id stringlengths 2 115 | private bool 1
class | tags sequence | description stringlengths 0 5.93k ⌀ | downloads int64 0 1.14M | likes int64 0 1.79k |
|---|---|---|---|---|---|
acronym_identification | false | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"acronym-identification",
"arxiv:2010.14678"
] | Acronym identification training and development sets for the acronym identification task at SDU@AAAI-21. | 5,973 | 11 |
ade_corpus_v2 | false | [
"task_categories:text-classification",
"task_categories:token-classification",
"task_ids:coreference-resolution",
"task_ids:fact-checking",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"... | ADE-Corpus-V2 Dataset: Adverse Drug Reaction Data.
This is a dataset for Classification if a sentence is ADE-related (True) or not (False) and Relation Extraction between Adverse Drug Event and Drug.
DRUG-AE.rel provides relations between drugs and adverse effects.
DRUG-DOSE.rel provides relations between drugs an... | 3,893 | 14 |
adversarial_qa | false | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"task_ids:open-domain-qa",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"arxiv:2002.0... | AdversarialQA is a Reading Comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles using an adversarial model-in-the-loop.
We use three different models; BiDAF (Seo et al., 2016), BERT-Large (Devlin et al., 2018), and RoBERTa-Large (Liu et al., 2019) in the annotation loop an... | 38,194 | 22 |
aeslc | false | [
"task_categories:summarization",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown",
"aspect-based-summarization",
"conversations-summarization",
"multi-document... | A collection of email messages of employees in the Enron Corporation.
There are two features:
- email_body: email body text.
- subject_line: email subject text. | 1,259 | 3 |
afrikaans_ner_corpus | false | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:af",
"license:other"
] | Named entity annotated data from the NCHLT Text Resource Development: Phase II Project, annotated with PERSON, LOCATION, ORGANISATION and MISCELLANEOUS tags. | 356 | 3 |
ag_news | false | [
"task_categories:text-classification",
"task_ids:topic-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:unknown"
] | 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 researc... | 28,764 | 49 |
ai2_arc | false | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"task_ids:multiple-choice-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0"
] | A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in
advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains
only questions answered incorrectly by both a retrieval-based algorithm and a... | 28,200 | 6 |
air_dialogue | false | [
"task_categories:conversational",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-generation",
"task_ids:dialogue-modeling",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:crowdsourced",
"language_creators:machine-generated... | AirDialogue, is a large dataset that contains 402,038 goal-oriented conversations. To collect this dataset, we create a contextgenerator which provides travel and flight restrictions. Then the human annotators are asked to play the role of a customer or an agent and interact with the goal of successfully booking a trip... | 466 | 1 |
ajgt_twitter_ar | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ar",
"license:unknown"
] | Arabic Jordanian General Tweets (AJGT) Corpus consisted of 1,800 tweets annotated as positive and negative. Modern Standard Arabic (MSA) or Jordanian dialect. | 358 | 2 |
allegro_reviews | false | [
"task_categories:text-classification",
"task_ids:sentiment-scoring",
"task_ids:text-scoring",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:cc-by-sa-4.0"
] | Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish and extracted
from Allegro.pl - a popular e-commerce marketplace. Each review contains at least 50 words and has a rating on a scale
from one (negative review) to five (positive review).
We recommend using the provi... | 279 | 0 |
allocine | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:fr",
"license:mit"
] | Allocine Dataset: A Large-Scale French Movie Reviews Dataset.
This is a dataset for binary sentiment classification, made of user reviews scraped from Allocine.fr.
It contains 100k positive and 100k negative reviews divided into 3 balanced splits: train (160k reviews), val (20k) and test (20k). | 542 | 5 |
alt | false | [
"task_categories:translation",
"task_categories:token-classification",
"task_ids:parsing",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"multilinguality:translation",
"size_categories:100K<n<1M",
"size_categories:10K<n<100K",
"source_da... | The ALT project aims to advance the state-of-the-art Asian natural language processing (NLP) techniques through the open collaboration for developing and using ALT. It was first conducted by NICT and UCSY as described in Ye Kyaw Thu, Win Pa Pa, Masao Utiyama, Andrew Finch and Eiichiro Sumita (2016). Then, it was develo... | 1,266 | 5 |
amazon_polarity | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"arxiv:1509.01626"
] | The Amazon reviews dataset consists of reviews from amazon.
The data span a period of 18 years, including ~35 million reviews up to March 2013.
Reviews include product and user information, ratings, and a plaintext review. | 20,483 | 23 |
amazon_reviews_multi | false | [
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"task_ids:sentiment-classification",
"task_ids:sentiment-scoring",
"ta... | 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 a... | 11,555 | 41 |
amazon_us_reviews | false | [
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"task_ids:sentiment-classification",
"task_ids:sentiment-scoring",
"ta... | Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website... | 15,051 | 16 |
ambig_qa | false | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|natural_questions",
"source_datasets:original",
"language:en",
"license:cc-by-sa-3... | AmbigNQ, a dataset covering 14,042 questions from NQ-open, an existing open-domain QA benchmark. We find that over half of the questions in NQ-open are ambiguous. The types of ambiguity are diverse and sometimes subtle, many of which are only apparent after examining evidence provided by a very large text corpus. AMBI... | 1,113 | 1 |
americas_nli | false | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:multilingual",
"multilinguality:translation",
"size_categories:unknown",
"source_datasets:extended|xnli",
"language:ay",
"la... | AmericasNLI is an extension of XNLI (Conneau et al., 2018) – a natural language inference (NLI) dataset covering 15 high-resource languages – to 10 low-resource indigenous languages spoken in the Americas: Ashaninka, Aymara, Bribri, Guarani, Nahuatl, Otomi, Quechua, Raramuri, Shipibo-Konibo, and Wixarika. As with MNLI,... | 2,774 | 0 |
ami | false | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0"
] | The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,... | 799 | 8 |
amttl | false | [
"task_categories:token-classification",
"task_ids:parsing",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:zh",
"license:mit"
] | Chinese word segmentation (CWS) trained from open source corpus faces dramatic performance drop
when dealing with domain text, especially for a domain with lots of special terms and diverse
writing styles, such as the biomedical domain. However, building domain-specific CWS requires
extremely high annotation cost. In t... | 276 | 0 |
anli | false | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"task_ids:multi-input-text-classification",
"annotations_creators:crowdsourced",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_data... | The Adversarial Natural Language Inference (ANLI) is a new large-scale NLI benchmark dataset,
The dataset is collected via an iterative, adversarial human-and-model-in-the-loop procedure.
ANLI is much more difficult than its predecessors including SNLI and MNLI.
It contains three rounds. Each round has train/dev/test s... | 51,185 | 15 |
app_reviews | false | [
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:sentiment-scoring",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:unknown"
] | It is a large dataset of Android applications belonging to 23 differentapps categories, which provides an overview of the types of feedback users report on the apps and documents the evolution of the related code metrics. The dataset contains about 395 applications of the F-Droid repository, including around 600 versio... | 5,794 | 6 |
aqua_rat | false | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:apache-... | A large-scale dataset consisting of approximately 100,000 algebraic word problems.
The solution to each question is explained step-by-step using natural language.
This data is used to train a program generation model that learns to generate the explanation,
while generating the program that solves the question. | 1,952 | 2 |
aquamuse | false | [
"task_categories:other",
"task_categories:question-answering",
"task_categories:text2text-generation",
"task_ids:abstractive-qa",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language_creators:expert-genera... | AQuaMuSe is a novel scalable approach to automatically mine dual query based multi-document summarization datasets for extractive and abstractive summaries using question answering dataset (Google Natural Questions) and large document corpora (Common Crawl) | 256 | 4 |
ar_cov19 | false | [
"task_categories:other",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:ar",
"data-mining",
"arxiv:2004.05861"
] | ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others | 273 | 1 |
ar_res_reviews | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ar",
"license:unknown"
] | Dataset of 8364 restaurant reviews scrapped from qaym.com in Arabic for sentiment analysis | 291 | 3 |
ar_sarcasm | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-semeval_2017",
"source_datasets:extended|other-astd",
"language:ar... | ArSarcasm is a new Arabic sarcasm detection dataset.
The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD)
and adds sarcasm and dialect labels to them. The dataset contains 10,547 tweets, 1,682 (16%) of which are sarcastic. | 323 | 4 |
arabic_billion_words | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"size_categories:10K<n<100K",
"size_categories:1M<... | Abu El-Khair Corpus is an Arabic text corpus, that includes more than five million newspaper articles.
It contains over a billion and a half words in total, out of which, there are about three million unique words.
The corpus is encoded with two types of encoding, namely: UTF-8, and Windows CP-1256.
Also it was marked ... | 1,568 | 6 |
arabic_pos_dialect | false | [
"task_categories:token-classification",
"task_ids:part-of-speech",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:n<1K",
"source_datasets:extended",
"language:ar",
"license:apache-2.0",
"arxiv:1708.05891"
] | The Dialectal Arabic Datasets contain four dialects of Arabic, Etyptian (EGY), Levantine (LEV), Gulf (GLF), and Maghrebi (MGR). Each dataset consists of a set of 350 manually segmented and POS tagged tweets. | 683 | 2 |
arabic_speech_corpus | false | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ar",
"license:cc-by-4.0"
] | This Speech corpus has been developed as part of PhD work carried out by Nawar Halabi at the University of Southampton.
The corpus was recorded in south Levantine Arabic
(Damascian accent) using a professional studio. Synthesized speech as an output using this corpus has produced a high quality, natural voice.
Note tha... | 474 | 12 |
arcd | false | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ar",
"license:mit"
] | Arabic Reading Comprehension Dataset (ARCD) composed of 1,395 questions posed by crowdworkers on Wikipedia articles. | 329 | 1 |
arsentd_lev | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"task_ids:topic-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:apc",
"language:ajp",
"lic... | The Arabic Sentiment Twitter Dataset for Levantine dialect (ArSenTD-LEV) contains 4,000 tweets written in Arabic and equally retrieved from Jordan, Lebanon, Palestine and Syria. | 275 | 3 |
art | false | [
"task_categories:multiple-choice",
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:unknown",... | the Abductive Natural Language Inference Dataset from AI2 | 1,128 | 3 |
arxiv_dataset | false | [
"task_categories:translation",
"task_categories:summarization",
"task_categories:text-retrieval",
"task_ids:document-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:explanation-generation",
"task_ids:fact-checking-retrieval",
"task_ids:text-simplification",
"annotations_creators:no-annota... | A dataset of 1.7 million arXiv articles for applications like trend analysis, paper recommender engines, category prediction, co-citation networks, knowledge graph construction and semantic search interfaces. | 486 | 19 |
ascent_kb | false | [
"task_categories:other",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"knowledge-base",
"arxiv:2011.00905"
] | This dataset contains 8.9M commonsense assertions extracted by the Ascent pipeline (https://ascent.mpi-inf.mpg.de/). | 409 | 2 |
aslg_pc12 | false | [
"task_categories:translation",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:translation",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ase",
"language:en",
"license:cc-by-nc-4.0"
] | A large synthetic collection of parallel English and ASL-Gloss texts.
There are two string features: text, and gloss. | 380 | 1 |
asnq | false | [
"task_categories:multiple-choice",
"task_ids:multiple-choice-qa",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:extended|natural_questions",
"language:en",
"license:cc-by-nc-sa-3.0",
"arxiv:1911.04118"
... | ASNQ is a dataset for answer sentence selection derived from
Google's Natural Questions (NQ) dataset (Kwiatkowski et al. 2019).
Each example contains a question, candidate sentence, label indicating whether or not
the sentence answers the question, and two additional features --
sentence_in_long_answer and short_answe... | 576 | 1 |
asset | false | [
"task_categories:text-classification",
"task_categories:text2text-generation",
"task_ids:text-simplification",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"source_datasets:extended|other-t... | ASSET is a dataset for evaluating Sentence Simplification systems with multiple rewriting transformations,
as described in "ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations".
The corpus is composed of 2000 validation and 359 test original sentences tha... | 2,465 | 6 |
assin | false | [
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:natural-language-inference",
"task_ids:semantic-similarity-scoring",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
... | The ASSIN (Avaliação de Similaridade Semântica e INferência textual) corpus is a corpus annotated with pairs of sentences written in
Portuguese that is suitable for the exploration of textual entailment and paraphrasing classifiers. The corpus contains pairs of sentences
extracted from news articles written in Europea... | 612 | 5 |
assin2 | false | [
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:natural-language-inference",
"task_ids:semantic-similarity-scoring",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
... | The ASSIN 2 corpus is composed of rather simple sentences. Following the procedures of SemEval 2014 Task 1.
The training and validation data are composed, respectively, of 6,500 and 500 sentence pairs in Brazilian Portuguese,
annotated for entailment and semantic similarity. Semantic similarity values range from 1 to 5... | 1,044 | 4 |
atomic | false | [
"task_categories:text2text-generation",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"common-sense-if-then-reasoning"
] | This dataset provides the template sentences and
relationships defined in the ATOMIC common sense dataset. There are
three splits - train, test, and dev.
From the authors.
Disclaimer/Content warning: the events in atomic have been
automatically extracted from blogs, stories and books written at
various times. The eve... | 286 | 4 |
autshumato | false | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"language:tn",
"language:ts",
"language:zu",
"lice... | Multilingual information access is stipulated in the South African constitution. In practise, this
is hampered by a lack of resources and capacity to perform the large volumes of translation
work required to realise multilingual information access. One of the aims of the Autshumato
project is to develop machine transla... | 936 | 1 |
facebook/babi_qa | false | [
"task_categories:question-answering",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"license:cc-by-3.0",
... | The (20) QA bAbI tasks are a set of proxy tasks that evaluate reading
comprehension via question answering. Our tasks measure understanding
in several ways: whether a system is able to answer questions via chaining facts,
simple induction, deduction and many more. The tasks are designed to be prerequisites
for any syst... | 641 | 1 |
banking77 | false | [
"task_categories:text-classification",
"task_ids:intent-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"li... | BANKING77 dataset provides a very fine-grained set of intents in a banking domain.
It comprises 13,083 customer service queries labeled with 77 intents.
It focuses on fine-grained single-domain intent detection. | 4,804 | 17 |
bbaw_egyptian | false | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"source_datasets:extended|wikipedia",
"language:de",
"language:egy",
"language:en",
"license:cc-by-4.0"
] | This dataset comprises parallel sentences of hieroglyphic encodings, transcription and translation
as used in the paper Multi-Task Modeling of Phonographic Languages: Translating Middle Egyptian
Hieroglyph. The data triples are extracted from the digital corpus of Egyptian texts compiled by
the project "Strukturen und ... | 282 | 3 |
bbc_hindi_nli | false | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|bbc__hindi_news_classification",
"language:hi",
"license:mit"
] | This dataset is used to train models for Natural Language Inference Tasks in Low-Resource Languages like Hindi. | 309 | 0 |
bc2gm_corpus | false | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown"
] | Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop.
In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions.
A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721.
Here ... | 539 | 2 |
beans | false | [
"task_categories:image-classification",
"task_ids:multi-class-image-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:mit"
] | Beans is a dataset of images of beans taken in the field using smartphone
cameras. It consists of 3 classes: 2 disease classes and the healthy class.
Diseases depicted include Angular Leaf Spot and Bean Rust. Data was annotated
by experts from the National Crops Resources Research Institute (NaCRRI) in
Uganda and colle... | 8,390 | 8 |
best2009 | false | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:th",
"license:cc-by-nc-sa-3.0",
"word-tokenization"
] | `best2009` is a Thai word-tokenization dataset from encyclopedia, novels, news and articles by
[NECTEC](https://www.nectec.or.th/) (148,995/2,252 lines of train/test). It was created for
[BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10).
The test set answers are ... | 386 | 0 |
bianet | false | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:translation",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"language:ku",
"language:tr",
"license:unknown"
] | A parallel news corpus in Turkish, Kurdish and English.
Bianet collects 3,214 Turkish articles with their sentence-aligned Kurdish or English translations from the Bianet online newspaper.
3 languages, 3 bitexts
total number of files: 6
total number of tokens: 2.25M
total number of sentence fragments: 0.14M | 539 | 0 |
bible_para | false | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:acu",
"language:af",
"language:agr",
"language:ake",
"language:am",
"language:amu",
"language:ar",
"la... | This is a multilingual parallel corpus created from translations of the Bible compiled by Christos Christodoulopoulos and Mark Steedman.
102 languages, 5,148 bitexts
total number of files: 107
total number of tokens: 56.43M
total number of sentence fragments: 2.84M | 1,007 | 6 |
big_patent | false | [
"task_categories:summarization",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"size_categories:10K<n<100K",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"patent-summariz... | BIGPATENT, consisting of 1.3 million records of U.S. patent documents
along with human written abstractive summaries.
Each US patent application is filed under a Cooperative Patent Classification
(CPC) code. There are nine such classification categories:
A (Human Necessities), B (Performing Operations; Transporting),
C... | 2,937 | 15 |
billsum | false | [
"task_categories:summarization",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc0-1.0",
"bills-summarization",
"arxiv:1910.00523"
] | BillSum, summarization of US Congressional and California state bills.
There are several features:
- text: bill text.
- summary: summary of the bills.
- title: title of the bills.
features for us bills. ca bills does not have.
- text_len: number of chars in text.
- sum_len: number of chars in summary. | 4,292 | 16 |
bing_coronavirus_query_set | false | [
"task_categories:text-classification",
"task_ids:intent-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:other"
] | This dataset was curated from the Bing search logs (desktop users only) over the period of Jan 1st, 2020 – (Current Month - 1). Only searches that were issued many times by multiple users were included. The dataset includes queries from all over the world that had an intent related to the Coronavirus or Covid-19. In so... | 840 | 0 |
biomrc | false | [
"language:en"
] | We introduce BIOMRC, a large-scale cloze-style biomedical MRC dataset. Care was taken to reduce noise, compared to the previous BIOREAD dataset of Pappas et al. (2018). Experiments show that simple heuristics do not perform well on the new dataset and that two neural MRC models that had been tested on BIOREAD perform m... | 1,130 | 3 |
biosses | false | [
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:semantic-similarity-scoring",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"license:gpl-3.0"
] | BIOSSES is a benchmark dataset for biomedical sentence similarity estimation. The dataset comprises 100 sentence pairs, in which each sentence was selected from the TAC (Text Analysis Conference) Biomedical Summarization Track Training Dataset containing articles from the biomedical domain. The sentence pairs were eval... | 1,246 | 3 |
blbooks | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:other",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:machine-generated",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"sou... | A dataset comprising of text created by OCR from the 49,455 digitised books, equating to 65,227 volumes (25+ million pages), published between c. 1510 - c. 1900.
The books cover a wide range of subject areas including philosophy, history, poetry and literature. | 679 | 4 |
blbooksgenre | false | [
"task_categories:text-classification",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:topic-classification",
"task_ids:multi-label-classification",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:expert-generated",
"language_creator... | This dataset contains metadata for resources belonging to the British Library’s digitised printed books (18th-19th century) collection (bl.uk/collection-guides/digitised-printed-books).
This metadata has been extracted from British Library catalogue records.
The metadata held within our main catalogue is updated regula... | 1,669 | 3 |
blended_skill_talk | false | [
"task_categories:conversational",
"task_ids:dialogue-generation",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"arxiv:2004.08449"
] | A dataset of 7k conversations explicitly designed to exhibit multiple conversation modes: displaying personality, having empathy, and demonstrating knowledge. | 1,607 | 26 |
blimp | false | [
"task_categories:text-classification",
"task_ids:acceptability-classification",
"annotations_creators:crowdsourced",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0"
] | BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted gr... | 18,657 | 27 |
blog_authorship_corpus | false | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown"
] | The Blog Authorship Corpus consists of the collected posts of 19,320 bloggers gathered from blogger.com in August 2004. The corpus incorporates a total of 681,288 posts and over 140 million words - or approximately 35 posts and 7250 words per person.
Each blog is presented as a separate file, the name of which indicat... | 602 | 4 |
bn_hate_speech | false | [
"task_categories:text-classification",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:bn",
"license:mit",
"hate-speech-topic-classification",
... | The Bengali Hate Speech Dataset is a collection of Bengali articles collected from Bengali news articles,
news dump of Bengali TV channels, books, blogs, and social media. Emphasis was placed on Facebook pages and
newspaper sources because they attract close to 50 million followers and is a common source of opinions
an... | 294 | 1 |
bnl_newspapers | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ar"... | Digitised historic newspapers from the Bibliothèque nationale (BnL) - the National Library of Luxembourg. | 276 | 0 |
bookcorpus | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:en"... | Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and how these states evolve through a story.This work aims to align books to their movie releases in order to providerich descriptive explanation... | 10,541 | 80 |
bookcorpusopen | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"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"... | Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and how these states evolve through a story.
This version of bookcorpus has 17868 dataset items (books). Each item contains two fields: title and... | 925 | 13 |
boolq | false | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-sa-3.0"
] | BoolQ is a question answering dataset for yes/no questions containing 15942 examples. These questions are naturally
occurring ---they are generated in unprompted and unconstrained settings.
Each example is a triplet of (question, passage, answer), with the title of the page as optional additional context.
The text-pair... | 4,429 | 10 |
bprec | false | [
"task_categories:text-retrieval",
"task_ids:entity-linking-retrieval",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:unknown"
] | Dataset consisting of Polish language texts annotated to recognize brand-product relations. | 805 | 0 |
break_data | false | [
"task_categories:text2text-generation",
"task_ids:open-domain-abstractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown"
] | Break is a human annotated dataset of natural language questions and their Question Decomposition Meaning Representations
(QDMRs). Break consists of 83,978 examples sampled from 10 question answering datasets over text, images and databases.
This repository contains the Break dataset along with information on the exact... | 1,203 | 0 |
brwac | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:pt",
... | The BrWaC (Brazilian Portuguese Web as Corpus) is a large corpus constructed following the Wacky framework,
which was made public for research purposes. The current corpus version, released in January 2017, is composed by
3.53 million documents, 2.68 billion tokens and 5.79 million types. Please note that this resource... | 299 | 5 |
bsd_ja_en | false | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"language:ja",
"license:cc-by-nc-sa-4.0",
"business-conversations-translation"
] | This is the Business Scene Dialogue (BSD) dataset,
a Japanese-English parallel corpus containing written conversations
in various business scenarios.
The dataset was constructed in 3 steps:
1) selecting business scenes,
2) writing monolingual conversation scenarios according to the selected scenes, and
3) transl... | 278 | 1 |
bswac | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100M<n<1B",
"source_datasets:original",
"language:bs",... | The Bosnian web corpus bsWaC was built by crawling the .ba top-level domain in 2014. The corpus was near-deduplicated on paragraph level, normalised via diacritic restoration, morphosyntactically annotated and lemmatised. The corpus is shuffled by paragraphs. Each paragraph contains metadata on the URL, domain and lang... | 272 | 0 |
c3 | false | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:zh",
"license:other",
"arxiv:1904.09679"
] | Machine reading comprehension tasks require a machine reader to answer questions relevant to the given document. In this paper, we present the first free-form multiple-Choice Chinese machine reading Comprehension dataset (C^3), containing 13,369 documents (dialogues or more formally written mixed-genre texts) and their... | 467 | 2 |
c4 | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:100M<n<1B",
"source_datasets:original",
"language:en"... | A colossal, cleaned version of Common Crawl's web crawl corpus.
Based on Common Crawl dataset: "https://commoncrawl.org".
This is the processed version of Google's C4 dataset by AllenAI. | 45,904 | 67 |
cail2018 | false | [
"task_categories:other",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:zh",
"license:unknown",
"judgement-prediction",
"arxiv:1807.02478"
] | In this paper, we introduce Chinese AI and Law challenge dataset (CAIL2018),
the first large-scale Chinese legal dataset for judgment prediction. CAIL contains more than 2.6 million
criminal cases published by the Supreme People's Court of China, which are several times larger than other
datasets in existing works on j... | 337 | 3 |
caner | false | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ar",
"license:unknown"
] | Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities. | 357 | 1 |
capes | false | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"language:pt",
"license:unknown",
"dissertation-abstracts-translation",
"theses-translation"
] | A parallel corpus of theses and dissertations abstracts in English and Portuguese were collected from the CAPES website (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) - Brazil. The corpus is sentence aligned for all language pairs. Approximately 240,000 documents were collected and aligned using the Huna... | 275 | 1 |
casino | false | [
"task_categories:conversational",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"languag... | We provide a novel dataset (referred to as CaSiNo) of 1030 negotiation dialogues. Two participants take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. This design keeps the task tractable, while still facilitating linguistical... | 303 | 1 |
catalonia_independence | false | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ca",
"language:es",
"license:cc-by-nc-sa-4.0",
"stance-detection"
] | This dataset contains two corpora in Spanish and Catalan that consist of annotated Twitter messages for automatic stance detection. The data was collected over 12 days during February and March of 2019 from tweets posted in Barcelona, and during September of 2018 from tweets posted in the town of Terrassa, Catalonia.
... | 421 | 1 |
cats_vs_dogs | false | [
"task_categories:image-classification",
"task_ids:multi-class-image-classification",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown"
] | null | 885 | 8 |
cawac | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:ca"... | caWaC is a 780-million-token web corpus of Catalan built from the .cat top-level-domain in late 2013. | 275 | 0 |
cbt | false | [
"task_categories:other",
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"licen... | The Children’s Book Test (CBT) is designed to measure directly
how well language models can exploit wider linguistic context.
The CBT is built from books that are freely available. | 4,089 | 7 |
cc100 | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"size_categories:1M<n<10M",
"source_data... | This corpus is an attempt to recreate the dataset used for training XLM-R. This corpus comprises of monolingual data for 100+ languages and also includes data for romanized languages (indicated by *_rom). This was constructed using the urls and paragraph indices provided by the CC-Net repository by processing January-D... | 3,397 | 22 |
cc_news | false | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",... | CC-News containing news articles from news sites all over the world The data is available on AWS S3 in the Common Crawl bucket at /crawl-data/CC-NEWS/. This version of the dataset has 708241 articles. It represents a small portion of English language subset of the CC-News dataset created using news-please(Hamborg et a... | 3,067 | 18 |
ccaligned_multilingual | false | [
"task_categories:other",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:translation",
"size_categories:n<1K",
"size_categories:1K<n<10K",
"size_categories:10K<n<100K",
"size_categories:100K<n<1M",
"size_categories:1M<n<10M",
"size_categories:10M<n<100M",
"sourc... | CCAligned consists of parallel or comparable web-document pairs in 137 languages aligned with English. These web-document pairs were constructed by performing language identification on raw web-documents, and ensuring corresponding language codes were corresponding in the URLs of web documents. This pattern matching ap... | 932 | 2 |
cdsc | false | [
"task_categories:other",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:cc-by-nc-sa-4.0",
"sentences entailment and relatedness"
] | Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness and entailment. The dataset may be used for the evaluation of compositional distributional semantics models of Polish. The dataset was presented at ACL 2017. Please refer to the Wróblewska and Krasnowska-Kieraś (20... | 404 | 0 |
cdt | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:bsd-3-clause"
] | The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content. | 272 | 0 |
cedr | false | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"task_ids:multi-label-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ru",
"license:apache-2... | This new dataset is designed to solve emotion recognition task for text data in Russian. The Corpus for Emotions Detecting in
Russian-language text sentences of different social sources (CEDR) contains 9410 sentences in Russian labeled for 5 emotion
categories. The data collected from different sources: posts of the Li... | 692 | 3 |
cfq | false | [
"task_categories:question-answering",
"task_categories:other",
"task_ids:open-domain-qa",
"task_ids:closed-domain-qa",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
... | The CFQ dataset (and it's splits) for measuring compositional generalization.
See https://arxiv.org/abs/1912.09713.pdf for background.
Example usage:
data = datasets.load_dataset('cfq/mcd1') | 1,225 | 1 |
chr_en | false | [
"task_categories:fill-mask",
"task_categories:text-generation",
"task_categories:translation",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:expert-generated",
"annotations_creators:found",
"annotations_creators:no-annotation",
"language_creators:found",
... | ChrEn is a Cherokee-English parallel dataset to facilitate machine translation research between Cherokee and English.
ChrEn is extremely low-resource contains 14k sentence pairs in total, split in ways that facilitate both in-domain and out-of-domain evaluation.
ChrEn also contains 5k Cherokee monolingual data to enabl... | 672 | 2 |
cifar10 | false | [
"task_categories:image-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-80-Million-Tiny-Images",
"language:en",
"license:unknown"
] | The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images
per class. There are 50000 training images and 10000 test images. | 23,528 | 14 |
cifar100 | false | [
"task_categories:image-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-80-Million-Tiny-Images",
"language:en",
"license:unknown"
] | The CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (act... | 3,516 | 6 |
circa | false | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"question-answer-pai... | The Circa (meaning ‘approximately’) dataset aims to help machine learning systems
to solve the problem of interpreting indirect answers to polar questions.
The dataset contains pairs of yes/no questions and indirect answers, together with
annotations for the interpretation of the answer. The data is collected in 10
di... | 1,314 | 1 |
civil_comments | false | [
"language:en",
"arxiv:1903.04561"
] | The comments in this dataset come from an archive of the Civil Comments
platform, a commenting plugin for independent news sites. These public comments
were created from 2015 - 2017 and appeared on approximately 50 English-language
news sites across the world. When Civil Comments shut down in 2017, they chose
to make t... | 892 | 1 |
clickbait_news_bg | false | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:bg",
"license:unknown"
] | Dataset with clickbait and fake news in Bulgarian. Introduced for the Hack the Fake News 2017. | 280 | 0 |
climate_fever | false | [
"task_categories:text-classification",
"task_categories:text-retrieval",
"task_ids:text-scoring",
"task_ids:fact-checking",
"task_ids:fact-checking-retrieval",
"task_ids:semantic-similarity-scoring",
"task_ids:multi-input-text-classification",
"annotations_creators:crowdsourced",
"annotations_creato... | A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim ... | 1,859 | 4 |
clinc_oos | false | [
"task_categories:text-classification",
"task_ids:intent-classification",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-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... | 3,086 | 9 |
clue | false | [
"task_categories:text-classification",
"task_categories:multiple-choice",
"task_ids:topic-classification",
"task_ids:semantic-similarity-scoring",
"task_ids:natural-language-inference",
"task_ids:multiple-choice-qa",
"annotations_creators:other",
"language_creators:other",
"multilinguality:monolingu... | CLUE, A Chinese Language Understanding Evaluation Benchmark
(https://www.cluebenchmarks.com/) is a collection of resources for training,
evaluating, and analyzing Chinese language understanding systems. | 4,366 | 17 |
cmrc2018 | false | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:zh",
"license:cc-by-sa-4.0"
] | A Span-Extraction dataset for Chinese machine reading comprehension to add language
diversities in this area. The dataset is composed by near 20,000 real questions annotated
on Wikipedia paragraphs by human experts. We also annotated a challenge set which
contains the questions that need comprehensive understanding and... | 851 | 6 |
cmu_hinglish_dog | false | [
"task_categories:translation",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"language:hi",
"license:cc-by-sa-3.0",
"license:gfdl",
... | This is a collection of text conversations in Hinglish (code mixing between Hindi-English) and their corresponding English only versions. Can be used for Translating between the two. | 321 | 1 |
cnn_dailymail | false | [
"task_categories:summarization",
"task_ids:news-articles-summarization",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:apache-2.0"
] | CNN/DailyMail non-anonymized summarization dataset.
There are two features:
- article: text of news article, used as the document to be summarized
- highlights: joined text of highlights with <s> and </s> around each
highlight, which is the target summary | 62,766 | 50 |
coached_conv_pref | false | [
"task_categories:other",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:token-classification",
"task_ids:dialogue-modeling",
"task_ids:parsing",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1... | A dataset consisting of 502 English dialogs with 12,000 annotated utterances between a user and an assistant discussing
movie preferences in natural language. It was collected using a Wizard-of-Oz methodology between two paid crowd-workers,
where one worker plays the role of an 'assistant', while the other plays the ro... | 273 | 2 |
End of preview. Expand in Data Studio
Dataset Card for "huggingface-datasets"
This dataset is a snapshot of all public datasets in HuggingFace as of 04/24/2023. It is based on the dataset metadata that can be found at the following endpoint: https://huggingface.co/api/datasets/{dataset_id}
Which contains information like the dataset name, its tags, description, and more. Please note that description is different from dataset card, which is what you are reading now :-).
I would love to replace this dataset with one which uses dataset card instead of description, but that is not something I can scrape in a realistic amount of time. In any case, this data still contains some useful metadata about the datasets on HF, and can be used for a variety of downstream tasks. Please like if you enjoy <3.
For more insight into how this data was collected and how it can be used, please checkout the repository here: https://github.com/nkasmanoff/searching-face
I did not check all descriptions in this > 30k sample dataset. Most are null, but it is possible that some may be NSFW. Please use responsibly.
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