.087046779692173,
0.002870776690542698,
-0.07195370644330978,
-0.06478150933980942,
0.19285908341407776,
-0.15949691832065582,
0.047871991991996765,
0.03357849270105362,
-0.040312062948942184,
-0.0005020854296162724,
0.01165273692458868,
0.023987481370568275,
-0.021567439660429955,
0.0924374982714653,
-0.05500924214720726,
-0.03761355206370354,
-0.10879732668399811,
-0.03591866046190262,
0.03197222575545311,
0.0022585385013371706,
-0.02967100404202938,
-0.033424828201532364,
-0.08920473605394363,
-0.0635172426700592,
0.09580977261066437,
-0.07413128018379211,
-0.05156254023313522,
-0.016345804557204247,
-0.0761859342455864,
0.026101797819137573,
0.01702207140624523,
0.08535456657409668,
-0.0213642455637455,
0.037230201065540314,
-0.05421315133571625,
0.06241346150636673,
0.10910454392433167,
0.0320611298084259,
-0.053984515368938446,
0.06094928830862045,
-0.2412392497062683,
0.10316064208745956,
-0.07156267017126083,
0.05108866095542908,
-0.15137021243572235,
-0.025331947952508926,
0.04665522649884224,
0.009590202011168003,
-0.011478574015200138,
0.14007656276226044,
-0.2198302298784256,
-0.029333066195249557,
0.1640782356262207,
-0.09730498492717743,
-0.08055570721626282,
0.059064920991659164,
-0.054139286279678345,
0.10999192297458649,
0.04003598168492317,
-0.023768696933984756,
0.06297750771045685,
-0.14250542223453522,
-0.0039275879971683025,
-0.041889119893312454,
-0.01720282807946205,
0.16010744869709015,
0.07506491243839264,
-0.06698185205459595,
0.077672079205513,
0.022212913259863853,
-0.023321649059653282,
-0.04393244534730911,
-0.022494852542877197,
-0.10826845467090607,
0.009565223939716816,
-0.06269361078739166,
0.02424052357673645,
-0.023944495245814323,
-0.0903024971485138,
-0.029575346037745476,
-0.1770460456609726,
-0.013402442447841167,
0.08679109811782837,
-0.010982494801282883,
-0.019886262714862823,
-0.11693590134382248,
0.012033592909574509,
0.032231178134679794,
0.0004325093177612871,
-0.13445010781288147,
-0.05658498778939247,
0.0273329745978117,
-0.16240260004997253,
0.031236927956342697,
-0.05114622414112091,
0.04928715154528618,
0.03406677767634392,
-0.03175085783004761,
-0.031348153948783875,
0.01572313904762268,
0.006510823033750057,
-0.013680041767656803,
-0.24737438559532166,
-0.02852414920926094,
-0.022412575781345367,
0.16979394853115082,
-0.2190135270357132,
0.04012007266283035,
0.07135825604200363,
0.15074580907821655,
0.006911954842507839,
-0.03669405356049538,
0.005606858059763908,
-0.0768459290266037,
-0.03284264728426933,
-0.0623927041888237,
-0.008401541970670223,
-0.03721899166703224,
-0.054593876004219055,
0.051287684589624405,
-0.16718235611915588,
-0.031153932213783264,
0.1028679683804512,
0.06780845671892166,
-0.13963541388511658,
-0.01705223321914673,
-0.04106766730546951,
-0.043112557381391525,
-0.05709490180015564,
-0.05539087578654289,
0.11148729920387268,
0.05757083371281624,
0.04828811436891556,
-0.06848311424255371,
-0.0756818875670433,
0.006132613401859999,
-0.0179264098405838,
-0.021222935989499092,
0.0928845927119255,
0.07583390921354294,
-0.12310270220041275,
0.09178637713193893,
0.10549022257328033,
0.0892157256603241,
0.10119049996137619,
-0.02137933485209942,
-0.08691582083702087,
-0.04892461374402046,
0.0229446180164814,
0.016364475712180138,
0.13983985781669617,
-0.016759416088461876,
0.05310053750872612,
0.04020100086927414,
-0.012910815887153149,
0.011883769184350967,
-0.09328193217515945,
0.02934250421822071,
0.03636814281344414,
-0.019501443952322006,
0.040251899510622025,
-0.03908125311136246,
0.020790016278624535,
0.08787564933300018,
0.04434992000460625,
0.03818633407354355,
0.013980780728161335,
-0.04370194673538208,
-0.11091572046279907,
0.17051653563976288,
-0.12536633014678955,
-0.239797443151474,
-0.14147889614105225,
0.001731917611323297,
0.041165996342897415,
-0.01159723661839962,
0.0031763319857418537,
-0.06770002096891403,
-0.11874829977750778,
-0.09346967190504074,
0.015001182444393635,
0.04228860139846802,
-0.080612413585186,
-0.05524664744734764,
0.05777253210544586,
0.040611669421195984,
-0.143319234251976,
0.020423002541065216,
0.04869217798113823,
-0.08989228308200836,
-0.00900039542466402,
0.08071441948413849,
0.06998268514871597,
0.17929090559482574,
0.009512054733932018,
-0.020932139828801155,
0.03292093798518181,
0.2157505750656128,
-0.13771237432956696,
0.11451084166765213,
0.14277678728103638,
-0.0911637470126152,
0.08293474465608597,
0.1991184800863266,
0.03884927183389664,
-0.10264625400304794,
0.03326369449496269,
0.022328944876790047,
-0.028676386922597885,
-0.2503291964530945,
-0.06918580830097198,
0.0007976540364325047,
-0.05238448083400726,
0.07527847588062286,
0.08888168632984161,
0.09494108706712723,
0.01729334332048893,
-0.09416709095239639,
-0.08025584369897842,
0.04901478812098503,
0.10409125685691833,
0.010409193113446236,
-0.01156378723680973,
0.09060908854007721,
-0.03323452174663544,
0.01843860000371933,
0.09313460439443588,
0.004041523206979036,
0.17060963809490204,
0.05550962686538696,
0.18336638808250427,
0.07643263041973114,
0.0721396952867508,
0.015671607106924057,
0.013079277239739895,
0.02304760180413723,
0.021578695625066757,
-0.0033059304114431143,
-0.0851421132683754,
-0.009511260315775871,
0.11862117052078247,
0.06801546365022659,
0.020754681900143623,
0.009507957845926285,
-0.033934496343135834,
0.08064714074134827,
0.17465052008628845,
-0.0009437129483558238,
-0.1870066076517105,
-0.06896740943193436,
0.08026526123285294,
-0.08972865343093872,
-0.10345284640789032,
-0.02900044620037079,
0.0354950949549675,
-0.17372116446495056,
0.02448408491909504,
-0.018045885488390923,
0.11108683049678802,
-0.1356782615184784,
-0.01890929788351059,
0.06319493800401688,
0.07008420675992966,
-0.0016097982879728079,
0.06208989396691322,
-0.16155508160591125,
0.10791012644767761,
0.01390943955630064,
0.06503470987081528,
-0.09786296635866165,
0.10111832618713379,
-0.006267238408327103,
-0.007413685787469149,
0.14043578505516052,
0.009255880489945412,
-0.07051325589418411,
-0.08343593031167984,
-0.0979004055261612,
-0.010649190284311771,
0.12877127528190613,
-0.14879846572875977,
0.08456916362047195,
-0.0322830006480217,
-0.04405250772833824,
0.005208021495491266,
-0.10768675804138184,
-0.12857580184936523,
-0.18887875974178314,
0.05537694692611694,
-0.13356289267539978,
0.033175256103277206,
-0.1055491715669632,
-0.0408647358417511,
-0.02885887771844864,
0.19630752503871918,
-0.22321896255016327,
-0.0670507624745369,
-0.15318840742111206,
-0.09096445143222809,
0.14798617362976074,
-0.049908362329006195,
0.08374498039484024,
-0.005065108183771372,
0.18742504715919495,
0.01894373446702957,
-0.024415504187345505,
0.1011786088347435,
-0.09638315439224243,
-0.19627197086811066,
-0.08534666895866394,
0.15457913279533386,
0.13537167012691498,
0.0351712740957737,
-0.004617651924490929,
0.03167666867375374,
-0.0189940445125103,
-0.12101218104362488,
0.022920187562704086,
0.17696480453014374,
0.07036592066287994,
0.024736741557717323,
-0.02639835514128208,
-0.11453131586313248,
-0.06600044667720795,
-0.032452553510665894,
0.02982977218925953,
0.18294402956962585,
-0.07586611062288284,
0.18679921329021454,
0.13732017576694489,
-0.05770440772175789,
-0.1956426501274109,
0.01923983357846737,
0.04058924317359924,
0.00837375782430172,
0.032165057957172394,
-0.20239581167697906,
0.08806682378053665,
0.0007347199134528637,
-0.05074144899845123,
0.13624143600463867,
-0.17552010715007782,
-0.15046143531799316,
0.06929060816764832,
0.03642011433839798,
-0.19279520213603973,
-0.12030941992998123,
-0.08865538984537125,
-0.05107492581009865,
-0.17776648700237274,
0.10758756101131439,
0.02193085290491581,
0.00676411809399724,
0.033654287457466125,
0.026140762493014336,
0.014790141955018044,
-0.0396585576236248,
0.19431912899017334,
-0.02348872646689415,
0.030807901173830032,
-0.08293910324573517,
-0.07001609355211258,
0.05941145867109299,
-0.05705835670232773,
0.0775861069560051,
-0.022215960547327995,
0.013414059765636921,
-0.10643109679222107,
-0.04425564035773277,
-0.03175993636250496,
0.015691282227635384,
-0.09722420573234558,
-0.08909335732460022,
-0.050057362765073776,
0.09262266010046005,
0.0974174216389656,
-0.035089656710624695,
-0.03564268350601196,
-0.07118509709835052,
0.039714183658361435,
0.18831974267959595,
0.17605267465114594,
0.046182651072740555,
-0.08030564337968826,
-0.004098092205822468,
-0.011694483458995819,
0.042484745383262634,
-0.21906526386737823,
0.062426332384347916,
0.05058585852384567,
0.014059843495488167,
0.1173645630478859,
-0.01779606007039547,
-0.15810294449329376,
-0.06761486083269119,
0.05993710458278656,
-0.06326820701360703,
-0.19225671887397766,
0.0032602818682789803,
0.055388111621141434,
-0.16711848974227905,
-0.04538320377469063,
0.0430813767015934,
-0.005750913172960281,
-0.039257556200027466,
0.01613711006939411,
0.08359149098396301,
0.0031580389477312565,
0.07040093839168549,
0.05520293489098549,
0.086640864610672,
-0.10250966250896454,
0.07937785238027573,
0.08386688679456711,
-0.08347215503454208,
0.028158824890851974,
0.09330378472805023,
-0.06144890934228897,
-0.029910072684288025,
0.032212331891059875,
0.08255140483379364,
0.012964491732418537,
-0.04401125758886337,
0.008184057660400867,
-0.10146338492631912,
0.0627170279622078,
0.09755739569664001,
0.03206513822078705,
0.011901181191205978,
0.03383762761950493,
0.04645882546901703,
-0.07481352984905243,
0.11842621862888336,
0.025973208248615265,
0.01822328381240368,
-0.04273592680692673,
-0.04516541585326195,
0.027133917436003685,
-0.02340707741677761,
-0.007566304877400398,
-0.03583317995071411,
-0.06988023966550827,
-0.01722576655447483,
-0.16493180394172668,
-0.01076561864465475,
-0.044063083827495575,
0.008020744659006596,
0.026847293600440025,
-0.0369400717318058,
0.008594665676355362,
0.009077225811779499,
-0.07577309012413025,
-0.06240518018603325,
-0.02245018258690834,
0.0914878100156784,
-0.16343435645103455,
0.023352261632680893,
0.08310231566429138,
-0.12098916620016098,
0.09322582185268402,
0.018653366714715958,
-0.0019369579385966063,
0.02680385299026966,
-0.15561461448669434,
0.0368269607424736,
-0.027320701628923416,
0.014671673998236656,
0.045705173164606094,
-0.21818207204341888,
-0.0014451020397245884,
-0.03558654710650444,
-0.059982262551784515,
-0.010693925432860851,
-0.037350837141275406,
-0.11245633661746979,
0.10088492184877396,
0.012412267737090588,
-0.08672942966222763,
-0.03157110512256622,
0.03652326017618179,
0.08053763210773468,
-0.02631879225373268,
0.15205731987953186,
-0.0010786735219880939,
0.07447176426649094,
-0.1738860309123993,
-0.0210786834359169,
-0.0090115275233984,
0.02177848480641842,
-0.016872623935341835,
-0.01564885675907135,
0.042430613189935684,
-0.026671668514609337,
0.18584245443344116,
-0.027355844154953957,
0.03733034059405327,
0.06316441297531128,
0.01770097203552723,
-0.021354418247938156,
0.10755398869514465,
0.06012963131070137,
0.02173144742846489,
0.019801700487732887,
0.0075409491546452045,
-0.041807159781455994,
-0.018543899059295654,
-0.19347810745239258,
0.07164526730775833,
0.14044208824634552,
0.08769161999225616,
-0.012164209969341755,
0.08067302405834198,
-0.10084949433803558,
-0.11743459850549698,
0.11121641099452972,
-0.059808436781167984,
-0.0022669173777103424,
-0.06652101874351501,
0.13155525922775269,
0.14582572877407074,
-0.19254228472709656,
0.07050827890634537,
-0.06511960923671722,
-0.05269601568579674,
-0.11906112730503082,
-0.1953776627779007,
-0.05703132599592209,
-0.054343048483133316,
-0.015079263597726822,
-0.05059242993593216,
0.07498416304588318,
0.05622640252113342,
0.010858895257115364,
0.0015552249969914556,
0.06971994787454605,
-0.019759170711040497,
0.001521410304121673,
0.032095473259687424,
0.06417544931173325,
0.014362066984176636,
-0.03133942559361458,
0.018592869862914085,
-0.008470231667160988,
0.03991629183292389,
0.0633486732840538,
0.04155107960104942,
-0.028110865503549576,
0.01659207232296467,
-0.0337030366063118,
-0.10854189842939377,
0.04278707876801491,
-0.028698457404971123,
-0.08063279837369919,
0.13984808325767517,
0.025403661653399467,
0.009562181308865547,
-0.022226108238101006,
0.241981640458107,
-0.07480388879776001,
-0.09265431761741638,
-0.14692139625549316,
0.1055137887597084,
-0.04348868504166603,
0.06415078788995743,
0.045384783297777176,
-0.10421041399240494,
0.012057800777256489,
0.12658540904521942,
0.1625804305076599,
-0.0438871793448925,
0.019560009241104126,
0.03037482313811779,
0.00398933095857501,
-0.03853052854537964,
0.05252939090132713,
0.06827457249164581,
0.14848913252353668,
-0.050116557627916336,
0.09223522990942001,
0.0050886585377156734,
-0.09908851981163025,
-0.034064266830682755,
0.11810369789600372,
-0.019035303965210915,
0.019260596483945847,
-0.05601469427347183,
0.11788773536682129,
-0.06368034332990646,
-0.233087420463562,
0.06406685709953308,
-0.07426205277442932,
-0.14131881296634674,
-0.024826664477586746,
0.07676053047180176,
-0.014309047721326351,
0.027850469574332237,
0.0722186341881752,
-0.07654546946287155,
0.19937579333782196,
0.03671684116125107,
-0.058611851185560226,
-0.05623113736510277,
0.07896319031715393,
-0.11419995129108429,
0.27488458156585693,
0.015893742442131042,
0.045155949890613556,
0.1038452610373497,
-0.013412448577582836,
-0.13435201346874237,
0.01833420805633068,
0.09638454020023346,
-0.08846497535705566,
0.04018587991595268,
0.20595665276050568,
-0.0028567397966980934,
0.11962885409593582,
0.07707620412111282,
-0.08087631314992905,
0.049051105976104736,
-0.09828304499387741,
-0.07230360060930252,
-0.08931835740804672,
0.09120666980743408,
-0.07232820242643356,
0.14308606088161469,
0.1311190128326416,
-0.05265164002776146,
0.00968363881111145,
-0.029376711696386337,
0.045510269701480865,
0.004632700700312853,
0.10403459519147873,
0.008749093860387802,
-0.1797543615102768,
0.02403045818209648,
0.01841445453464985,
0.10992073267698288,
-0.1701374351978302,
-0.09734909981489182,
0.043629229068756104,
-0.0012522460892796516,
-0.06121290475130081,
0.1290796846151352,
0.05957380682229996,
0.05011506378650665,
-0.043520737439394,
-0.0211784765124321,
-0.008504665456712246,
0.14072857797145844,
-0.10404830425977707,
-0.00016830587992444634
] |
null | null | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# emotion_recognition2
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4483
- Accuracy: 0.575
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 40 | 1.4497 | 0.5188 |
| No log | 2.0 | 80 | 1.5957 | 0.5062 |
| No log | 3.0 | 120 | 1.4758 | 0.5625 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
| {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "emotion_recognition2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.575, "name": "Accuracy"}]}]}]} | image-classification | Dricz/emotion_recognition2 | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2024-02-11T08:27:25+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| emotion\_recognition2
=====================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4483
* Accuracy: 0.575
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu121
* Datasets 2.17.0
* Tokenizers 0.15.1
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
"TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
86,
98,
4,
33
] | [
"passage: TAGS\n#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #dataset-imagefolder #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu121\n* Datasets 2.17.0\n* Tokenizers 0.15.1"
] | [
-0.11703837662935257,
0.13337396085262299,
-0.0026314614806324244,
0.12070085108280182,
0.14108110964298248,
0.004635666497051716,
0.13976868987083435,
0.13915185630321503,
-0.07275068759918213,
0.07987997680902481,
0.14880694448947906,
0.13123802840709686,
0.030614977702498436,
0.186843603849411,
-0.049425795674324036,
-0.22279761731624603,
0.02685735560953617,
0.04665452614426613,
-0.048514917492866516,
0.12098179757595062,
0.08884505927562714,
-0.13715827465057373,
0.11813674122095108,
0.025373730808496475,
-0.20166562497615814,
-0.007906285114586353,
0.028533801436424255,
-0.05778995901346207,
0.11590585857629776,
0.03695005550980568,
0.09109177440404892,
0.029183940961956978,
0.05279802158474922,
-0.15043242275714874,
0.010382969863712788,
0.07545940577983856,
-0.008873723447322845,
0.09604368358850479,
0.05648350343108177,
0.011809377931058407,
0.011960681527853012,
-0.09294059872627258,
0.04073645547032356,
0.02618785761296749,
-0.1126071959733963,
-0.23252299427986145,
-0.08630016446113586,
0.05883171036839485,
0.07816880941390991,
0.07029051333665848,
-0.002089416841045022,
0.14405477046966553,
-0.00737989554181695,
0.09751922637224197,
0.2301016002893448,
-0.27348390221595764,
-0.07743311673402786,
0.03915984183549881,
0.018593033775687218,
0.07816129922866821,
-0.10029579699039459,
0.013005148619413376,
0.05876810848712921,
0.015363712795078754,
0.15396012365818024,
-0.005486635956913233,
-0.012113339267671108,
-0.02576831355690956,
-0.12579193711280823,
-0.06398480385541916,
0.19302216172218323,
0.08900821954011917,
-0.04782756417989731,
-0.08186109364032745,
-0.07897835224866867,
-0.13923798501491547,
-0.045598313212394714,
-0.01130685769021511,
0.05696497857570648,
-0.03428177163004875,
-0.06387034803628922,
-0.03622199594974518,
-0.09861935675144196,
-0.0694071352481842,
-0.01417485624551773,
0.09747761487960815,
0.05392841622233391,
0.013733952306210995,
-0.01965475268661976,
0.08202629536390305,
-0.03903357684612274,
-0.14419008791446686,
-0.008073186501860619,
0.016317779198288918,
0.025416046380996704,
-0.031292639672756195,
-0.02456621825695038,
-0.11346811056137085,
0.021297236904501915,
0.10916416347026825,
-0.06965523958206177,
0.05674217268824577,
-0.020271146669983864,
0.05181616172194481,
-0.11094168573617935,
0.19113050401210785,
-0.04913107678294182,
0.016911955550312996,
0.040070004761219025,
0.10395632684230804,
0.05103425309062004,
-0.0021235921885818243,
-0.10635765641927719,
0.018188273534178734,
0.12026511132717133,
0.007220359053462744,
-0.034489840269088745,
0.08142359554767609,
-0.06266428530216217,
-0.0302606038749218,
0.07919827848672867,
-0.08607569336891174,
0.026211019605398178,
-0.00618899567052722,
-0.05342717096209526,
-0.05631585419178009,
0.046617813408374786,
-0.011000683531165123,
-0.013043655082583427,
0.041490864008665085,
-0.10070876032114029,
0.012835947796702385,
-0.06701703369617462,
-0.10771821439266205,
0.013119104318320751,
-0.11608368158340454,
0.014757844619452953,
-0.12414803355932236,
-0.1380673348903656,
-0.012368048541247845,
0.06022344157099724,
-0.03041667491197586,
-0.05152950808405876,
-0.041196927428245544,
-0.08038634061813354,
0.026152383536100388,
0.004225734621286392,
0.04650184512138367,
-0.05763401836156845,
0.08761324733495712,
0.04544827342033386,
0.07616794109344482,
-0.020994113758206367,
0.045899562537670135,
-0.08738765865564346,
0.05809153988957405,
-0.2045249044895172,
0.03679561987519264,
-0.05837831273674965,
0.08663726598024368,
-0.11987154185771942,
-0.08720742911100388,
0.0016014266293495893,
-0.02086605131626129,
0.06450971961021423,
0.10771549493074417,
-0.13847248256206512,
-0.05708669498562813,
0.1700592339038849,
-0.10256218165159225,
-0.15680526196956635,
0.1140514686703682,
-0.029748473316431046,
0.02859514206647873,
0.05555932968854904,
0.19654671847820282,
0.07996563613414764,
-0.11017503589391708,
-0.0066634067334234715,
-0.03167468309402466,
0.03426699712872505,
-0.053370796144008636,
0.07663652300834656,
-0.0009144639479927719,
-0.011858968064188957,
0.022494114935398102,
-0.09691387414932251,
0.06316110491752625,
-0.07301964610815048,
-0.08512462675571442,
-0.06534026563167572,
-0.08831242471933365,
0.042954590171575546,
0.058359675109386444,
0.0645759254693985,
-0.10121571272611618,
-0.09006785601377487,
0.027817653492093086,
0.08084576576948166,
-0.09410694986581802,
0.018196698278188705,
-0.08191899210214615,
0.1126723513007164,
-0.1093708872795105,
0.0004419925680849701,
-0.13329780101776123,
-0.03131695091724396,
0.04985025152564049,
-0.06135560944676399,
-0.009030998684465885,
-0.03844417631626129,
0.07354863733053207,
0.06243178993463516,
-0.06397026032209396,
-0.07401686161756516,
-0.039857376366853714,
-0.002541468245908618,
-0.09822724014520645,
-0.1930789202451706,
-0.02491181716322899,
-0.027390971779823303,
0.1042720228433609,
-0.2170361429452896,
0.04140092059969902,
0.051480215042829514,
0.10060609132051468,
0.059354208409786224,
-0.031083568930625916,
0.003881290787830949,
0.018517998978495598,
-0.040115389972925186,
-0.08943285048007965,
0.06251829862594604,
0.01465153694152832,
-0.0682663545012474,
0.007539455778896809,
-0.1002621054649353,
0.17529559135437012,
0.12993976473808289,
-0.034416016191244125,
-0.06298492103815079,
-0.00528334453701973,
-0.04372486099600792,
-0.035125672817230225,
-0.035741571336984634,
0.00796236377209425,
0.0818292573094368,
-0.009152678772807121,
0.16176961362361908,
-0.10541821271181107,
-0.02614610828459263,
0.05752480775117874,
-0.030310874804854393,
-0.03932845965027809,
0.0879305824637413,
0.0689462199807167,
-0.13795559108257294,
0.14652696251869202,
0.16725656390190125,
-0.06790488958358765,
0.12538579106330872,
-0.04648170992732048,
-0.061255231499671936,
-0.02388312853872776,
0.0413455031812191,
0.033161431550979614,
0.12936992943286896,
-0.11827138066291809,
-0.012466629967093468,
0.02318766713142395,
0.0034411177039146423,
-0.007749029900878668,
-0.20055235922336578,
-0.008930030278861523,
0.03852272033691406,
-0.06102276220917702,
0.027995122596621513,
-0.0059851473197340965,
-0.021226882934570312,
0.08483211696147919,
0.008784144185483456,
-0.04312850162386894,
0.047620926052331924,
0.011016378179192543,
-0.070640929043293,
0.1946350783109665,
-0.08425688743591309,
-0.21688829362392426,
-0.13184000551700592,
-0.02259995974600315,
-0.08116496354341507,
0.021704653277993202,
0.05834820121526718,
-0.0939188152551651,
-0.05737043544650078,
-0.1059584692120552,
-0.014644067734479904,
0.029605969786643982,
0.039716124534606934,
0.04239022359251976,
-0.0021739343646913767,
0.13141466677188873,
-0.09900851547718048,
-0.007951428182423115,
-0.009906016290187836,
-0.024484282359480858,
0.0484999381005764,
0.019389836117625237,
0.12063866853713989,
0.08635938912630081,
-0.026420699432492256,
0.034378863871097565,
-0.02176588401198387,
0.24209915101528168,
-0.07170218974351883,
-0.002313279313966632,
0.15088510513305664,
0.01899421401321888,
0.0680055096745491,
0.1311551034450531,
0.0380869098007679,
-0.1028253585100174,
0.00868341512978077,
0.02154296450316906,
-0.026541180908679962,
-0.18667645752429962,
-0.017275797203183174,
-0.039236802607774734,
-0.002954996656626463,
0.15129339694976807,
0.055661555379629135,
0.05976345017552376,
0.09332019090652466,
0.0007176376529969275,
0.08904192596673965,
-0.003959463443607092,
0.08775415271520615,
0.10959029197692871,
0.04645396023988724,
0.1098446249961853,
-0.04363267868757248,
-0.028399335220456123,
0.03291943296790123,
0.01738213188946247,
0.2241400182247162,
-0.00003631914296420291,
0.17261895537376404,
0.04836900904774666,
0.1900348961353302,
0.01713091880083084,
0.05570961907505989,
-0.021902672946453094,
-0.0266709141433239,
-0.009243522770702839,
-0.054415035992860794,
-0.020340489223599434,
0.035104844719171524,
-0.04811236634850502,
0.06586732715368271,
-0.09328407049179077,
0.04222632199525833,
0.0642194002866745,
0.26483941078186035,
0.03752564638853073,
-0.3791341185569763,
-0.0939597487449646,
-0.0049210237339138985,
-0.013265467248857021,
-0.062238745391368866,
0.002539258450269699,
0.14532248675823212,
-0.06168266385793686,
0.06027646362781525,
-0.1037464290857315,
0.08121387660503387,
-0.050712015479803085,
0.021209081634879112,
0.07831300795078278,
0.08860913664102554,
0.008514128625392914,
0.05597322806715965,
-0.2486269623041153,
0.2566283643245697,
0.01536697056144476,
0.06393660604953766,
-0.046393249183893204,
0.013083992525935173,
0.035263027995824814,
0.10594192892313004,
0.10975627601146698,
-0.005398198962211609,
-0.013294120319187641,
-0.1774248480796814,
-0.08987019956111908,
0.006320901680737734,
0.07202734053134918,
-0.04535548761487007,
0.08152179419994354,
-0.03076917491853237,
-0.023336147889494896,
0.05034853145480156,
-0.0023333407007157803,
-0.09037072211503983,
-0.0938434824347496,
-0.007769833784550428,
0.042169827967882156,
0.014453562907874584,
-0.09538816660642624,
-0.09747780859470367,
-0.1048489362001419,
0.1335330307483673,
-0.01618613675236702,
-0.04101753234863281,
-0.1197008490562439,
0.08539466559886932,
0.05789906159043312,
-0.09232202917337418,
0.07979302108287811,
-0.028646942228078842,
0.13591405749320984,
0.029946301132440567,
-0.06286513060331345,
0.108878493309021,
-0.060614846646785736,
-0.17376556992530823,
-0.04674529656767845,
0.10528187453746796,
-0.018827708438038826,
0.024799806997179985,
0.0014270436950027943,
0.027369540184736252,
-0.009907948784530163,
-0.0595303513109684,
0.058219511061906815,
0.013695329427719116,
0.05881156399846077,
-0.012535660527646542,
-0.02047077752649784,
0.0071998704224824905,
-0.06425852328538895,
-0.02980400249361992,
0.13548409938812256,
0.24640130996704102,
-0.09706414490938187,
0.00592033751308918,
0.01898462325334549,
-0.05172053724527359,
-0.19607172906398773,
0.04743197187781334,
0.06572196632623672,
0.0012101199245080352,
0.03240214288234711,
-0.15322856605052948,
0.0722271278500557,
0.08123486489057541,
-0.030632134526968002,
0.09312167763710022,
-0.26652154326438904,
-0.13317318260669708,
0.07914533466100693,
0.18482905626296997,
0.06634730100631714,
-0.14518675208091736,
-0.05395825579762459,
-0.011692943051457405,
-0.09194391965866089,
0.09448184818029404,
-0.05885150656104088,
0.10514575242996216,
-0.02882414683699608,
0.0015335388015955687,
0.00582722807303071,
-0.05773221328854561,
0.13027338683605194,
-0.03471249341964722,
0.10697836428880692,
-0.057575780898332596,
-0.009273887611925602,
0.07730783522129059,
-0.07756908237934113,
0.06389493495225906,
-0.09080985933542252,
0.06284743547439575,
-0.06249602884054184,
-0.01630096137523651,
-0.07085379213094711,
0.032720524817705154,
-0.018907397985458374,
-0.025998355820775032,
-0.05104759335517883,
0.02411961741745472,
0.05202407017350197,
-0.0008917939267121255,
0.19917307794094086,
0.049436453729867935,
0.08815135806798935,
0.13946491479873657,
0.04505709558725357,
-0.07640576362609863,
-0.09965261816978455,
-0.02794247306883335,
-0.028156407177448273,
0.08631274104118347,
-0.1821335107088089,
0.050633545964956284,
0.09562115371227264,
0.008786720223724842,
0.1437925398349762,
0.046659890562295914,
-0.033027566969394684,
0.019468659535050392,
0.0716174766421318,
-0.15473493933677673,
-0.16070124506950378,
-0.03147938475012779,
-0.01959877274930477,
-0.11593525856733322,
0.06277275830507278,
0.11234544962644577,
-0.08436606824398041,
0.003143449081107974,
-0.008115489035844803,
0.016445670276880264,
-0.002922833664342761,
0.1620379239320755,
0.08044344931840897,
0.04440523684024811,
-0.09107036888599396,
0.09909168630838394,
0.05257095769047737,
-0.10333825647830963,
0.022850388661026955,
0.026029350236058235,
-0.10419294983148575,
-0.03795844316482544,
0.06664425134658813,
0.14432570338249207,
0.00006186454265844077,
-0.05099732056260109,
-0.145272359251976,
-0.09429456293582916,
0.05694856867194176,
0.12373209744691849,
0.09292376786470413,
0.015423471108078957,
-0.01091066561639309,
-0.00009720020898384973,
-0.10389916598796844,
0.11914563179016113,
0.03167761489748955,
0.09743194282054901,
-0.21961945295333862,
0.05785536766052246,
0.018080802634358406,
0.03249455615878105,
-0.019513674080371857,
0.029373042285442352,
-0.09893912822008133,
-0.015827111899852753,
-0.062337394803762436,
0.042512133717536926,
-0.03638628125190735,
0.005922649521380663,
-0.006159887183457613,
-0.06887022405862808,
-0.0612044595181942,
0.04134524613618851,
-0.10006293654441833,
-0.04592924565076828,
0.036102935671806335,
0.07028134912252426,
-0.1017250046133995,
-0.02997429668903351,
0.025206606835126877,
-0.08065185695886612,
0.08027215301990509,
0.013028341345489025,
-0.0004450915439520031,
0.02310003526508808,
-0.10084504634141922,
0.010026423260569572,
0.08489544689655304,
0.0024503201711922884,
0.02952449768781662,
-0.10438298434019089,
0.0064419936388731,
-0.0005933578358963132,
0.001203361782245338,
-0.007561885751783848,
0.10678712278604507,
-0.13309365510940552,
-0.024426471441984177,
-0.03807325288653374,
-0.032700758427381516,
-0.05843300372362137,
0.06268969178199768,
0.08548111468553543,
-0.002174717141315341,
0.20140309631824493,
-0.08715260028839111,
0.00044914960744790733,
-0.22340458631515503,
0.004364042077213526,
-0.004667307715862989,
-0.13584661483764648,
-0.12687353789806366,
-0.02751031517982483,
0.05282249674201012,
-0.07272692024707794,
0.09648748487234116,
0.015602112747728825,
0.005482446402311325,
0.03584155812859535,
0.002860749838873744,
-0.00020455298363231122,
0.026773367077112198,
0.18494276702404022,
-0.008662721142172813,
-0.021410565823316574,
0.07181929796934128,
0.018126700073480606,
0.11767108738422394,
0.08362764120101929,
0.100187748670578,
0.16270700097084045,
-0.043137241154909134,
0.1047297790646553,
0.05020562559366226,
-0.02201724424958229,
-0.17260314524173737,
0.099579818546772,
-0.07432375103235245,
0.1438605636358261,
-0.01329872664064169,
0.16352100670337677,
0.12169411033391953,
-0.1587391346693039,
0.026834789663553238,
-0.0289441104978323,
-0.07310780137777328,
-0.07127818465232849,
-0.14489620923995972,
-0.11695800721645355,
-0.18523749709129333,
0.014706979505717754,
-0.09824713319540024,
0.006036174017935991,
0.07335814088582993,
-0.008756529539823532,
-0.02278182841837406,
0.20525194704532623,
0.05062941461801529,
-0.0015471938531845808,
0.06982497125864029,
0.0004000072949565947,
-0.06756534427404404,
-0.058266229927539825,
-0.08429080992937088,
0.03729024529457092,
-0.008315094746649265,
0.033800289034843445,
-0.029064588248729706,
-0.006984272971749306,
0.049001943320035934,
-0.0008032873156480491,
-0.1114795133471489,
0.017399339005351067,
0.015422964468598366,
0.0104808509349823,
0.004319962579756975,
0.005276380572468042,
0.006768873892724514,
-0.009149119257926941,
0.18285971879959106,
-0.054600365459918976,
-0.007288629654794931,
-0.118613101541996,
0.12515847384929657,
0.027603721246123314,
-0.015562397427856922,
0.028825828805565834,
-0.07919397950172424,
0.025804884731769562,
0.21893082559108734,
0.1471487581729889,
-0.019513681530952454,
-0.0012397143291309476,
-0.008512388914823532,
-0.020078860223293304,
-0.02962370589375496,
0.09381722658872604,
0.093077652156353,
-0.045276205986738205,
-0.055423036217689514,
-0.02287806011736393,
-0.04775697737932205,
-0.01556673739105463,
-0.037331387400627136,
0.03700118884444237,
0.018096478655934334,
0.01576288789510727,
-0.06422943621873856,
0.042788662016391754,
0.01872457005083561,
-0.06986422836780548,
0.08822456747293472,
-0.195314422249794,
-0.13894817233085632,
-0.033102765679359436,
0.10025840252637863,
-0.006814622785896063,
0.03010626882314682,
-0.021688636392354965,
0.015948232263326645,
0.06887423992156982,
-0.024077434092760086,
-0.08256082236766815,
-0.09813321381807327,
0.05134633928537369,
-0.13101309537887573,
0.24609622359275818,
-0.032189205288887024,
0.006966001819819212,
0.1118864119052887,
0.018069008365273476,
-0.11937997490167618,
0.051981233060359955,
0.02522706799209118,
-0.03701399639248848,
0.025646666064858437,
0.11088280379772186,
-0.020911220461130142,
0.10904537886381149,
0.034553103148937225,
-0.08759990334510803,
-0.01746610552072525,
-0.054005686193704605,
-0.04080064594745636,
-0.055988289415836334,
-0.024216534569859505,
-0.06890667229890823,
0.12402335554361343,
0.17284543812274933,
-0.04252352565526962,
-0.02652166597545147,
-0.06382237374782562,
0.03748849779367447,
0.09080575406551361,
0.016650447621941566,
-0.013948991894721985,
-0.22873233258724213,
0.017291316762566566,
0.022657809779047966,
-0.0036899205297231674,
-0.21419458091259003,
-0.1106068342924118,
-0.017107412219047546,
-0.052657902240753174,
-0.08919410407543182,
0.08719994127750397,
0.11713390052318573,
0.05087953433394432,
-0.06030537560582161,
-0.04394691064953804,
-0.06989791989326477,
0.1599205732345581,
-0.12348966300487518,
-0.08576145023107529
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.