Datasets:
nkasmanoff
/
huggingface-datasets

Dataset card Data Studio Files Community
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masakhane/masakhanews
false
[ "task_categories:text-classification", "task_ids:topic-classification", "annotations_creators:expert-generated", "language_creators:expert-generated", "multilinguality:multilingual", "size_categories:1K<n<10K", "source_datasets:original", "language:am", "language:en", "language:fr", "language:ha", "language:ig", "language:ln", "language:lg", "language:om", "language:pcm", "language:rn", "language:sn", "language:so", "language:sw", "language:ti", "language:xh", "language:yo", "license:afl-3.0", "news-topic", "masakhanews", "masakhane" ]
MasakhaNEWS is the largest publicly available dataset for news topic classification in 16 languages widely spoken in Africa. The languages are: - Amharic (amh) - English (eng) - French (fra) - Hausa (hau) - Igbo (ibo) - Lingala (lin) - Luganda (lug) - Oromo (orm) - Nigerian Pidgin (pcm) - Rundi (run) - chShona (sna) - Somali (som) - Kiswahili (swą) - Tigrinya (tir) - isiXhosa (xho) - Yorùbá (yor) The train/validation/test sets are available for all the 16 languages. For more details see *** arXiv link **
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chronbmm/sanskrit-sandhi-split-sighum
false
[]
null
0
0
chronbmm/sanskrit-sandhi-split-hackathon
false
[]
null
0
0
ZeroUnbound/kodayuapril
false
[]
null
0
0
jasperan/redbull-analytics-hol
false
[ "license:gpl-3.0" ]
null
0
0
distilled-one-sec-cv12/chunk_190
false
[]
null
0
0
vincha77/generadai-sample-tutorial
false
[]
null
0
0
distilled-one-sec-cv12/chunk_189
false
[]
null
0
0
distilled-one-sec-cv12/chunk_191
false
[]
null
0
0
mprzymus/osm_tiles_small
false
[]
null
0
0
TeraSpace/glados_ru_fred_tune
false
[ "task_categories:text-generation", "language:ru", "license:mit" ]
null
0
0
Kanike54/cagliostro-colab-ui
false
[]
null
0
0
SHS/cancer_test_data2
false
[]
null
0
0
thewall/Aptani2Param
false
[ "license:openrail" ]
null
0
0
casey-martin/oa_cpp_annotate_gen
false
[ "task_categories:question-answering", "task_categories:text-classification", "language:en" ]
null
0
0
Ayane22/asami
false
[]
null
0
0
hieunguyen1053/vsec
false
[]
null
0
0
ACCA225/111
false
[]
null
0
0
Grop/1
false
[]
null
0
0
doushabao4766/weibo_ner_knowledge_V3
false
[]
null
0
0
EdwardLin2023/MELD-Audio
false
[ "license:cc-by-4.0" ]
Multimodal EmotionLines Dataset (MELD) has been created by enhancing and extending EmotionLines dataset. MELD contains the same dialogue instances available in EmotionLines, but it also encompasses audio and visual modality along with text. MELD has more than 1400 dialogues and 13000 utterances from Friends TV series. Multiple speakers participated in the dialogues. Each utterance in a dialogue has been labeled by any of these seven emotions -- Anger, Disgust, Sadness, Joy, Neutral, Surprise and Fear. MELD also has sentiment (positive, negative and neutral) annotation for each utterance. This dataset is slightly modified, so that it concentrates on Emotion recognition in audio input only.
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Vincent-luo/hagrid50k
false
[]
null
0
0
chronbmm/vedic-dependency-parsing
false
[]
null
0
0
miausdioa/mijulkaromana
false
[ "license:other" ]
null
0
0
b-mc2/sql-create-context
false
[ "task_categories:text-generation", "task_categories:question-answering", "task_categories:table-question-answering", "size_categories:10K<n<100K", "language:en", "license:cc-by-4.0", "SQL", "code", "NLP", "text-to-sql", "context-sql", "spider", "wikisql", "sqlglot" ]
null
0
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chetahy0711/CS6301_sampledata
false
[]
null
0
0
Spico/ChCatExt
false
[ "language:zh", "license:apache-2.0", "finance" ]
null
0
0
Zerenidel/kodayuapril
false
[]
null
0
0
chunpingvi/audio_1
false
[]
null
0
0
nRuaif/Vietnamese_x_Alpaca
false
[ "license:mit" ]
null
0
2
markkerzner/cool_new_dataset
false
[]
null
0
0
ethers/cat-waifu-datasets
false
[]
null
0
0
JerryMo/db-simpsons-dataset
false
[]
null
0
0
strictiondbloodsugar/StrictionDBloodSugarReviews
false
[]
null
0
0
quocanh34/youtube_dataset_wer_10
false
[]
null
0
0
hypeFit/HypeFit
false
[]
null
0
0
nuveiskintagremoval/SharkTankSkinTagRemover
false
[]
null
0
0
minxdragon/ddpm-butterflies-128
false
[ "license:apache-2.0" ]
null
0
0
quocanh34/youtube_dataset_wer_0
false
[]
null
0
0
bigcode/commits-8192
false
[]
null
0
0
korean-corpus/namu_wiki
false
[]
null
0
0
thewall/Simulation
false
[ "license:openrail" ]
null
0
0
ParisNeo/GPT4All-Community-Discussions
false
[ "task_categories:conversational", "language:en", "language:fr", "language:de", "language:ar", "language:it", "language:es", "license:apache-2.0" ]
null
0
0
lponsard/admCom
false
[]
null
0
0
Phonecharger/news-programmatic-labeling
false
[]
null
0
0
rika22/pretrained
false
[]
null
0
0
Circularmachines/batch_indexing_machine_720f_768px
false
[]
null
0
0
distilled-one-sec-cv12/chunk_197
false
[]
null
0
0
distilled-one-sec-cv12/chunk_200
false
[]
null
0
0
Maadhu/allenai
false
[]
null
0
0
carnival13/hpqa-fid-input
false
[]
null
0
0
distilled-one-sec-cv12/chunk_194
false
[]
null
0
0
sdasdadas/food
false
[]
null
0
0
distilled-one-sec-cv12/chunk_195
false
[]
null
0
0
ruanchaves/assin2_por_Latn_to_eng_Latn
false
[]
null
0
0
ruanchaves/rerelem_por_Latn_to_eng_Latn
false
[]
null
0
0
ruanchaves/porsimplessent_por_Latn_to_eng_Latn
false
[]
null
0
0
distilled-one-sec-cv12/chunk_198
false
[]
null
0
0
13GP/training
false
[ "license:mit" ]
null
0
0
distilled-one-sec-cv12/chunk_201
false
[]
null
0
0
FASOXO/Kaggle-and-colab-NoveAI-Stabled-diffusion-ipynb
false
[ "license:openrail" ]
null
0
1
distilled-one-sec-cv12/chunk_199
false
[]
null
0
0
distilled-one-sec-cv12/chunk_192
false
[]
null
0
0
distilled-one-sec-cv12/chunk_196
false
[]
null
0
0
Laskari-Naveen/donut_800
false
[]
null
0
0
aravind-selvam/chart_processed_512
false
[ "license:mit" ]
null
0
0
marasama/nva-yorktown
false
[]
null
0
0
distilled-one-sec-cv12/chunk_202
false
[]
null
0
0
Haribert/your-dataset-name
false
[]
null
0
0
jkot/parliament_hearings_processed
false
[]
null
0
0
prajwalsahu5/smiles40m
false
[]
null
0
0
BrunoHays/ESLO
false
[ "task_categories:automatic-speech-recognition", "language:fr", "license:cc-by-nc-4.0" ]
ESLO dataset, each utterance are taken out individually
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0
saivn98/Sd-webui
false
[]
null
0
0
prajwalsahu5/smiles4m
false
[]
null
0
0
reginaboateng/pubmed_long_tokenised
false
[]
null
0
0
distilled-one-sec-cv12/chunk_204
false
[]
null
0
0
distilled-one-sec-cv12/chunk_205
false
[]
null
0
0
marasama/nva-kuroneko
false
[]
null
0
0
distilled-one-sec-cv12/chunk_206
false
[]
null
0
0
fuwlstudioab/test
false
[ "license:cc-by-nc-sa-2.0" ]
null
0
0
distilled-one-sec-cv12/chunk_208
false
[]
null
0
0
distilled-one-sec-cv12/chunk_203
false
[]
null
0
0
distilled-one-sec-cv12/chunk_210
false
[]
null
0
0
distilled-one-sec-cv12/chunk_207
false
[]
null
0
0
distilled-one-sec-cv12/chunk_209
false
[]
null
0
0
tejasbale02/friends-s03
false
[]
null
0
0
LevMuchnik/SupremeCourtOfIsrael
false
[ "size_categories:100K<n<1M", "language:he", "license:openrail", "legal, verdicts, metadata" ]
null
0
0
chilge/vits
false
[]
null
0
0
distilled-one-sec-cv12/chunk_211
false
[]
null
0
0
distilled-one-sec-cv12/chunk_212
false
[]
null
0
0
carnival13/hpqa-fid-input-wo-sp
false
[]
null
0
0
factored/fr_crawler2
false
[]
null
0
0
sander-wood/wikimusictext
false
[ "task_categories:text-classification", "task_categories:text2text-generation", "size_categories:1K<n<10K", "language:en", "license:mit", "music", "arxiv:2304.11029" ]
null
0
0
nouman-10/americas_nlp_quy_everything
false
[]
null
0
0
lighteval/mutual
false
[]
null
0
0
lighteval/mutual_plus
false
[]
null
0
0
lighteval/ThePileEval
false
[]
null
0
0
slvnwhrl/tenkgnad-clustering-s2s
false
[ "size_categories:10K<n<100K", "language:de", "license:cc-by-nc-sa-4.0", "embeddings", "clustering", "benchmark", "arxiv:2210.07316" ]
null
0
0
slvnwhrl/tenkgnad-clustering-p2p
false
[ "size_categories:10K<n<100K", "language:de", "license:cc-by-nc-sa-4.0", "embeddings", "clustering", "benchmark", "arxiv:2210.07316" ]
null
0
0
renumics/speech_commands_enriched
false
[ "license:apache-2.0" ]
This is a set of one-second .wav audio files, each containing a single spoken English word or background noise. These words are from a small set of commands, and are spoken by a variety of different speakers. This data set is designed to help train simple machine learning models. This dataset is covered in more detail at [https://arxiv.org/abs/1804.03209](https://arxiv.org/abs/1804.03209). Version 0.01 of the data set (configuration `"v0.01"`) was released on August 3rd 2017 and contains 64,727 audio files. In version 0.01 thirty different words were recoded: "Yes", "No", "Up", "Down", "Left", "Right", "On", "Off", "Stop", "Go", "Zero", "One", "Two", "Three", "Four", "Five", "Six", "Seven", "Eight", "Nine", "Bed", "Bird", "Cat", "Dog", "Happy", "House", "Marvin", "Sheila", "Tree", "Wow". In version 0.02 more words were added: "Backward", "Forward", "Follow", "Learn", "Visual". In both versions, ten of them are used as commands by convention: "Yes", "No", "Up", "Down", "Left", "Right", "On", "Off", "Stop", "Go". Other words are considered to be auxiliary (in current implementation it is marked by `True` value of `"is_unknown"` feature). Their function is to teach a model to distinguish core words from unrecognized ones. The `_silence_` class contains a set of longer audio clips that are either recordings or a mathematical simulation of noise.
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