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115
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class | tags
list | description
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5.93k
⌀ | downloads
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1.14M
| likes
int64 0
1.79k
|
|---|---|---|---|---|---|
reallycarlaost/emobank_w | false | []
| null | 0 | 0 |
cestwc/paraphrase | false | []
| null | 0 | 0 |
launch/gov_report_qs | false | [
"task_categories:summarization",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:launch/gov_report",
"language:en",
"license:cc-by-4.0"
]
| GovReport-QS hierarchical question-summary generation dataset.
There are two configs:
- paragraph: paragraph-level annotated data
- document: aggregated paragraph-level annotated data for the same document | 2 | 1 |
Rexhaif/xnli-en-ru | false | []
| null | 4 | 0 |
conceptofmind/pile_hacker_news | false | [
"arxiv:2101.00027"
]
| null | 40 | 1 |
conceptofmind/pile_wikipedia_en | false | [
"arxiv:2101.00027"
]
| null | 6 | 0 |
conceptofmind/pile_open_web_text_2 | false | [
"arxiv:2101.00027"
]
| null | 0 | 0 |
conceptofmind/pile_uspto_backgrounds | false | [
"arxiv:2101.00027"
]
| null | 0 | 0 |
teven/mpww_filtered | false | []
| null | 0 | 0 |
conceptofmind/pile_dm_mathematics | false | [
"arxiv:2101.00027"
]
| null | 5 | 2 |
conceptofmind/pile_open_subtitles | false | [
"arxiv:2101.00027"
]
| null | 0 | 0 |
conceptofmind/pile_project_gutenberg | false | []
| null | 0 | 0 |
zhangqiaobit/tangshi | false | []
| null | 0 | 0 |
sijunhe/thchs30 | false | [
"license:apache-2.0"
]
| null | 0 | 0 |
mesolitica/rumi-jawi | false | [
"task_categories:text2text-generation",
"language:ms",
"conditional-text-generation"
]
| null | 0 | 0 |
myradeng/cs-230-news-v2-test-moderate | false | []
| null | 0 | 0 |
myradeng/cs-230-news-v2-test-liberal | false | []
| null | 4 | 0 |
myradeng/cs-230-news-v2-test-conservative | false | []
| null | 0 | 0 |
NLPC-UOM/document_alignment_dataset-Sinhala-Tamil-English | false | []
| null | 0 | 0 |
breezedeus/cnocr-wx-qr-code | false | [
"license:apache-2.0"
]
| null | 0 | 0 |
NLPC-UOM/sentence_alignment_dataset-Sinhala-Tamil-English | false | []
| null | 0 | 0 |
ekinakyurek/ftrace | false | [
"task_ids:masked-language-modeling",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:TRex",
"source_datasets:Lama",
"language:en",
"license:cc-by-sa-4.0",
"license:cc-by-nc-4.0",
"arxiv:2205.11482"
]
| Factual Tracing Dataset that contains queries and abstracts, and their corresponding ground truth. | 194 | 2 |
nielsr/video-demo | false | []
| null | 0 | 0 |
GEM-submissions/lewtun__this-is-a-test-name__1653295318 | false | [
"benchmark:gem",
"evaluation",
"benchmark"
]
| null | 0 | 0 |
GEM-submissions/lewtun__this-is-a-test-name__1653295430 | false | [
"benchmark:gem",
"evaluation",
"benchmark"
]
| null | 0 | 0 |
reannayang/FL_pavement | false | []
| null | 0 | 0 |
aflah/autotrain-data-Engage | false | []
| null | 0 | 0 |
mteb/emotion | false | [
"language:en"
]
| null | 1,927 | 0 |
teven/mpww_filtered_all_passages | false | []
| null | 0 | 0 |
reannayang/FL_pavement2 | false | []
| null | 0 | 0 |
abdoutony207/en_ar_dt | false | [
"license:other"
]
| null | 2 | 0 |
myradeng/cs-230-news-v3 | false | []
| null | 0 | 0 |
strombergnlp/ara-stance | false | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ar",
"license:cc-by-4.0",
"stance-detection",
"arxiv:2104.13559"
]
| The AraStance dataset contains true and false claims, where each claim is paired with one or more documents. Each claim–article pair has a stance label: agree, disagree, discuss, or unrelated. | 0 | 1 |
elifaltintas/new_mimic | false | []
| null | 0 | 0 |
myradeng/cs-230-news-v3-test-moderate | false | []
| null | 0 | 0 |
myradeng/cs-230-news-v3-test-liberal | false | []
| null | 0 | 0 |
myradeng/cs-230-news-v3-test-conservative | false | []
| null | 0 | 0 |
angerhang/neurips_submission | false | []
| null | 0 | 0 |
cpllab/syntaxgym | false | []
| null | 33 | 0 |
elmurod1202/SimRelUz_semantic_evaluation_dataset | false | []
| null | 0 | 0 |
espnet/Libri-Trans-Spatialized_SLURP-Spatialized_dataset | false | [
"license:cc-by-4.0"
]
| null | 0 | 0 |
jonas/osdg_sdg_data_processed | false | [
"task_categories:text-classification",
"language:en"
]
| null | 0 | 0 |
juliensimon/amazon-shoe-reviews | false | []
| null | 25 | 0 |
resist/l | false | []
| null | 0 | 0 |
statworx/Py150ExceptionClassification | false | [
"license:cc"
]
| null | 0 | 0 |
InfroLab/REBEL-RU | false | [
"license:afl-3.0"
]
| null | 0 | 0 |
bloomberg/entsum | false | []
| null | 1 | 6 |
GroNLP/divemt | false | [
"task_categories:translation",
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"language:it",
"language:vi",
"language:nl",
"language:uk",
"language:tr",
"language:ar",
"license:gpl-3.0",
"arxiv:2205.12215"
]
| DivEMT is the first publicly available post-editing study of Neural Machine Translation (NMT) over a typologically diverse set of target languages. Using a strictly controlled setup, 18 professional translators were instructed to translate or post-edit the same set of English documents into Arabic, Dutch, Italian, Turkish, Ukrainian, and Vietnamese. During the process, their edits, keystrokes, editing times, pauses, and perceived effort were logged, enabling an in-depth, cross-lingual evaluation of NMT quality and its post-editing process. | 327 | 2 |
Aniemore/resd | false | [
"task_categories:audio-classification",
"task_ids:audio-emotion-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ru",
"license:mit"
]
| null | 27 | 3 |
Fhrozen/dcase22_task3 | false | [
"task_categories:audio-classification",
"task_ids:slot-filling",
"annotations_creators:unknown",
"language_creators:unknown",
"size_categories:100K<n<100M",
"source_datasets:unknown",
"license:mit"
]
| null | 0 | 0 |
haml/halml | false | [
"license:apache-2.0"
]
| null | 0 | 0 |
Splend1dchan/NMSQA_features_wav2vec2-large-lv60 | false | []
| null | 0 | 0 |
trashsock/hands-images | false | [
"license:gpl-3.0"
]
| null | 10 | 4 |
Etephyr/Project-Echo | false | [
"license:mit"
]
| null | 2 | 0 |
taln-ls2n/pubmed | false | [
"task_categories:text-generation",
"annotations_creators:unknown",
"language_creators:unknown",
"multilinguality:monolingual",
"size_categories:1k<n<10k",
"language:en",
"license:unknown",
"keyphrase-generation",
"keyphrase-extraction",
"text-mining"
]
| PubMed benchmark dataset for keyphrase extraction and generation. | 0 | 0 |
ajders/machine_translated_cnn_dailymail_da_small | false | [
"task_categories:summarization",
"task_ids:news-articles-summarization",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:translation",
"size_categories:1K<n<10K",
"language:da",
"license:apache-2.0"
]
| null | 4 | 0 |
supermario/autotrain-data-test-auto | false | []
| null | 0 | 0 |
slegalAI/legalquestion | false | []
| null | 1 | 0 |
gzbang/datasetest | false | []
| null | 0 | 0 |
mariosasko/test_push_to_hub | false | []
| null | 0 | 0 |
Aniemore/cedr-m7 | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|cedr",
"language:ru",
"license:mit"
]
| null | 19 | 5 |
arampacha/librispeech39 | false | []
| null | 0 | 0 |
duclee9x/speech_recognition_tdtu | false | []
| null | 0 | 0 |
Voicemod/librispeech40 | false | []
| null | 0 | 1 |
yanekyuk/wikikey-tr | false | []
| null | 0 | 0 |
yanekyuk/wikikey-en | false | []
| null | 0 | 0 |
leo123/squad_posgrados | false | []
| automatic translation of the Stanford Question Answering Dataset (SQuAD) v2 into Spanish | 0 | 0 |
emilylearning/cond_ft_none_on_reddit__prcnt_20__test_run_False__xlm-roberta-base | false | []
| null | 0 | 0 |
dfstrans/elevator_data | false | []
| null | 0 | 0 |
thomasg26/fr_corpora_parliament_processed | false | []
| null | 0 | 0 |
emilylearning/cond_ft_subreddit_on_reddit__prcnt_20__test_run_False__xlm-roberta-base | false | []
| null | 0 | 0 |
emilylearning/cond_ft_none_on_reddit__prcnt_100__test_run_False__xlm-roberta-base | false | []
| null | 0 | 0 |
loubnabnl/repo-images | false | []
| null | 0 | 0 |
nouamanetazi/amazon_polarity | false | []
| null | 0 | 0 |
thomasg26/sv_corpora_parliament_processed | false | []
| null | 0 | 0 |
blinoff/healthcare_facilities_reviews | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:ru"
]
| null | 60 | 0 |
cradle-bio/meltome_cluster_split | false | []
| null | 0 | 1 |
evaluate/media | false | []
| null | 0 | 0 |
meetyildiz/toqad | false | []
| Turkish Question Answering Dataset - Base | 0 | 0 |
myvision/filtered_synthetic | false | []
| null | 0 | 0 |
anvelezec/maderapp | false | [
"license:mit"
]
| null | 2 | 0 |
mariodoebleriss/test_dataset | false | [
"license:other"
]
| null | 0 | 0 |
lexington/Sneakers | false | []
| null | 0 | 0 |
mteb/amazon_reviews_multi | false | [
"language:de",
"language:en",
"language:es",
"language:fr",
"language:ja",
"language:zh"
]
| We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.
For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.
Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language. | 2,174 | 0 |
erickdp/final_dataset | false | []
| null | 0 | 0 |
Lehrig/GTZAN-Collection | false | [
"license:apache-2.0"
]
| The dataset consists of 1000 audio tracks each 30 seconds long.
It contains 10 genres, each represented by 100 tracks.
The tracks are all 22050Hz Mono 16-bit audio files in .wav format.
The genres are:
* blues
* classical
* country
* disco
* hiphop
* jazz
* metal
* pop
* reggae
* rock
This collection includes the following GTZAN variants:
* raw (original WAV files)
* melspectrograms (from each WAV file, contiguous 2-second windows at 4 random locations are sampled and transformed to Mel Spectrograms, resulting in 8000 Mel Spectrograms) | 3 | 1 |
valurank/News_Articles_Categorization | false | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"multilinguality:monolingual",
"language:en",
"license:other"
]
| null | 3 | 0 |
mteb/amazon_polarity | false | [
"language:en"
]
| null | 170 | 0 |
nawalhmw/demo | false | []
| null | 0 | 0 |
emilylearning/cond_ft_none_on_reddit__prcnt_na__test_run_True__xlm-roberta-base | false | []
| null | 0 | 0 |
seoyeon-22/test | false | []
| null | 0 | 0 |
ulysses-camara/ulysses-ner-br | false | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:pt"
]
| null | 0 | 0 |
spoiled/ecqa_classify_5 | false | []
| null | 0 | 0 |
Jianxin1111/1111 | false | [
"license:bsl-1.0"
]
| null | 0 | 0 |
taesiri/GamePhysics_Grand_Theft_Auto_V | false | []
| A test dataset for GamePhysics | 3 | 3 |
idonov/test | false | []
| null | 1 | 0 |
mteb/imdb | false | [
"language:en"
]
| null | 139 | 0 |
emilylearning/cond_ft_subreddit_on_reddit__prcnt_100__test_run_False__xlm-roberta-base | false | []
| null | 0 | 0 |
mteb/amazon_counterfactual | false | [
"language:de",
"language:en",
"language:ja",
"arxiv:2104.06893"
]
| The dataset contains sentences from Amazon customer reviews (sampled from Amazon product review dataset) annotated for counterfactual detection (CFD) binary classification. Counterfactual statements describe events that did not or cannot take place. Counterfactual statements may be identified as statements of the form – If p was true, then q would be true (i.e. assertions whose antecedent (p) and consequent (q) are known or assumed to be false). | 2,375 | 0 |
Ashe/ceshi | false | [
"license:afl-3.0"
]
| null | 0 | 1 |
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