Datasets:
nkasmanoff
/
huggingface-datasets

Dataset card Data Studio Files Community
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PoolC/3-fold-clone-detection-600k-5fold
false
[]
null
2
0
PoolC/4-fold-clone-detection-600k-5fold
false
[]
null
1
0
PoolC/5-fold-clone-detection-600k-5fold
false
[]
null
2
0
gary109/onset-chord_corpora_parliament_processed
false
[]
null
0
0
clementgyj/FNLP
false
[]
null
0
0
da3m0n/pln
false
[]
null
0
0
OneFly/NER
false
[]
null
0
0
martaculla/Rubrix
false
[]
null
0
0
tomekkorbak/pile-debug-value-test
false
[]
null
0
0
enwik8
false
[ "task_categories:fill-mask", "task_categories:text-generation", "task_ids:language-modeling", "task_ids:masked-language-modeling", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "license:mit" ]
The dataset is based on the Hutter Prize (http://prize.hutter1.net) and contains the first 10^8 bytes of English Wikipedia in 2006 in XML
1,129
3
Taeham/wav2vec2-ksponspeech-train
false
[]
null
0
0
tomekkorbak/python-github-code
false
[]
null
4
1
dianalogan/Marketing-Budget-and-Actual-Sales-Dataset
false
[ "task_ids:intent-classification", "task_ids:multi-class-classification", "task_ids:sentiment-classification", "annotations_creators:diana_logan", "multilinguality:monolingual", "source_datasets:other-generated-datasets", "language:en", "license:apache-2.0", "arxiv:2010.12421" ]
null
1
0
tomekkorbak/pile-toxicity-balanced3-with-values
false
[]
null
0
0
STAM/agricore-datasets
false
[]
null
0
0
cestwc/assumptions
false
[]
null
0
0
binaya-s/en_corpora_parliament_processed
false
[]
null
0
0
alejandro7548/Rubrix
false
[]
null
0
0
flxclxc/cellock_data
false
[]
null
1
0
Non-Residual-Prompting/common_gen_dev2
false
[]
null
0
0
Nurseiit/nedzhi
false
[ "license:agpl-3.0" ]
This dataset is for evaluating the performance of intent classification systems in the presence of "out-of-scope" queries. By "out-of-scope", we mean queries that do not fall into any of the system-supported intent classes. Most datasets include only data that is "in-scope". Our dataset includes both in-scope and out-of-scope data. You might also know the term "out-of-scope" by other terms, including "out-of-domain" or "out-of-distribution".
0
0
Splend1dchan/NMSQA_testupload
false
[]
null
0
0
Attention/mailabs_fyw
false
[]
null
0
0
Splend1dchan/NMSQA_testupload2
false
[]
null
0
0
LeboNLP/toxic-natural-utterances
false
[]
null
0
0
koudeheld/beatles_lyrics
false
[]
null
0
0
DWFlanagan/sentiment-banking
false
[]
null
0
0
koudeheld/beatles_lyrics_dict
false
[]
null
0
0
spasis/datasets-github-issues-2
false
[]
null
0
0
lmqg/qg_squadshifts
false
[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:subjqa", "language:en", "license:cc-by-4.0", "question-generation", "arxiv:2210.03992" ]
[SQuAD Shifts](https://modestyachts.github.io/squadshifts-website/index.html) dataset for question generation (QG) task.
247
1
marwansalam/semeval
false
[]
null
0
0
benwri/GaryOut
false
[]
null
0
0
lmqg/qg_esquad
false
[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:squad_es", "language:es", "license:cc-by-4.0", "question-generation", "arxiv:2210.03992" ]
[SQuAD-es](https://huggingface.co/datasets/squad_es) dataset for question generation (QG) task.
1,295
0
lmqg/qg_koquad
false
[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:squad_es", "language:ko", "license:cc-by-4.0", "question-generation", "arxiv:2210.03992" ]
[KorQuAD](https://huggingface.co/datasets/squad_kor_v1) dataset for question generation (QG) task.
2,423
0
lmqg/qg_ruquad
false
[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:deepset/germanquad", "language:ru", "license:cc-by-4.0", "question-generation", "arxiv:2210.03992" ]
[SberSQuAD](https://huggingface.co/datasets/sberquad) dataset for question generation (QG) task.
1,897
1
lmqg/qg_itquad
false
[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:squad_es", "language:it", "license:cc-by-4.0", "question-generation", "arxiv:2210.03992" ]
[SQuAD-it](https://huggingface.co/datasets/squad_it) dataset for question generation (QG) task.
1,308
1
lmqg/qg_dequad
false
[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:deepset/germanquad", "language:de", "license:cc-by-4.0", "question-generation", "arxiv:2210.03992" ]
[GermanSQuAD](https://huggingface.co/datasets/deepset/germanquad) dataset for question generation (QG) task.
118
0
juanastudillo/datos_caudal
false
[ "license:mit" ]
null
2
0
mehnaazasad/arxiv-co-ga
false
[ "arxiv:1905.00075" ]
null
0
0
Vlasta/human_cdna
false
[]
null
0
0
theJainuineGuy/ravdess_test
false
[]
null
0
0
AlixCF/sample
false
[ "license:cc" ]
null
0
0
amartyobanerjee/github-issues
false
[]
null
0
0
cmotions/Beatles_lyrics
false
[ "language:en", "language modeling" ]
null
0
3
flxclxc/cellock_embeddings
false
[]
null
0
0
flxclxc/cellock_data_with_embeddings
false
[]
null
0
0
wgolding/test2
false
[ "license:apache-2.0" ]
null
0
0
juancavallotti/bea-19-corruption
false
[]
null
0
0
NLPC-UOM/Travel-Dataset-5000
false
[ "language:en", "license:mit" ]
null
4
2
NLPC-UOM/Sinhala-short-sentences
false
[ "language:si", "license:mit" ]
null
4
0
NLPC-UOM/Sinhala-news-clustering
false
[ "language:si", "license:mit" ]
null
0
0
NLPC-UOM/sinhala-sentiment-lexicon-generation
false
[ "language:si", "license:mit" ]
null
0
0
NLPC-UOM/Sinhala-Neuspellcorrector
false
[ "language:si", "license:mit" ]
null
0
0
NLPC-UOM/Tamil-Sinhala-short-sentence-similarity-deep-learning
false
[ "language:ta", "language:si", "license:mit" ]
null
0
0
NLPC-UOM/Sentiment-tagger
false
[ "language:si", "license:mit" ]
null
0
0
PLN-Activdad-2/sentiment-banking
false
[]
null
0
0
yanekyuk/wikikey-fr
false
[ "language:fr" ]
null
0
0
limsc/mlm-tapt-requirements
false
[]
null
0
0
limsc/fr-nfr-classification
false
[]
null
0
0
limsc/req-subclass-classification
false
[]
null
0
0
limsc/mlm-dapt-aeroastro
false
[]
null
0
0
awghuku/infore25
false
[ "license:cc-by-4.0" ]
null
0
0
crystina-z/mmarco-train
false
[]
mMARCO translated datasets
19
0
anton-l/earnings22
false
[ "license:cc-by-sa-4.0" ]
The Earnings 22 dataset ( also referred to as earnings22 ) is a 119-hour corpus of English-language earnings calls collected from global companies. The primary purpose is to serve as a benchmark for industrial and academic automatic speech recognition (ASR) models on real-world accented speech.
5
0
DaniDelgon/sentiment-banking
false
[]
null
0
0
DaniDelgon/rubrix
false
[]
null
0
0
cakiki/fr_wikipedia_unigrams
false
[]
null
0
0
arbml/metrecv2
false
[]
\
0
0
TheoMrc/Zebrafish-AChE-Staining
false
[]
null
0
0
cakiki/es_wikipedia_unigrams
false
[]
null
0
0
pqknasvquolylkvlic/sentiment-banking
false
[]
null
0
0
eduu16/Rubrix
false
[]
null
0
0
juancavallotti/english-gec-tatoeba
false
[]
null
0
0
cakiki/ar_wikipedia_unigrams
false
[]
null
0
0
AlekseyKorshuk/persona-chat
false
[]
null
74
4
cakiki/bn_wikipedia_unigrams
false
[]
null
0
0
AllenGeng/OCaml_program_corpus
false
[]
null
0
0
taesiri/GamePhysics
false
[ "license:creativeml-openrail-m", "arxiv:2203.11096" ]
GamePhysics dataset
0
2
juancavallotti/bea-19-fine-tune
false
[]
null
0
0
alexyanchag/demo
false
[ "license:other" ]
null
0
0
shpotes/pathfinder
false
[ "license:apache-2.0" ]
null
0
0
wql/UIE_demo
false
[]
null
0
0
cakiki/en_wikipedia_unigrams
false
[]
null
0
0
cakiki/en_wikipedia_bigrams
false
[]
null
0
0
buio/heart-disease
false
[ "structured-data", "tabular-data", "classification" ]
null
13
0
cakiki/fr_wikipedia_bigrams
false
[]
null
0
0
cakiki/fr_wikipedia_trigrams
false
[ "language:fr" ]
null
0
0
BlackSamorez/2ch_b_dialogues
false
[ "task_categories:conversational", "task_ids:dialogue-generation", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:ru" ]
Dialogues build from 2ch.hk/b/ threads
53
3
BeIR/fiqa
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
367
1
BeIR/trec-covid
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
556
0
carblacac/twitter-sentiment-analysis
false
[ "task_categories:text-classification", "annotations_creators:expert-generated", "language_creators:other", "multilinguality:monolingual", "size_categories:100K<n<1M", "source_datasets:original", "language:en", "license:apache-2.0" ]
The Twitter Sentiment Analysis Dataset contains 1,578,627 classified tweets, each row is marked as 1 for positive sentiment and 0 for negative sentiment. The dataset is based on data from the following two sources: University of Michigan Sentiment Analysis competition on Kaggle Twitter Sentiment Corpus by Niek Sanders Finally, I randomly selected a subset of them, applied a cleaning process, and divided them between the test and train subsets, keeping a balance between the number of positive and negative tweets within each of these subsets.
632
4
BeIR/trec-covid-qrels
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
86
0
BeIR/scifact
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
278
0
BeIR/nfcorpus
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
190
0
BeIR/msmarco
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
987
0
BeIR/nq
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
20
0
BeIR/hotpotqa
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
293
1
BeIR/arguana
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
266
0
BeIR/webis-touche2020
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
46
0
BeIR/quora
false
[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0" ]
null
70
0