Datasets:
nkasmanoff
/
huggingface-datasets

Dataset card Data Studio Files Community
id
stringlengths
2
115
private
bool
1 class
tags
list
description
stringlengths
0
5.93k
⌀
downloads
int64
0
1.14M
likes
int64
0
1.79k
GEM-submissions/lewtun__this-is-a-test__1647247409
false
[ "benchmark:gem", "evaluation", "benchmark" ]
null
0
0
EMBO/BLURB
false
[ "task_categories:question-answering", "task_categories:token-classification", "task_categories:sentence-similarity", "task_categories:text-classification", "task_ids:closed-domain-qa", "task_ids:named-entity-recognition", "task_ids:parsing", "task_ids:semantic-similarity-scoring", "task_ids:text-scoring", "task_ids:topic-classification", "annotations_creators:expert-generated", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "license:apache-2.0", "arxiv:2007.15779", "arxiv:1909.06146" ]
null
301
2
Jiejie/asr_book_lm_v2.0
false
[]
null
0
0
GEM-submissions/lewtun__this-is-a-test__1647256250
false
[ "benchmark:gem", "evaluation", "benchmark" ]
null
0
0
wikitablequestions
false
[ "task_categories:question-answering", "annotations_creators:crowdsourced", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "license:cc-by-4.0", "table-question-answering", "arxiv:1508.00305" ]
This WikiTableQuestions dataset is a large-scale dataset for the task of question answering on semi-structured tables.
302
6
gimmaru/github-issues
false
[ "arxiv:2005.00614" ]
null
0
0
GEM-submissions/lewtun__this-is-a-test__1647263213
false
[ "benchmark:gem", "evaluation", "benchmark" ]
null
0
0
marsyas/gtzan
false
[]
GTZAN is a dataset for musical genre classification of audio signals. The dataset consists of 1,000 audio tracks, each of 30 seconds long. It contains 10 genres, each represented by 100 tracks. The tracks are all 22,050Hz Mono 16-bit audio files in WAV format. The genres are: blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, and rock.
1
0
GEM/xwikis
false
[ "task_categories:summarization", "annotations_creators:found", "language_creators:unknown", "multilinguality:unknown", "size_categories:unknown", "source_datasets:original", "language:de", "language:en", "language:fr", "language:cs", "license:cc-by-sa-4.0", "arxiv:2202.09583" ]
The XWikis Corpus (Perez-Beltrachini and Lapata, 2021) provides datasets with different language pairs and directions for cross-lingual abstractive document summarisation. This current version includes four languages: English, German, French, and Czech. The dataset is derived from Wikipedia. It is based on the observation that for a Wikipedia title, the lead section provides an overview conveying salient information, while the body provides detailed information. It thus assumes the body and lead paragraph as a document-summary pair. Furthermore, as a Wikipedia title can be associated with Wikipedia articles in various languages, 1) Wikipedia’s Interlanguage Links are used to find titles across languages and 2) given any two related Wikipedia titles, e.g., Huile d’Olive (French) and Olive Oil (English), the lead paragraph from one title is paired with the body of the other to derive cross-lingual pairs.
21
2
lvwerra/my_test
false
[]
null
0
0
lvwerra/my_test_2
false
[]
null
0
0
Jiejie/asr_book_lm_v2.1
false
[]
null
0
0
cgarciae/cartoonset
false
[ "size_categories:10K<n<100K", "license:cc-by-4.0", "arxiv:1711.05139" ]
Cartoon Set is a collection of random, 2D cartoon avatar images. The cartoons vary in 10 artwork categories, 4 color categories, and 4 proportion categories, with a total of ~1013 possible combinations. We provide sets of 10k and 100k randomly chosen cartoons and labeled attributes.
25
11
PradeepReddyThathireddy/Inspiring_Content_Detection_Dataset
false
[]
null
0
0
conll2012_ontonotesv5
false
[ "task_categories:token-classification", "task_ids:named-entity-recognition", "task_ids:part-of-speech", "task_ids:coreference-resolution", "task_ids:parsing", "task_ids:lemmatization", "task_ids:word-sense-disambiguation", "annotations_creators:expert-generated", "language_creators:found", "multilinguality:multilingual", "size_categories:10K<n<100K", "source_datasets:original", "language:ar", "language:en", "language:zh", "license:cc-by-nc-nd-4.0", "semantic-role-labeling" ]
OntoNotes v5.0 is the final version of OntoNotes corpus, and is a large-scale, multi-genre, multilingual corpus manually annotated with syntactic, semantic and discourse information. This dataset is the version of OntoNotes v5.0 extended and is used in the CoNLL-2012 shared task. It includes v4 train/dev and v9 test data for English/Chinese/Arabic and corrected version v12 train/dev/test data (English only). The source of data is the Mendeley Data repo [ontonotes-conll2012](https://data.mendeley.com/datasets/zmycy7t9h9), which seems to be as the same as the official data, but users should use this dataset on their own responsibility. See also summaries from paperwithcode, [OntoNotes 5.0](https://paperswithcode.com/dataset/ontonotes-5-0) and [CoNLL-2012](https://paperswithcode.com/dataset/conll-2012-1) For more detailed info of the dataset like annotation, tag set, etc., you can refer to the documents in the Mendeley repo mentioned above.
2,048
17
anjandash/java-8m-methods-v2
false
[ "multilinguality:monolingual", "language:java", "license:mit" ]
null
0
0
victor/autonlp-data-tweet-sentiment
false
[ "task_categories:text-classification", "language:en" ]
null
0
0
agemagician/uniref50
false
[]
null
4,605
0
hazal/Turkish-Biomedical-corpus-trM
false
[ "language:tr" ]
null
0
2
rubrix/go_emotions_training
false
[]
null
2
0
Jiejie/asr_book_lm_v2.3
false
[]
null
0
0
malteos/paperswithcode-aspects
false
[]
Papers with aspects from paperswithcode.com dataset
0
0
kSaluja/tokens_data
false
[]
null
0
0
Dayyan/bwns
false
[]
null
0
0
Hiruni99/eng-sin-laws-and-acts
false
[]
null
0
0
rubrix/research_titles_multi-label
false
[]
null
8
0
rubrix/go_emotions_multi-label
false
[]
null
4
0
elricwan/roberta-data
false
[]
null
1
0
willcai/wav2vec2_common_voice_accents_3
false
[]
null
0
0
jorge-henao/disco_poetry_spanish
false
[]
null
0
1
gcaillaut/enwiki_el
false
[ "task_categories:other", "annotations_creators:machine-generated", "multilinguality:monolingual", "size_categories:unknown", "source_datasets:original", "language:en-EN", "license:wtfpl" ]
English Wikipedia dataset for Entity Linking
0
0
crabz/stsb-sk
false
[ "task_ids:semantic-similarity-scoring", "annotations_creators:other", "language_creators:other", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:extended|stsb_multi_mt", "language:sk", "license:unknown" ]
null
0
0
mfleck/german_extracted_text
false
[]
null
0
0
ebrigham/agnewsadapted
false
[]
AG is a collection of more than 1 million news articles. News articles have been gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of activity. ComeToMyHead is an academic news search engine which has been running since July, 2004. The dataset is provided by the academic comunity for research purposes in data mining (clustering, classification, etc), information retrieval (ranking, search, etc), xml, data compression, data streaming, and any other non-commercial activity. For more information, please refer to the link http://www.di.unipi.it/~gulli/AG_corpus_of_news_articles.html . The AG's news topic classification dataset is constructed by Xiang Zhang ([email protected]) from the dataset above. It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).
0
0
yangdong/ecqa
false
[]
null
63
0
davanstrien/newspaper_navigator_people
false
[]
null
0
0
voidful/NMSQA
false
[ "task_categories:question-answering", "task_categories:automatic-speech-recognition", "task_ids:abstractive-qa", "annotations_creators:crowdsourced", "annotations_creators:machine-generated", "language_creators:expert-generated", "language_creators:machine-generated", "language_creators:crowdsourced", "multilinguality:monolingual", "size_categories:unknown", "source_datasets:original", "language:en", "speech-recognition", "arxiv:2203.04911" ]
null
140
3
shpotes/SJTU
false
[]
null
0
0
shpotes/ImVisible
false
[]
This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
0
0
LongNN/news_sum
false
[ "license:gpl-3.0" ]
null
0
0
tomekkorbak/test
false
[]
null
0
0
tomekkorbak/pile-curse-small
false
[]
null
0
0
MatanBenChorin/temp
false
[]
null
0
0
shivam/split-test
false
[]
This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
0
0
rubrix/research_papers_multi-label
false
[]
null
0
1
wietsedv/udpos28
false
[]
Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
532
0
nimaster/autonlp-data-devign_raw_test
false
[ "task_categories:text-classification" ]
null
0
0
anthonny/hate_speech
false
[ "task_categories:text-classification", "task_ids:semantic-similarity-classification", "annotations_creators:found", "language_creators:crowdsourced", "multilinguality:monolingual", "size_categories:unknown", "source_datasets:original", "language:es-EC", "license:unknown" ]
null
1
0
umanlp/xscitldr
false
[]
This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
0
0
nikit91/qald9
false
[]
null
0
0
n6L3/kaggle
false
[ "license:apache-2.0" ]
null
0
0
n6L3/nlp
false
[]
null
0
0
Wang123/codeparrot-train
false
[]
null
0
0
Wang123/codeparrot-valid
false
[]
null
0
0
tomekkorbak/pile-curse-full_test
false
[]
null
0
0
DrishtiSharma/MESD-Processed-Dataset
false
[]
null
0
0
abidlabs/crowdsourced-test3
false
[]
null
0
0
abidlabs/crowdsourced-test4
false
[]
null
0
0
abidlabs/crowdsourced-test5
false
[]
null
0
0
shivam/split
false
[]
null
0
0
mrm8488/test2
false
[ "license:wtfpl" ]
null
0
0
mercerchen/fakenews-jsonl
false
[]
null
0
0
Mionozmi/Ddy
false
[]
null
0
0
franz96521/scientific_papers
false
[]
null
1
0
Paulosdeanllons/ODS_BOE
false
[ "license:afl-3.0" ]
null
0
1
malteos/test-ds
false
[ "task_categories:text-retrieval", "multilinguality:monolingual", "size_categories:unknown", "language:en-US" ]
null
0
0
malteos/test2
false
[ "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "size_categories:100K<n<1M", "source_datasets:original", "language:en", "license:apache-2.0" ]
null
0
0
malteos/aspect-paper-embeddings
false
[]
null
0
0
elena-soare/crawled-ecommerce
false
[]
null
0
0
abdusah/arabic_speech_massive
false
[]
null
1
0
cfilt/iwn_wordlists
false
[ "task_categories:token-classification", "annotations_creators:Shivam Mhaskar, Diptesh Kanojia", "language_creators:found", "multilinguality:monolingual", "size_categories:100K<n<1M", "source_datasets:original", "language:as", "language:bn", "language:mni", "language:gu", "language:hi", "language:kn", "language:ks", "language:kok", "language:ml", "language:mr", "language:or", "language:ne", "language:pa", "language:sa", "language:ta", "language:te", "language:ur", "license:cc-by-nc-sa-4.0", "abbreviation-detection" ]
We provide the unique word list form the IndoWordnet (IWN) knowledge base.
0
2
arun007/mydata
false
[]
null
0
0
tomekkorbak/pile-debug
false
[]
null
0
0
malteos/aspect-paper-metadata
false
[]
null
2
0
hackathon-pln-es/parallel-sentences
false
[]
null
0
0
fofiu/test-dataset
false
[]
null
0
0
indonesian-nlp/eli5_id
false
[]
null
0
1
tomekkorbak/pile-curse-chunk-1
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-0
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-3
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-2
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-5
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-6
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-4
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-16
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-15
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-14
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-13
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-8
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-9
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-20
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-18
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-7
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-24
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-17
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-21
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-22
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-10
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-26
false
[]
null
0
0
tomekkorbak/pile-curse-chunk-11
false
[]
null
0
0