Egor Spirin
commited on
Commit
·
0942cf9
1
Parent(s):
0292a03
Upload model and tokenizer
Browse files- .gitattributes +1 -0
- 1_Pooling/config.json +10 -0
- README.md +225 -0
- assets/mrl.png +3 -0
- assets/training_stages.png +3 -0
- config.json +85 -0
- config_sentence_transformers.json +15 -0
- model.safetensors +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +46 -0
- tokenizer.json +0 -0
- tokenizer_config.json +961 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
36 |
+
*.png filter=lfs diff=lfs merge=lfs -text
|
1_Pooling/config.json
ADDED
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"word_embedding_dimension": 768,
|
3 |
+
"pooling_mode_cls_token": false,
|
4 |
+
"pooling_mode_mean_tokens": true,
|
5 |
+
"pooling_mode_max_tokens": false,
|
6 |
+
"pooling_mode_mean_sqrt_len_tokens": false,
|
7 |
+
"pooling_mode_weightedmean_tokens": false,
|
8 |
+
"pooling_mode_lasttoken": false,
|
9 |
+
"include_prompt": true
|
10 |
+
}
|
README.md
ADDED
@@ -0,0 +1,225 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: sentence-transformers
|
3 |
+
pipeline_tag: sentence-similarity
|
4 |
+
tags:
|
5 |
+
- sentence-transformers
|
6 |
+
- feature-extraction
|
7 |
+
- sentence-similarity
|
8 |
+
license: apache-2.0
|
9 |
+
base_model:
|
10 |
+
- deepvk/RuModernBERT-base
|
11 |
+
datasets:
|
12 |
+
- deepvk/ru-HNP
|
13 |
+
- deepvk/ru-WANLI
|
14 |
+
- deepvk/cultura_ru_ed
|
15 |
+
- Shitao/bge-m3-data
|
16 |
+
- CarlBrendt/Summ_Dialog_News
|
17 |
+
- IlyaGusev/gazeta
|
18 |
+
- its5Q/habr_qna
|
19 |
+
- wikimedia/wikipedia
|
20 |
+
- RussianNLP/wikiomnia
|
21 |
+
language:
|
22 |
+
- ru
|
23 |
+
---
|
24 |
+
|
25 |
+
# USER2-base
|
26 |
+
|
27 |
+
**USER2** is a new generation of the **U**niversal **S**entence **E**ncoder for **R**ussian, designed for sentence representation with long-context support of up to 8,192 tokens.
|
28 |
+
|
29 |
+
The models are built on top of the [`RuModernBERT`](https://huggingface.co/collections/deepvk/rumodernbert-67b5e82fbc707d7ed3857743) encoders and are fine-tuned for retrieval and semantic tasks.
|
30 |
+
They also support [Matryoshka Representation Learning (MRL)](https://arxiv.org/abs/2205.13147) — a technique that enables reducing embedding size with minimal loss in representation quality.
|
31 |
+
|
32 |
+
This is a base model with 149 million parameters.
|
33 |
+
|
34 |
+
| Model | Size | Context Length | Hidden Dim | MRL Dims |
|
35 |
+
|-----------------------------------------------------------------------:|:----:|:--------------:|:----------:|:-----------------------:|
|
36 |
+
| [`deepvk/USER2-small`](https://huggingface.co/deepvk/USER2-small) | 34M | 8192 | 384 | [32, 64, 128, 256, 384] |
|
37 |
+
| `deepvk/USER2-base` | 149M | 8192 | 768 | [32, 64, 128, 256, 384, 512, 768] |
|
38 |
+
|
39 |
+
## Performance
|
40 |
+
|
41 |
+
To evaluate the model, we measure quality on the `MTEB-rus` benchmark.
|
42 |
+
Additionally, to measure long-context retrieval, we run Russian subset of MultiLongDocRetrieval (MLDR) task.
|
43 |
+
|
44 |
+
**MTEB-rus**
|
45 |
+
|
46 |
+
| Model | Size | Hidden Dim | Context Length | MRL support | Mean(task) | Mean(taskType) | Classification | Clustering | MultiLabelClassification | PairClassification | Reranking | Retrieval | STS |
|
47 |
+
|----------------------------------------------------------------------------------------------:|:-----:|:----------:|:--------------:|:-----------:|:----------:|:--------------:|:-------------:|:----------:|:------------------------:|:-----------------:|:---------:|:---------:|:-----:|
|
48 |
+
| `USER-base` | 124M | 768 | 512 | ❌ | 58.11 | 56.67 | 59.89 | 53.26 | 37.72 | 59.76 | 55.58 | 56.14 | 74.35 |
|
49 |
+
| `USER-bge-m3` | 359M | 1024 | 8192 | ❌ | 62.80 | 62.28 | 61.92 | 53.66 | 36.18 | 65.07 | 68.72 | 73.63 | 76.76 |
|
50 |
+
| `multilingual-e5-base` | 278M | 768 | 512 | ❌ | 58.34 | 57.24 | 58.25 | 50.27 | 33.65 | 54.98 | 66.24 | 67.14 | 70.16 |
|
51 |
+
| `multilingual-e5-large-instruct` | 560M | 1024 | 512 | ❌ | 65.00 | 63.36 | 66.28 | 63.13 | 41.15 | 63.89 | 64.35 | 68.23 | 76.48 |
|
52 |
+
| `jina-embeddings-v3` | 572M | 1024 | 8192 | ✅ | 63.45 | 60.93 | 65.24 | 60.90 | 39.24 | 59.22 | 53.86 | 71.99 | 76.04 |
|
53 |
+
| `ru-en-RoSBERTa` | 404M | 1024 | 512 | ❌ | 61.71 | 60.40 | 62.56 | 56.06 | 38.88 | 60.79 | 63.89 | 66.52 | 74.13 |
|
54 |
+
| `USER2-small` | 34M | 384 | 8192 | ✅ | 58.32 | 56.68 | 59.76 | 57.06 | 33.56 | 54.02 | 58.26 | 61.87 | 72.25 |
|
55 |
+
| `USER2-base` | 149M | 768 | 8192 | ✅ | 61.12 | 59.59 | 61.67 | 59.22 | 36.61 | 56.39 | 62.06 | 66.90 | 74.28 |
|
56 |
+
|
57 |
+
**MLDR-rus**
|
58 |
+
|
59 |
+
| Model | Size | nDCG@10 ↑ |
|
60 |
+
|---------------------:|:---------:|:---------:|
|
61 |
+
| `USER-bge-m3` | 359M | 58.53 |
|
62 |
+
| `KaLM-v1.5` | 494M | 53.75 |
|
63 |
+
| `jina-embeddings-v3` | 572M | 49.67 |
|
64 |
+
| `E5-mistral-7b` | 7.11B | 52.40 |
|
65 |
+
| `USER2-small` | 34M | 51.69 |
|
66 |
+
| `USER2-base` | 149M | 54.17 |
|
67 |
+
|
68 |
+
We compare only model with context length of 8192.
|
69 |
+
|
70 |
+
## Matryoshka
|
71 |
+
|
72 |
+
To evaluate MRL capabilities, we also use `MTEB-rus`, applying dimensionality cropping to the embeddings to match the selected size.
|
73 |
+
|
74 |
+
<img src="assets/mrl.png" alt="MRL" width="600"/>
|
75 |
+
|
76 |
+
## Usage
|
77 |
+
|
78 |
+
### Prefixes
|
79 |
+
|
80 |
+
This model is trained similarly to [Nomic Embed](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5#task-instruction-prefixes) and expects task-specific prefixes to be added to the input. The choice of prefix depends on the specific task. We follow a few general guidelines when selecting a prefix:
|
81 |
+
- "classification: " is the default and most universal prefix, often performing well across a variety of tasks.
|
82 |
+
- "clustering: " is recommended for clustering applications: group texts into clusters, discover shared topics, or remove semantic duplicates.
|
83 |
+
- "search_query: " and "search_document: " are intended for retrieval and reranking tasks. Also, in some classification tasks, especially with shorter texts, "search_query" shows superior performance to other prefixes. On the other hand, "search_document" can be beneficial for long-context sentence similarity tasks.
|
84 |
+
|
85 |
+
However, we encourage users to experiment with different prefixes, as certain domains may benefit from specific ones.
|
86 |
+
|
87 |
+
### Sentence Transformers
|
88 |
+
|
89 |
+
```python
|
90 |
+
from sentence_transformers import SentenceTransformer
|
91 |
+
|
92 |
+
model = SentenceTransformer("deepvk/USER2-base")
|
93 |
+
|
94 |
+
query_embeddings = model.encode(["Когда был спущен на воду первый миноносец «Спокойный»?"], prompt_name="search_query")
|
95 |
+
document_embeddings = model.encode(["Спокойный (эсминец)\nЗачислен в списки ВМФ СССР 19 августа 1952 года."], prompt_name="search_document")
|
96 |
+
|
97 |
+
similarities = model.similarity(query_embeddings, document_embeddings)
|
98 |
+
```
|
99 |
+
|
100 |
+
To truncate the embedding dimension, simply pass the new value to the model initialization:
|
101 |
+
```python
|
102 |
+
model = SentenceTransformer("deepvk/USER2-base", truncate_dim=128)
|
103 |
+
```
|
104 |
+
This model was trained with dimensions `[32, 64, 128, 256, 384, 512, 768]`, so it’s recommended to use one of these for best performance.
|
105 |
+
|
106 |
+
### Transformers
|
107 |
+
|
108 |
+
```python
|
109 |
+
import torch
|
110 |
+
import torch.nn.functional as F
|
111 |
+
from transformers import AutoTokenizer, AutoModel
|
112 |
+
|
113 |
+
|
114 |
+
def mean_pooling(model_output, attention_mask):
|
115 |
+
token_embeddings = model_output[0]
|
116 |
+
input_mask_expanded = (
|
117 |
+
attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
|
118 |
+
)
|
119 |
+
return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(
|
120 |
+
input_mask_expanded.sum(1), min=1e-9
|
121 |
+
)
|
122 |
+
|
123 |
+
|
124 |
+
queries = ["search_query: Когда был спущен на воду первый миноносец «Спокойный»?"]
|
125 |
+
documents = ["search_document: Спокойный (эсминец)\nЗачислен в списки ВМФ СССР 19 августа 1952 года."]
|
126 |
+
|
127 |
+
tokenizer = AutoTokenizer.from_pretrained("deepvk/USER2-base")
|
128 |
+
model = AutoModel.from_pretrained("deepvk/USER2-base")
|
129 |
+
|
130 |
+
encoded_queries = tokenizer(queries, padding=True, truncation=True, return_tensors="pt")
|
131 |
+
encoded_documents = tokenizer(documents, padding=True, truncation=True, return_tensors="pt")
|
132 |
+
|
133 |
+
with torch.no_grad():
|
134 |
+
queries_outputs = model(**encoded_queries)
|
135 |
+
documents_outputs = model(**encoded_documents)
|
136 |
+
|
137 |
+
query_embeddings = mean_pooling(queries_outputs, encoded_queries["attention_mask"])
|
138 |
+
query_embeddings = F.normalize(query_embeddings, p=2, dim=1)
|
139 |
+
doc_embeddings = mean_pooling(documents_outputs, encoded_documents["attention_mask"])
|
140 |
+
doc_embeddings = F.normalize(doc_embeddings, p=2, dim=1)
|
141 |
+
|
142 |
+
similarities = query_embeddings @ doc_embeddings.T
|
143 |
+
```
|
144 |
+
|
145 |
+
To truncate the embedding dimension, select the first values:
|
146 |
+
```python
|
147 |
+
query_embeddings = mean_pooling(queries_outputs, encoded_queries["attention_mask"])
|
148 |
+
query_embeddings = query_embeddings[:, :truncate_dim]
|
149 |
+
query_embeddings = F.normalize(query_embeddings, p=2, dim=1)
|
150 |
+
```
|
151 |
+
|
152 |
+
## Training details
|
153 |
+
|
154 |
+
This is the base version with 149 million parameters, based on [`RuModernBERT-base`](https://huggingface.co/deepvk/RuModernBERT-base).
|
155 |
+
It was fine-tuned in three stages: RetroMAE, Weakly Supervised Fine-Tuning, and Supervised Fine-Tuning.
|
156 |
+
|
157 |
+
Following the *bge-m3* training strategy, we use RetroMAE as a retrieval-oriented continuous pretraining step.
|
158 |
+
Leveraging data from the final stage of RuModernBERT training, RetroMAE enhances retrieval quality—particularly for long-context inputs.
|
159 |
+
|
160 |
+
To follow best practices for building a state-of-the-art encoder, we rely on large-scale training with weakly related text pairs.
|
161 |
+
However, such datasets are not publicly available for Russian, unlike for English or Chinese.
|
162 |
+
To overcome this, we apply two complementary strategies:
|
163 |
+
|
164 |
+
- **Cross-lingual transfer**: We train on both English and Russian data, leveraging English resources (`nomic-unsupervised`) alongside our in-house English-Russian parallel corpora.
|
165 |
+
- **Unsupervised pair mining**: From the [`deepvk/cultura_ru_edu`](https://huggingface.co/datasets/deepvk/cultura_ru_edu) corpus, we extract 50M pairs using a simple heuristic—selecting non-overlapping text blocks that are not substrings of one another.
|
166 |
+
|
167 |
+
This approach has shown promising results, allowing us to train high-performing models with minimal target-language pairs—especially when compared to pipelines used for other languages.
|
168 |
+
|
169 |
+
The table below shows the datasets used and the number of times each was upsampled.
|
170 |
+
|
171 |
+
| Dataset | Size | Upsample |
|
172 |
+
|----------------------------:|:----:|:-------:|
|
173 |
+
| [nomic-en](https://github.com/nomic-ai/nomic) | 235M | 1 |
|
174 |
+
| [nomic-ru](https://github.com/nomic-ai/nomic) | 39M | 3 |
|
175 |
+
| in-house En-Ru parallel | 250M | 1 |
|
176 |
+
| [cultura-sampled](https://huggingface.co/datasets/deepvk/cultura_ru_edu) | 50M | 1 |
|
177 |
+
| **Total** | 652M | |
|
178 |
+
|
179 |
+
For the third stage, we switch to cleaner, task-specific datasets.
|
180 |
+
In some cases, additional filtering was applied using a cross-encoder.
|
181 |
+
For all retrieval datasets, we mine hard negatives.
|
182 |
+
|
183 |
+
| Dataset | Examples | Notes |
|
184 |
+
|-------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:------------------------------------------|
|
185 |
+
| [Nomic-en-supervised](https://huggingface.co/datasets/nomic-ai/nomic-embed-supervised-data) | 1.7 M | Unmodified |
|
186 |
+
| AllNLI | 200 K | Translated SNLI/MNLI/ANLI to Russian |
|
187 |
+
| [fishkinet-posts](https://huggingface.co/datasets/nyuuzyou/fishkinet-posts) | 93 K | Title–content pairs |
|
188 |
+
| [gazeta](https://huggingface.co/datasets/IlyaGusev/gazeta) | 55 K | Title–text pairs |
|
189 |
+
| [habr_qna](https://huggingface.co/datasets/its5Q/habr_qna) | 100 K | Title–description pairs |
|
190 |
+
| [lenta](https://huggingface.co/datasets/zloelias/lenta-ru) | 100 K | Title–news pairs |
|
191 |
+
| [miracl_ru](https://huggingface.co/datasets/Shitao/bge-m3-data) | 10 K | One positive per anchor |
|
192 |
+
| [mldr_ru](https://huggingface.co/datasets/Shitao/bge-m3-data) | 1.8 K | Unmodified |
|
193 |
+
| [mr-tydi_ru](https://huggingface.co/datasets/Shitao/bge-m3-data) | 5.3 K | Unmodified |
|
194 |
+
| [mmarco_ru](https://huggingface.co/datasets/unicamp-dl/mmarco) | 500 K | Unmodified |
|
195 |
+
| [ru-HNP](https://huggingface.co/datasets/deepvk/ru-HNP) | 100 K | One pos + one neg per anchor |
|
196 |
+
| ru‑queries | 199 K | In-house (generated as in [arXiv:2401.00368](https://arxiv.org/abs/2401.00368)) |
|
197 |
+
| [ru‑WaNLI](https://huggingface.co/datasets/deepvk/ru-WANLI) | 35 K | Entailment -> pos, contradiction -> neg |
|
198 |
+
| [sampled_wiki](https://huggingface.co/datasets/wikimedia/wikipedia) | 1 M | Sampled text blocks from Wikipedia |
|
199 |
+
| [summ_dialog_news](https://huggingface.co/datasets/CarlBrendt/Summ_Dialog_News) | 37 K | Summary–info pairs |
|
200 |
+
| [wikiomnia_qna](https://huggingface.co/datasets/RussianNLP/wikiomnia) | 100 K | QA pairs (T5-generated) |
|
201 |
+
| [yandex_q](https://huggingface.co/datasets/its5Q/yandex-q) | 83 K | Q+desc-answer pairs |
|
202 |
+
| **Total** | 4.3 M | |
|
203 |
+
|
204 |
+
|
205 |
+
### Ablation
|
206 |
+
|
207 |
+
Alongside the final model, we also release all intermediate training steps.
|
208 |
+
Both the **retromae** and **weakly_sft** models are available under the specified revisions in this repository.
|
209 |
+
We hope these additional models prove useful for your experiments.
|
210 |
+
|
211 |
+
Below is a comparison of all training stages on a subset of `MTEB-rus`.
|
212 |
+
|
213 |
+
<img src="assets/training_stages.png" alt="training_stages" width="600"/>
|
214 |
+
|
215 |
+
## Citations
|
216 |
+
|
217 |
+
```
|
218 |
+
@misc{deepvk2025user,
|
219 |
+
title={USER2},
|
220 |
+
author={Malashenko, Boris and Spirin, Egor and Sokolov Andrey},
|
221 |
+
url={https://huggingface.co/deepvk/USER2-base},
|
222 |
+
publisher={Hugging Face}
|
223 |
+
year={2025},
|
224 |
+
}
|
225 |
+
```
|
assets/mrl.png
ADDED
![]() |
Git LFS Details
|
assets/training_stages.png
ADDED
![]() |
Git LFS Details
|
config.json
ADDED
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "last_base",
|
3 |
+
"activation_function": "gelu",
|
4 |
+
"allow_embedding_resizing": true,
|
5 |
+
"architectures": [
|
6 |
+
"ModernBertModel"
|
7 |
+
],
|
8 |
+
"attention_bias": false,
|
9 |
+
"attention_dropout": 0.0,
|
10 |
+
"attention_layer": "rope",
|
11 |
+
"attention_probs_dropout_prob": 0.0,
|
12 |
+
"attn_out_bias": false,
|
13 |
+
"attn_out_dropout_prob": 0.1,
|
14 |
+
"attn_qkv_bias": false,
|
15 |
+
"bert_layer": "prenorm",
|
16 |
+
"bos_token_id": 50281,
|
17 |
+
"classifier_activation": "gelu",
|
18 |
+
"classifier_bias": false,
|
19 |
+
"classifier_dropout": 0.0,
|
20 |
+
"classifier_pooling": "cls",
|
21 |
+
"cls_token_id": 50281,
|
22 |
+
"compile_model": true,
|
23 |
+
"decoder_bias": true,
|
24 |
+
"deterministic_flash_attn": false,
|
25 |
+
"embed_dropout_prob": 0.0,
|
26 |
+
"embed_norm": true,
|
27 |
+
"embedding_dropout": 0.0,
|
28 |
+
"embedding_layer": "sans_pos",
|
29 |
+
"eos_token_id": 50282,
|
30 |
+
"final_norm": true,
|
31 |
+
"global_attn_every_n_layers": 3,
|
32 |
+
"global_rope_theta": 160000.0,
|
33 |
+
"head_pred_act": "gelu",
|
34 |
+
"hidden_act": "gelu",
|
35 |
+
"hidden_activation": "gelu",
|
36 |
+
"hidden_dropout_prob": 0.0,
|
37 |
+
"hidden_size": 768,
|
38 |
+
"init_method": "full_megatron",
|
39 |
+
"initializer_cutoff_factor": 2.0,
|
40 |
+
"initializer_range": 0.02,
|
41 |
+
"intermediate_size": 1152,
|
42 |
+
"layer_norm_eps": 1e-05,
|
43 |
+
"local_attention": 128,
|
44 |
+
"local_attn_rotary_emb_base": 10000.0,
|
45 |
+
"local_rope_theta": 10000.0,
|
46 |
+
"loss_function": "fa_cross_entropy",
|
47 |
+
"loss_kwargs": {
|
48 |
+
"reduction": "mean"
|
49 |
+
},
|
50 |
+
"masked_prediction": true,
|
51 |
+
"max_position_embeddings": 8192,
|
52 |
+
"mlp_bias": false,
|
53 |
+
"mlp_dropout": 0.0,
|
54 |
+
"mlp_dropout_prob": 0.0,
|
55 |
+
"mlp_in_bias": false,
|
56 |
+
"mlp_layer": "glu",
|
57 |
+
"mlp_out_bias": false,
|
58 |
+
"model_type": "modernbert",
|
59 |
+
"norm_bias": false,
|
60 |
+
"norm_eps": 1e-05,
|
61 |
+
"norm_kwargs": {
|
62 |
+
"bias": false,
|
63 |
+
"eps": 1e-05
|
64 |
+
},
|
65 |
+
"normalization": "layernorm",
|
66 |
+
"num_attention_heads": 12,
|
67 |
+
"num_hidden_layers": 22,
|
68 |
+
"pad_token_id": 50283,
|
69 |
+
"padding": "unpadded",
|
70 |
+
"reference_compile": null,
|
71 |
+
"repad_logits_with_grad": false,
|
72 |
+
"rotary_emb_base": 160000.0,
|
73 |
+
"rotary_emb_dim": null,
|
74 |
+
"rotary_emb_interleaved": false,
|
75 |
+
"rotary_emb_scale_base": null,
|
76 |
+
"sep_token_id": 50282,
|
77 |
+
"skip_first_prenorm": true,
|
78 |
+
"sliding_window": 128,
|
79 |
+
"sparse_pred_ignore_index": -100,
|
80 |
+
"sparse_prediction": false,
|
81 |
+
"torch_dtype": "float32",
|
82 |
+
"transformers_version": "4.49.0",
|
83 |
+
"unpad_embeddings": true,
|
84 |
+
"vocab_size": 50368
|
85 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "4.0.2",
|
4 |
+
"transformers": "4.49.0",
|
5 |
+
"pytorch": "2.6.0"
|
6 |
+
},
|
7 |
+
"prompts": {
|
8 |
+
"classification": "classification: ",
|
9 |
+
"clustering": "clustering: ",
|
10 |
+
"search_query": "search_query: ",
|
11 |
+
"search_document": "search_document: "
|
12 |
+
},
|
13 |
+
"default_prompt_name": null,
|
14 |
+
"similarity_fn_name": "cosine"
|
15 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:54174e02d3948c546218159cc4940472e9dc0eee8f707aa9915ab632ed12acad
|
3 |
+
size 596070136
|
modules.json
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"idx": 0,
|
4 |
+
"name": "0",
|
5 |
+
"path": "",
|
6 |
+
"type": "sentence_transformers.models.Transformer"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"idx": 1,
|
10 |
+
"name": "1",
|
11 |
+
"path": "1_Pooling",
|
12 |
+
"type": "sentence_transformers.models.Pooling"
|
13 |
+
}
|
14 |
+
]
|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"max_seq_length": 8192,
|
3 |
+
"do_lower_case": false
|
4 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"additional_special_tokens": [
|
3 |
+
"<|padding|>",
|
4 |
+
"<|endoftext|>",
|
5 |
+
"[UNK]",
|
6 |
+
"[CLS]",
|
7 |
+
"[SEP]",
|
8 |
+
"[PAD]",
|
9 |
+
"[MASK]"
|
10 |
+
],
|
11 |
+
"cls_token": {
|
12 |
+
"content": "[CLS]",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false
|
17 |
+
},
|
18 |
+
"mask_token": {
|
19 |
+
"content": "[MASK]",
|
20 |
+
"lstrip": true,
|
21 |
+
"normalized": false,
|
22 |
+
"rstrip": false,
|
23 |
+
"single_word": false
|
24 |
+
},
|
25 |
+
"pad_token": {
|
26 |
+
"content": "[PAD]",
|
27 |
+
"lstrip": false,
|
28 |
+
"normalized": false,
|
29 |
+
"rstrip": false,
|
30 |
+
"single_word": false
|
31 |
+
},
|
32 |
+
"sep_token": {
|
33 |
+
"content": "[SEP]",
|
34 |
+
"lstrip": false,
|
35 |
+
"normalized": false,
|
36 |
+
"rstrip": false,
|
37 |
+
"single_word": false
|
38 |
+
},
|
39 |
+
"unk_token": {
|
40 |
+
"content": "[UNK]",
|
41 |
+
"lstrip": false,
|
42 |
+
"normalized": false,
|
43 |
+
"rstrip": false,
|
44 |
+
"single_word": false
|
45 |
+
}
|
46 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,961 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "<|padding|>",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"1": {
|
12 |
+
"content": "<|endoftext|>",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"2": {
|
20 |
+
"content": " ",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": true,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": false
|
26 |
+
},
|
27 |
+
"3": {
|
28 |
+
"content": " ",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": true,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": false
|
34 |
+
},
|
35 |
+
"4": {
|
36 |
+
"content": " ",
|
37 |
+
"lstrip": false,
|
38 |
+
"normalized": true,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": false
|
42 |
+
},
|
43 |
+
"5": {
|
44 |
+
"content": "|||EMAIL_ADDRESS|||",
|
45 |
+
"lstrip": false,
|
46 |
+
"normalized": true,
|
47 |
+
"rstrip": false,
|
48 |
+
"single_word": false,
|
49 |
+
"special": false
|
50 |
+
},
|
51 |
+
"6": {
|
52 |
+
"content": "|||PHONE_NUMBER|||",
|
53 |
+
"lstrip": false,
|
54 |
+
"normalized": true,
|
55 |
+
"rstrip": false,
|
56 |
+
"single_word": false,
|
57 |
+
"special": false
|
58 |
+
},
|
59 |
+
"50259": {
|
60 |
+
"content": "|||IP_ADDRESS|||",
|
61 |
+
"lstrip": false,
|
62 |
+
"normalized": true,
|
63 |
+
"rstrip": false,
|
64 |
+
"single_word": false,
|
65 |
+
"special": false
|
66 |
+
},
|
67 |
+
"50260": {
|
68 |
+
"content": " ",
|
69 |
+
"lstrip": false,
|
70 |
+
"normalized": true,
|
71 |
+
"rstrip": false,
|
72 |
+
"single_word": false,
|
73 |
+
"special": false
|
74 |
+
},
|
75 |
+
"50261": {
|
76 |
+
"content": " ",
|
77 |
+
"lstrip": false,
|
78 |
+
"normalized": true,
|
79 |
+
"rstrip": false,
|
80 |
+
"single_word": false,
|
81 |
+
"special": false
|
82 |
+
},
|
83 |
+
"50262": {
|
84 |
+
"content": " ",
|
85 |
+
"lstrip": false,
|
86 |
+
"normalized": true,
|
87 |
+
"rstrip": false,
|
88 |
+
"single_word": false,
|
89 |
+
"special": false
|
90 |
+
},
|
91 |
+
"50263": {
|
92 |
+
"content": " ",
|
93 |
+
"lstrip": false,
|
94 |
+
"normalized": true,
|
95 |
+
"rstrip": false,
|
96 |
+
"single_word": false,
|
97 |
+
"special": false
|
98 |
+
},
|
99 |
+
"50264": {
|
100 |
+
"content": " ",
|
101 |
+
"lstrip": false,
|
102 |
+
"normalized": true,
|
103 |
+
"rstrip": false,
|
104 |
+
"single_word": false,
|
105 |
+
"special": false
|
106 |
+
},
|
107 |
+
"50265": {
|
108 |
+
"content": " ",
|
109 |
+
"lstrip": false,
|
110 |
+
"normalized": true,
|
111 |
+
"rstrip": false,
|
112 |
+
"single_word": false,
|
113 |
+
"special": false
|
114 |
+
},
|
115 |
+
"50266": {
|
116 |
+
"content": " ",
|
117 |
+
"lstrip": false,
|
118 |
+
"normalized": true,
|
119 |
+
"rstrip": false,
|
120 |
+
"single_word": false,
|
121 |
+
"special": false
|
122 |
+
},
|
123 |
+
"50267": {
|
124 |
+
"content": " ",
|
125 |
+
"lstrip": false,
|
126 |
+
"normalized": true,
|
127 |
+
"rstrip": false,
|
128 |
+
"single_word": false,
|
129 |
+
"special": false
|
130 |
+
},
|
131 |
+
"50268": {
|
132 |
+
"content": " ",
|
133 |
+
"lstrip": false,
|
134 |
+
"normalized": true,
|
135 |
+
"rstrip": false,
|
136 |
+
"single_word": false,
|
137 |
+
"special": false
|
138 |
+
},
|
139 |
+
"50269": {
|
140 |
+
"content": " ",
|
141 |
+
"lstrip": false,
|
142 |
+
"normalized": true,
|
143 |
+
"rstrip": false,
|
144 |
+
"single_word": false,
|
145 |
+
"special": false
|
146 |
+
},
|
147 |
+
"50270": {
|
148 |
+
"content": " ",
|
149 |
+
"lstrip": false,
|
150 |
+
"normalized": true,
|
151 |
+
"rstrip": false,
|
152 |
+
"single_word": false,
|
153 |
+
"special": false
|
154 |
+
},
|
155 |
+
"50271": {
|
156 |
+
"content": " ",
|
157 |
+
"lstrip": false,
|
158 |
+
"normalized": true,
|
159 |
+
"rstrip": false,
|
160 |
+
"single_word": false,
|
161 |
+
"special": false
|
162 |
+
},
|
163 |
+
"50272": {
|
164 |
+
"content": " ",
|
165 |
+
"lstrip": false,
|
166 |
+
"normalized": true,
|
167 |
+
"rstrip": false,
|
168 |
+
"single_word": false,
|
169 |
+
"special": false
|
170 |
+
},
|
171 |
+
"50273": {
|
172 |
+
"content": " ",
|
173 |
+
"lstrip": false,
|
174 |
+
"normalized": true,
|
175 |
+
"rstrip": false,
|
176 |
+
"single_word": false,
|
177 |
+
"special": false
|
178 |
+
},
|
179 |
+
"50274": {
|
180 |
+
"content": " ",
|
181 |
+
"lstrip": false,
|
182 |
+
"normalized": true,
|
183 |
+
"rstrip": false,
|
184 |
+
"single_word": false,
|
185 |
+
"special": false
|
186 |
+
},
|
187 |
+
"50275": {
|
188 |
+
"content": " ",
|
189 |
+
"lstrip": false,
|
190 |
+
"normalized": true,
|
191 |
+
"rstrip": false,
|
192 |
+
"single_word": false,
|
193 |
+
"special": false
|
194 |
+
},
|
195 |
+
"50276": {
|
196 |
+
"content": " ",
|
197 |
+
"lstrip": false,
|
198 |
+
"normalized": true,
|
199 |
+
"rstrip": false,
|
200 |
+
"single_word": false,
|
201 |
+
"special": false
|
202 |
+
},
|
203 |
+
"50277": {
|
204 |
+
"content": " ",
|
205 |
+
"lstrip": false,
|
206 |
+
"normalized": true,
|
207 |
+
"rstrip": false,
|
208 |
+
"single_word": false,
|
209 |
+
"special": false
|
210 |
+
},
|
211 |
+
"50278": {
|
212 |
+
"content": " ",
|
213 |
+
"lstrip": false,
|
214 |
+
"normalized": true,
|
215 |
+
"rstrip": false,
|
216 |
+
"single_word": false,
|
217 |
+
"special": false
|
218 |
+
},
|
219 |
+
"50279": {
|
220 |
+
"content": " ",
|
221 |
+
"lstrip": false,
|
222 |
+
"normalized": true,
|
223 |
+
"rstrip": false,
|
224 |
+
"single_word": false,
|
225 |
+
"special": false
|
226 |
+
},
|
227 |
+
"50280": {
|
228 |
+
"content": "[UNK]",
|
229 |
+
"lstrip": false,
|
230 |
+
"normalized": false,
|
231 |
+
"rstrip": false,
|
232 |
+
"single_word": false,
|
233 |
+
"special": true
|
234 |
+
},
|
235 |
+
"50281": {
|
236 |
+
"content": "[CLS]",
|
237 |
+
"lstrip": false,
|
238 |
+
"normalized": false,
|
239 |
+
"rstrip": false,
|
240 |
+
"single_word": false,
|
241 |
+
"special": true
|
242 |
+
},
|
243 |
+
"50282": {
|
244 |
+
"content": "[SEP]",
|
245 |
+
"lstrip": false,
|
246 |
+
"normalized": false,
|
247 |
+
"rstrip": false,
|
248 |
+
"single_word": false,
|
249 |
+
"special": true
|
250 |
+
},
|
251 |
+
"50283": {
|
252 |
+
"content": "[PAD]",
|
253 |
+
"lstrip": false,
|
254 |
+
"normalized": false,
|
255 |
+
"rstrip": false,
|
256 |
+
"single_word": false,
|
257 |
+
"special": true
|
258 |
+
},
|
259 |
+
"50284": {
|
260 |
+
"content": "[MASK]",
|
261 |
+
"lstrip": true,
|
262 |
+
"normalized": false,
|
263 |
+
"rstrip": false,
|
264 |
+
"single_word": false,
|
265 |
+
"special": true
|
266 |
+
},
|
267 |
+
"50285": {
|
268 |
+
"content": "[unused0]",
|
269 |
+
"lstrip": false,
|
270 |
+
"normalized": true,
|
271 |
+
"rstrip": false,
|
272 |
+
"single_word": false,
|
273 |
+
"special": false
|
274 |
+
},
|
275 |
+
"50286": {
|
276 |
+
"content": "[unused1]",
|
277 |
+
"lstrip": false,
|
278 |
+
"normalized": true,
|
279 |
+
"rstrip": false,
|
280 |
+
"single_word": false,
|
281 |
+
"special": false
|
282 |
+
},
|
283 |
+
"50287": {
|
284 |
+
"content": "[unused2]",
|
285 |
+
"lstrip": false,
|
286 |
+
"normalized": true,
|
287 |
+
"rstrip": false,
|
288 |
+
"single_word": false,
|
289 |
+
"special": false
|
290 |
+
},
|
291 |
+
"50288": {
|
292 |
+
"content": "[unused3]",
|
293 |
+
"lstrip": false,
|
294 |
+
"normalized": true,
|
295 |
+
"rstrip": false,
|
296 |
+
"single_word": false,
|
297 |
+
"special": false
|
298 |
+
},
|
299 |
+
"50289": {
|
300 |
+
"content": "[unused4]",
|
301 |
+
"lstrip": false,
|
302 |
+
"normalized": true,
|
303 |
+
"rstrip": false,
|
304 |
+
"single_word": false,
|
305 |
+
"special": false
|
306 |
+
},
|
307 |
+
"50290": {
|
308 |
+
"content": "[unused5]",
|
309 |
+
"lstrip": false,
|
310 |
+
"normalized": true,
|
311 |
+
"rstrip": false,
|
312 |
+
"single_word": false,
|
313 |
+
"special": false
|
314 |
+
},
|
315 |
+
"50291": {
|
316 |
+
"content": "[unused6]",
|
317 |
+
"lstrip": false,
|
318 |
+
"normalized": true,
|
319 |
+
"rstrip": false,
|
320 |
+
"single_word": false,
|
321 |
+
"special": false
|
322 |
+
},
|
323 |
+
"50292": {
|
324 |
+
"content": "[unused7]",
|
325 |
+
"lstrip": false,
|
326 |
+
"normalized": true,
|
327 |
+
"rstrip": false,
|
328 |
+
"single_word": false,
|
329 |
+
"special": false
|
330 |
+
},
|
331 |
+
"50293": {
|
332 |
+
"content": "[unused8]",
|
333 |
+
"lstrip": false,
|
334 |
+
"normalized": true,
|
335 |
+
"rstrip": false,
|
336 |
+
"single_word": false,
|
337 |
+
"special": false
|
338 |
+
},
|
339 |
+
"50294": {
|
340 |
+
"content": "[unused9]",
|
341 |
+
"lstrip": false,
|
342 |
+
"normalized": true,
|
343 |
+
"rstrip": false,
|
344 |
+
"single_word": false,
|
345 |
+
"special": false
|
346 |
+
},
|
347 |
+
"50295": {
|
348 |
+
"content": "[unused10]",
|
349 |
+
"lstrip": false,
|
350 |
+
"normalized": true,
|
351 |
+
"rstrip": false,
|
352 |
+
"single_word": false,
|
353 |
+
"special": false
|
354 |
+
},
|
355 |
+
"50296": {
|
356 |
+
"content": "[unused11]",
|
357 |
+
"lstrip": false,
|
358 |
+
"normalized": true,
|
359 |
+
"rstrip": false,
|
360 |
+
"single_word": false,
|
361 |
+
"special": false
|
362 |
+
},
|
363 |
+
"50297": {
|
364 |
+
"content": "[unused12]",
|
365 |
+
"lstrip": false,
|
366 |
+
"normalized": true,
|
367 |
+
"rstrip": false,
|
368 |
+
"single_word": false,
|
369 |
+
"special": false
|
370 |
+
},
|
371 |
+
"50298": {
|
372 |
+
"content": "[unused13]",
|
373 |
+
"lstrip": false,
|
374 |
+
"normalized": true,
|
375 |
+
"rstrip": false,
|
376 |
+
"single_word": false,
|
377 |
+
"special": false
|
378 |
+
},
|
379 |
+
"50299": {
|
380 |
+
"content": "[unused14]",
|
381 |
+
"lstrip": false,
|
382 |
+
"normalized": true,
|
383 |
+
"rstrip": false,
|
384 |
+
"single_word": false,
|
385 |
+
"special": false
|
386 |
+
},
|
387 |
+
"50300": {
|
388 |
+
"content": "[unused15]",
|
389 |
+
"lstrip": false,
|
390 |
+
"normalized": true,
|
391 |
+
"rstrip": false,
|
392 |
+
"single_word": false,
|
393 |
+
"special": false
|
394 |
+
},
|
395 |
+
"50301": {
|
396 |
+
"content": "[unused16]",
|
397 |
+
"lstrip": false,
|
398 |
+
"normalized": true,
|
399 |
+
"rstrip": false,
|
400 |
+
"single_word": false,
|
401 |
+
"special": false
|
402 |
+
},
|
403 |
+
"50302": {
|
404 |
+
"content": "[unused17]",
|
405 |
+
"lstrip": false,
|
406 |
+
"normalized": true,
|
407 |
+
"rstrip": false,
|
408 |
+
"single_word": false,
|
409 |
+
"special": false
|
410 |
+
},
|
411 |
+
"50303": {
|
412 |
+
"content": "[unused18]",
|
413 |
+
"lstrip": false,
|
414 |
+
"normalized": true,
|
415 |
+
"rstrip": false,
|
416 |
+
"single_word": false,
|
417 |
+
"special": false
|
418 |
+
},
|
419 |
+
"50304": {
|
420 |
+
"content": "[unused19]",
|
421 |
+
"lstrip": false,
|
422 |
+
"normalized": true,
|
423 |
+
"rstrip": false,
|
424 |
+
"single_word": false,
|
425 |
+
"special": false
|
426 |
+
},
|
427 |
+
"50305": {
|
428 |
+
"content": "[unused20]",
|
429 |
+
"lstrip": false,
|
430 |
+
"normalized": true,
|
431 |
+
"rstrip": false,
|
432 |
+
"single_word": false,
|
433 |
+
"special": false
|
434 |
+
},
|
435 |
+
"50306": {
|
436 |
+
"content": "[unused21]",
|
437 |
+
"lstrip": false,
|
438 |
+
"normalized": true,
|
439 |
+
"rstrip": false,
|
440 |
+
"single_word": false,
|
441 |
+
"special": false
|
442 |
+
},
|
443 |
+
"50307": {
|
444 |
+
"content": "[unused22]",
|
445 |
+
"lstrip": false,
|
446 |
+
"normalized": true,
|
447 |
+
"rstrip": false,
|
448 |
+
"single_word": false,
|
449 |
+
"special": false
|
450 |
+
},
|
451 |
+
"50308": {
|
452 |
+
"content": "[unused23]",
|
453 |
+
"lstrip": false,
|
454 |
+
"normalized": true,
|
455 |
+
"rstrip": false,
|
456 |
+
"single_word": false,
|
457 |
+
"special": false
|
458 |
+
},
|
459 |
+
"50309": {
|
460 |
+
"content": "[unused24]",
|
461 |
+
"lstrip": false,
|
462 |
+
"normalized": true,
|
463 |
+
"rstrip": false,
|
464 |
+
"single_word": false,
|
465 |
+
"special": false
|
466 |
+
},
|
467 |
+
"50310": {
|
468 |
+
"content": "[unused25]",
|
469 |
+
"lstrip": false,
|
470 |
+
"normalized": true,
|
471 |
+
"rstrip": false,
|
472 |
+
"single_word": false,
|
473 |
+
"special": false
|
474 |
+
},
|
475 |
+
"50311": {
|
476 |
+
"content": "[unused26]",
|
477 |
+
"lstrip": false,
|
478 |
+
"normalized": true,
|
479 |
+
"rstrip": false,
|
480 |
+
"single_word": false,
|
481 |
+
"special": false
|
482 |
+
},
|
483 |
+
"50312": {
|
484 |
+
"content": "[unused27]",
|
485 |
+
"lstrip": false,
|
486 |
+
"normalized": true,
|
487 |
+
"rstrip": false,
|
488 |
+
"single_word": false,
|
489 |
+
"special": false
|
490 |
+
},
|
491 |
+
"50313": {
|
492 |
+
"content": "[unused28]",
|
493 |
+
"lstrip": false,
|
494 |
+
"normalized": true,
|
495 |
+
"rstrip": false,
|
496 |
+
"single_word": false,
|
497 |
+
"special": false
|
498 |
+
},
|
499 |
+
"50314": {
|
500 |
+
"content": "[unused29]",
|
501 |
+
"lstrip": false,
|
502 |
+
"normalized": true,
|
503 |
+
"rstrip": false,
|
504 |
+
"single_word": false,
|
505 |
+
"special": false
|
506 |
+
},
|
507 |
+
"50315": {
|
508 |
+
"content": "[unused30]",
|
509 |
+
"lstrip": false,
|
510 |
+
"normalized": true,
|
511 |
+
"rstrip": false,
|
512 |
+
"single_word": false,
|
513 |
+
"special": false
|
514 |
+
},
|
515 |
+
"50316": {
|
516 |
+
"content": "[unused31]",
|
517 |
+
"lstrip": false,
|
518 |
+
"normalized": true,
|
519 |
+
"rstrip": false,
|
520 |
+
"single_word": false,
|
521 |
+
"special": false
|
522 |
+
},
|
523 |
+
"50317": {
|
524 |
+
"content": "[unused32]",
|
525 |
+
"lstrip": false,
|
526 |
+
"normalized": true,
|
527 |
+
"rstrip": false,
|
528 |
+
"single_word": false,
|
529 |
+
"special": false
|
530 |
+
},
|
531 |
+
"50318": {
|
532 |
+
"content": "[unused33]",
|
533 |
+
"lstrip": false,
|
534 |
+
"normalized": true,
|
535 |
+
"rstrip": false,
|
536 |
+
"single_word": false,
|
537 |
+
"special": false
|
538 |
+
},
|
539 |
+
"50319": {
|
540 |
+
"content": "[unused34]",
|
541 |
+
"lstrip": false,
|
542 |
+
"normalized": true,
|
543 |
+
"rstrip": false,
|
544 |
+
"single_word": false,
|
545 |
+
"special": false
|
546 |
+
},
|
547 |
+
"50320": {
|
548 |
+
"content": "[unused35]",
|
549 |
+
"lstrip": false,
|
550 |
+
"normalized": true,
|
551 |
+
"rstrip": false,
|
552 |
+
"single_word": false,
|
553 |
+
"special": false
|
554 |
+
},
|
555 |
+
"50321": {
|
556 |
+
"content": "[unused36]",
|
557 |
+
"lstrip": false,
|
558 |
+
"normalized": true,
|
559 |
+
"rstrip": false,
|
560 |
+
"single_word": false,
|
561 |
+
"special": false
|
562 |
+
},
|
563 |
+
"50322": {
|
564 |
+
"content": "[unused37]",
|
565 |
+
"lstrip": false,
|
566 |
+
"normalized": true,
|
567 |
+
"rstrip": false,
|
568 |
+
"single_word": false,
|
569 |
+
"special": false
|
570 |
+
},
|
571 |
+
"50323": {
|
572 |
+
"content": "[unused38]",
|
573 |
+
"lstrip": false,
|
574 |
+
"normalized": true,
|
575 |
+
"rstrip": false,
|
576 |
+
"single_word": false,
|
577 |
+
"special": false
|
578 |
+
},
|
579 |
+
"50324": {
|
580 |
+
"content": "[unused39]",
|
581 |
+
"lstrip": false,
|
582 |
+
"normalized": true,
|
583 |
+
"rstrip": false,
|
584 |
+
"single_word": false,
|
585 |
+
"special": false
|
586 |
+
},
|
587 |
+
"50325": {
|
588 |
+
"content": "[unused40]",
|
589 |
+
"lstrip": false,
|
590 |
+
"normalized": true,
|
591 |
+
"rstrip": false,
|
592 |
+
"single_word": false,
|
593 |
+
"special": false
|
594 |
+
},
|
595 |
+
"50326": {
|
596 |
+
"content": "[unused41]",
|
597 |
+
"lstrip": false,
|
598 |
+
"normalized": true,
|
599 |
+
"rstrip": false,
|
600 |
+
"single_word": false,
|
601 |
+
"special": false
|
602 |
+
},
|
603 |
+
"50327": {
|
604 |
+
"content": "[unused42]",
|
605 |
+
"lstrip": false,
|
606 |
+
"normalized": true,
|
607 |
+
"rstrip": false,
|
608 |
+
"single_word": false,
|
609 |
+
"special": false
|
610 |
+
},
|
611 |
+
"50328": {
|
612 |
+
"content": "[unused43]",
|
613 |
+
"lstrip": false,
|
614 |
+
"normalized": true,
|
615 |
+
"rstrip": false,
|
616 |
+
"single_word": false,
|
617 |
+
"special": false
|
618 |
+
},
|
619 |
+
"50329": {
|
620 |
+
"content": "[unused44]",
|
621 |
+
"lstrip": false,
|
622 |
+
"normalized": true,
|
623 |
+
"rstrip": false,
|
624 |
+
"single_word": false,
|
625 |
+
"special": false
|
626 |
+
},
|
627 |
+
"50330": {
|
628 |
+
"content": "[unused45]",
|
629 |
+
"lstrip": false,
|
630 |
+
"normalized": true,
|
631 |
+
"rstrip": false,
|
632 |
+
"single_word": false,
|
633 |
+
"special": false
|
634 |
+
},
|
635 |
+
"50331": {
|
636 |
+
"content": "[unused46]",
|
637 |
+
"lstrip": false,
|
638 |
+
"normalized": true,
|
639 |
+
"rstrip": false,
|
640 |
+
"single_word": false,
|
641 |
+
"special": false
|
642 |
+
},
|
643 |
+
"50332": {
|
644 |
+
"content": "[unused47]",
|
645 |
+
"lstrip": false,
|
646 |
+
"normalized": true,
|
647 |
+
"rstrip": false,
|
648 |
+
"single_word": false,
|
649 |
+
"special": false
|
650 |
+
},
|
651 |
+
"50333": {
|
652 |
+
"content": "[unused48]",
|
653 |
+
"lstrip": false,
|
654 |
+
"normalized": true,
|
655 |
+
"rstrip": false,
|
656 |
+
"single_word": false,
|
657 |
+
"special": false
|
658 |
+
},
|
659 |
+
"50334": {
|
660 |
+
"content": "[unused49]",
|
661 |
+
"lstrip": false,
|
662 |
+
"normalized": true,
|
663 |
+
"rstrip": false,
|
664 |
+
"single_word": false,
|
665 |
+
"special": false
|
666 |
+
},
|
667 |
+
"50335": {
|
668 |
+
"content": "[unused50]",
|
669 |
+
"lstrip": false,
|
670 |
+
"normalized": true,
|
671 |
+
"rstrip": false,
|
672 |
+
"single_word": false,
|
673 |
+
"special": false
|
674 |
+
},
|
675 |
+
"50336": {
|
676 |
+
"content": "[unused51]",
|
677 |
+
"lstrip": false,
|
678 |
+
"normalized": true,
|
679 |
+
"rstrip": false,
|
680 |
+
"single_word": false,
|
681 |
+
"special": false
|
682 |
+
},
|
683 |
+
"50337": {
|
684 |
+
"content": "[unused52]",
|
685 |
+
"lstrip": false,
|
686 |
+
"normalized": true,
|
687 |
+
"rstrip": false,
|
688 |
+
"single_word": false,
|
689 |
+
"special": false
|
690 |
+
},
|
691 |
+
"50338": {
|
692 |
+
"content": "[unused53]",
|
693 |
+
"lstrip": false,
|
694 |
+
"normalized": true,
|
695 |
+
"rstrip": false,
|
696 |
+
"single_word": false,
|
697 |
+
"special": false
|
698 |
+
},
|
699 |
+
"50339": {
|
700 |
+
"content": "[unused54]",
|
701 |
+
"lstrip": false,
|
702 |
+
"normalized": true,
|
703 |
+
"rstrip": false,
|
704 |
+
"single_word": false,
|
705 |
+
"special": false
|
706 |
+
},
|
707 |
+
"50340": {
|
708 |
+
"content": "[unused55]",
|
709 |
+
"lstrip": false,
|
710 |
+
"normalized": true,
|
711 |
+
"rstrip": false,
|
712 |
+
"single_word": false,
|
713 |
+
"special": false
|
714 |
+
},
|
715 |
+
"50341": {
|
716 |
+
"content": "[unused56]",
|
717 |
+
"lstrip": false,
|
718 |
+
"normalized": true,
|
719 |
+
"rstrip": false,
|
720 |
+
"single_word": false,
|
721 |
+
"special": false
|
722 |
+
},
|
723 |
+
"50342": {
|
724 |
+
"content": "[unused57]",
|
725 |
+
"lstrip": false,
|
726 |
+
"normalized": true,
|
727 |
+
"rstrip": false,
|
728 |
+
"single_word": false,
|
729 |
+
"special": false
|
730 |
+
},
|
731 |
+
"50343": {
|
732 |
+
"content": "[unused58]",
|
733 |
+
"lstrip": false,
|
734 |
+
"normalized": true,
|
735 |
+
"rstrip": false,
|
736 |
+
"single_word": false,
|
737 |
+
"special": false
|
738 |
+
},
|
739 |
+
"50344": {
|
740 |
+
"content": "[unused59]",
|
741 |
+
"lstrip": false,
|
742 |
+
"normalized": true,
|
743 |
+
"rstrip": false,
|
744 |
+
"single_word": false,
|
745 |
+
"special": false
|
746 |
+
},
|
747 |
+
"50345": {
|
748 |
+
"content": "[unused60]",
|
749 |
+
"lstrip": false,
|
750 |
+
"normalized": true,
|
751 |
+
"rstrip": false,
|
752 |
+
"single_word": false,
|
753 |
+
"special": false
|
754 |
+
},
|
755 |
+
"50346": {
|
756 |
+
"content": "[unused61]",
|
757 |
+
"lstrip": false,
|
758 |
+
"normalized": true,
|
759 |
+
"rstrip": false,
|
760 |
+
"single_word": false,
|
761 |
+
"special": false
|
762 |
+
},
|
763 |
+
"50347": {
|
764 |
+
"content": "[unused62]",
|
765 |
+
"lstrip": false,
|
766 |
+
"normalized": true,
|
767 |
+
"rstrip": false,
|
768 |
+
"single_word": false,
|
769 |
+
"special": false
|
770 |
+
},
|
771 |
+
"50348": {
|
772 |
+
"content": "[unused63]",
|
773 |
+
"lstrip": false,
|
774 |
+
"normalized": true,
|
775 |
+
"rstrip": false,
|
776 |
+
"single_word": false,
|
777 |
+
"special": false
|
778 |
+
},
|
779 |
+
"50349": {
|
780 |
+
"content": "[unused64]",
|
781 |
+
"lstrip": false,
|
782 |
+
"normalized": true,
|
783 |
+
"rstrip": false,
|
784 |
+
"single_word": false,
|
785 |
+
"special": false
|
786 |
+
},
|
787 |
+
"50350": {
|
788 |
+
"content": "[unused65]",
|
789 |
+
"lstrip": false,
|
790 |
+
"normalized": true,
|
791 |
+
"rstrip": false,
|
792 |
+
"single_word": false,
|
793 |
+
"special": false
|
794 |
+
},
|
795 |
+
"50351": {
|
796 |
+
"content": "[unused66]",
|
797 |
+
"lstrip": false,
|
798 |
+
"normalized": true,
|
799 |
+
"rstrip": false,
|
800 |
+
"single_word": false,
|
801 |
+
"special": false
|
802 |
+
},
|
803 |
+
"50352": {
|
804 |
+
"content": "[unused67]",
|
805 |
+
"lstrip": false,
|
806 |
+
"normalized": true,
|
807 |
+
"rstrip": false,
|
808 |
+
"single_word": false,
|
809 |
+
"special": false
|
810 |
+
},
|
811 |
+
"50353": {
|
812 |
+
"content": "[unused68]",
|
813 |
+
"lstrip": false,
|
814 |
+
"normalized": true,
|
815 |
+
"rstrip": false,
|
816 |
+
"single_word": false,
|
817 |
+
"special": false
|
818 |
+
},
|
819 |
+
"50354": {
|
820 |
+
"content": "[unused69]",
|
821 |
+
"lstrip": false,
|
822 |
+
"normalized": true,
|
823 |
+
"rstrip": false,
|
824 |
+
"single_word": false,
|
825 |
+
"special": false
|
826 |
+
},
|
827 |
+
"50355": {
|
828 |
+
"content": "[unused70]",
|
829 |
+
"lstrip": false,
|
830 |
+
"normalized": true,
|
831 |
+
"rstrip": false,
|
832 |
+
"single_word": false,
|
833 |
+
"special": false
|
834 |
+
},
|
835 |
+
"50356": {
|
836 |
+
"content": "[unused71]",
|
837 |
+
"lstrip": false,
|
838 |
+
"normalized": true,
|
839 |
+
"rstrip": false,
|
840 |
+
"single_word": false,
|
841 |
+
"special": false
|
842 |
+
},
|
843 |
+
"50357": {
|
844 |
+
"content": "[unused72]",
|
845 |
+
"lstrip": false,
|
846 |
+
"normalized": true,
|
847 |
+
"rstrip": false,
|
848 |
+
"single_word": false,
|
849 |
+
"special": false
|
850 |
+
},
|
851 |
+
"50358": {
|
852 |
+
"content": "[unused73]",
|
853 |
+
"lstrip": false,
|
854 |
+
"normalized": true,
|
855 |
+
"rstrip": false,
|
856 |
+
"single_word": false,
|
857 |
+
"special": false
|
858 |
+
},
|
859 |
+
"50359": {
|
860 |
+
"content": "[unused74]",
|
861 |
+
"lstrip": false,
|
862 |
+
"normalized": true,
|
863 |
+
"rstrip": false,
|
864 |
+
"single_word": false,
|
865 |
+
"special": false
|
866 |
+
},
|
867 |
+
"50360": {
|
868 |
+
"content": "[unused75]",
|
869 |
+
"lstrip": false,
|
870 |
+
"normalized": true,
|
871 |
+
"rstrip": false,
|
872 |
+
"single_word": false,
|
873 |
+
"special": false
|
874 |
+
},
|
875 |
+
"50361": {
|
876 |
+
"content": "[unused76]",
|
877 |
+
"lstrip": false,
|
878 |
+
"normalized": true,
|
879 |
+
"rstrip": false,
|
880 |
+
"single_word": false,
|
881 |
+
"special": false
|
882 |
+
},
|
883 |
+
"50362": {
|
884 |
+
"content": "[unused77]",
|
885 |
+
"lstrip": false,
|
886 |
+
"normalized": true,
|
887 |
+
"rstrip": false,
|
888 |
+
"single_word": false,
|
889 |
+
"special": false
|
890 |
+
},
|
891 |
+
"50363": {
|
892 |
+
"content": "[unused78]",
|
893 |
+
"lstrip": false,
|
894 |
+
"normalized": true,
|
895 |
+
"rstrip": false,
|
896 |
+
"single_word": false,
|
897 |
+
"special": false
|
898 |
+
},
|
899 |
+
"50364": {
|
900 |
+
"content": "[unused79]",
|
901 |
+
"lstrip": false,
|
902 |
+
"normalized": true,
|
903 |
+
"rstrip": false,
|
904 |
+
"single_word": false,
|
905 |
+
"special": false
|
906 |
+
},
|
907 |
+
"50365": {
|
908 |
+
"content": "[unused80]",
|
909 |
+
"lstrip": false,
|
910 |
+
"normalized": true,
|
911 |
+
"rstrip": false,
|
912 |
+
"single_word": false,
|
913 |
+
"special": false
|
914 |
+
},
|
915 |
+
"50366": {
|
916 |
+
"content": "[unused81]",
|
917 |
+
"lstrip": false,
|
918 |
+
"normalized": true,
|
919 |
+
"rstrip": false,
|
920 |
+
"single_word": false,
|
921 |
+
"special": false
|
922 |
+
},
|
923 |
+
"50367": {
|
924 |
+
"content": "[unused82]",
|
925 |
+
"lstrip": false,
|
926 |
+
"normalized": true,
|
927 |
+
"rstrip": false,
|
928 |
+
"single_word": false,
|
929 |
+
"special": false
|
930 |
+
}
|
931 |
+
},
|
932 |
+
"additional_special_tokens": [
|
933 |
+
"<|padding|>",
|
934 |
+
"<|endoftext|>",
|
935 |
+
"[UNK]",
|
936 |
+
"[CLS]",
|
937 |
+
"[SEP]",
|
938 |
+
"[PAD]",
|
939 |
+
"[MASK]"
|
940 |
+
],
|
941 |
+
"clean_up_tokenization_spaces": true,
|
942 |
+
"cls_token": "[CLS]",
|
943 |
+
"extra_special_tokens": {},
|
944 |
+
"mask_token": "[MASK]",
|
945 |
+
"max_length": 2048,
|
946 |
+
"model_input_names": [
|
947 |
+
"input_ids",
|
948 |
+
"attention_mask"
|
949 |
+
],
|
950 |
+
"model_max_length": 8192,
|
951 |
+
"pad_to_multiple_of": null,
|
952 |
+
"pad_token": "[PAD]",
|
953 |
+
"pad_token_type_id": 0,
|
954 |
+
"padding_side": "right",
|
955 |
+
"sep_token": "[SEP]",
|
956 |
+
"stride": 0,
|
957 |
+
"tokenizer_class": "PreTrainedTokenizer",
|
958 |
+
"truncation_side": "right",
|
959 |
+
"truncation_strategy": "longest_first",
|
960 |
+
"unk_token": "[UNK]"
|
961 |
+
}
|