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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
naver-clova-conversation-ul | null | null | null | false | 10 | false | naver-clova-conversation-ul/klue-tc-dev | 2021-05-26T08:57:19.000Z | null | false | db43d6f16deec9fbcda9919d25c4f56018175cc9 | [] | [] | https://huggingface.co/datasets/naver-clova-conversation-ul/klue-tc-dev/resolve/main/README.md | This is a in-house development version of KLUE Topic Classification benchmark, as the test split is not released by the KLUE team.
We randomly split the original validation set (9,107 instances) into in-house validation set (5,107 instances) and the in-house test set (4,000 instances).
|
navjordj | null | null | null | false | 2 | false | navjordj/nak_nb | 2021-11-18T18:39:13.000Z | null | false | 5a918d7d41b3cdad342d07f2b58d5b87e73c9e37 | [] | [] | https://huggingface.co/datasets/navjordj/nak_nb/resolve/main/README.md | Norsk Avis Korpus 2012-2019
* https://www.nb.no/sprakbanken/ressurskatalog/oai-nb-no-sbr-4/
Hentet ut artiklene på bokmål
Parset xml og hentet ut all teksten inni <p>-tags.
|
ncats | null | John JN, Sid E, Zhu Q. Recurrent Neural Networks to Automatically Identify Rare Disease Epidemiologic Studies from PubMed. AMIA Jt Summits Transl Sci Proc. 2021 May 17;2021:325-334. PMID: 34457147; PMCID: PMC8378621. | INSERT DESCRIPTION | false | 1 | false | ncats/EpiSet4BinaryClassification | 2022-10-25T09:51:14.000Z | glue | false | 956069bd8059d11100450dad2b8d3ec2a0f558d6 | [] | [
"annotations_creators:unknown",
"language_creators:unknown",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:unknown"
] | https://huggingface.co/datasets/ncats/EpiSet4BinaryClassification/resolve/main/README.md | ---
annotations_creators:
- unknown
language_creators:
- unknown
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- unknown
paperswithcode_id: glue
pretty_name: GLUE (General Language Understanding Evaluation benchmark)
---
# DOCUMENTATION UPDATES IN PRO... |
ncats | null | *REDO*
@inproceedings{wang2019crossweigh,
title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Proc... | **REWRITE*
EpiSet4NER is a dataset generated from 620 rare disease abstracts labeled using statistical and rule-base methods. The test set was then manually corrected by a rare disease expert.
For more details see *INSERT PAPER* and https://github.com/ncats/epi4GARD/tree/master/EpiExtract4GARD#epiextract4gard | false | 1 | false | ncats/EpiSet4NER-v1 | 2022-09-20T14:08:28.000Z | null | false | 5f626f0ef45a3f8f0f0c1224cdb82b596c540d3b | [] | [
"language_creators:found",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/ncats/EpiSet4NER-v1/resolve/main/README.md | ---
annotations_creators:
- train: programmatically-generated
- val: programmatically-generated
- test: programmatically-generated, expert-validated
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
task_categories:
- structure-prediction
task_ids:
-... |
ncduy | null | null | null | false | 5 | false | ncduy/mt-en-vi | 2022-10-22T15:08:45.000Z | null | false | 7cd5eb8359df27b6e68c9400642764ff07e89e3b | [] | [
"annotations_creators:found",
"language_creators:found",
"language:en",
"language:vi",
"license:mit",
"multilinguality:translation",
"size_categories:1M<n<10M",
"source_datasets:own",
"source_datasets:open_subtitles",
"source_datasets:tatoeba",
"source_datasets:opus_tedtalks",
"source_datasets... | https://huggingface.co/datasets/ncduy/mt-en-vi/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
- vi
license:
- mit
multilinguality:
- translation
pretty_name: "Machine Translation Paired English-Vietnamese Sentences"
size_categories:
- 1M<n<10M
source_datasets:
- own
- open_subtitles
- tatoeba
- opus_tedtalks
- qed_amara
- opus_wikipedia... |
neelalex | null | \\n@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | \\nThis dataset contains a corpus of AI papers. The first task is to determine\\n whether or not a datapoint is an AI safety paper. The second task is to\\n determine what type of paper it is. | false | 2 | false | neelalex/raft-predictions | 2021-08-04T22:25:12.000Z | null | false | cd74da4bdfd725d7c21a8ab8d7a128097e0d3771 | [] | [
"benchmark:raft"
] | https://huggingface.co/datasets/neelalex/raft-predictions/resolve/main/README.md | ---
benchmark: raft
---
# Dummy predictions for RAFT |
nferruz | null | null | null | false | 2 | false | nferruz/UR50_2021_04 | 2022-07-22T13:44:04.000Z | null | false | 603e7e491c203758566b0c7d264ba93f8bd72810 | [] | [
"size_categories:unknown"
] | https://huggingface.co/datasets/nferruz/UR50_2021_04/resolve/main/README.md | ---
YAML tags:
annotations_creators: []
language_creators: []
language: []
license: []
multilinguality: []
pretty_name: ''
size_categories:
- unknown
source_datasets: []
task_categories: []
task_ids: []
---
# Dataset Card for UR50_2021_04
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Desc... |
nickmuchi | null | null | null | false | 47 | false | nickmuchi/financial-classification | 2022-10-24T01:05:49.000Z | null | false | 3212e172737ca693859a84b347f4606860782b46 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/nickmuchi/financial-classification/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
task_categories:
- text-classification
task_ids:
- multi-class-classification
- sentiment-classification
train-eval-index:
- config: sentences_50agree
- task: text-classification
- task_ids: multi_class_classification
- splits:
... |
nid989 | null | null | null | false | 2 | false | nid989/FNC-1 | 2021-12-27T11:04:06.000Z | null | false | 485bc494bfc0f2bc3c0a878c84a83fc1f156d8b2 | [] | [] | https://huggingface.co/datasets/nid989/FNC-1/resolve/main/README.md | ### Dataset Summary
The data provided is (headline, body, stance) instances, where the stance is one of {unrelated, discuss, agree, disagree}.
**Input**
* A headline and a body text - either from the same news article or from two different articles.
**Output**
* Classify the stance of the body text relative to the ... |
nielsr | null | @article{Jaume2019FUNSDAD,
title={FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents},
author={Guillaume Jaume and H. K. Ekenel and J. Thiran},
journal={2019 International Conference on Document Analysis and Recognition Workshops (ICDARW)},
year={2019},
volume={2},
pages={1-6}
} | https://guillaumejaume.github.io/FUNSD/ | false | 235 | false | nielsr/FUNSD_layoutlmv2 | 2022-10-25T09:51:20.000Z | funsd | false | 1941df61807cb4a99712d25115704fda9a0f8b25 | [] | [
"arxiv:1905.13538",
"language:en"
] | https://huggingface.co/datasets/nielsr/FUNSD_layoutlmv2/resolve/main/README.md | ---
language:
- en
paperswithcode_id: funsd
---
# Dataset Card for "FUNSD"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-str... |
nlpufg | null | null | null | false | 1 | false | nlpufg/brwac-pt | 2021-07-12T23:25:24.000Z | null | false | e4806d1eaf1dcab208ac30a6c921c710bc104374 | [] | [] | https://huggingface.co/datasets/nlpufg/brwac-pt/resolve/main/README.md | preprocessed removing mojibake texts |
nlpufg | null | null | null | false | 2 | false | nlpufg/oscar-pt | 2021-07-12T23:26:15.000Z | null | false | 73c8546913e7e34d1378c8ac74795539d55aa837 | [] | [] | https://huggingface.co/datasets/nlpufg/oscar-pt/resolve/main/README.md | preprocessed removing mojibake texts |
nlpyeditepe | null | null | null | false | 2 | false | nlpyeditepe/tr-qnli | 2022-07-01T15:28:44.000Z | null | false | 5331951940a16c65ff8a1bfaff0724d2944065a9 | [] | [
"annotations_creators:found",
"language_creators:machine-generated",
"language:tr-TR",
"license:mit",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:extended|glue",
"task_categories:text-classification",
"task_ids:natural-language-inference"
] | https://huggingface.co/datasets/nlpyeditepe/tr-qnli/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- machine-generated
language:
- tr-TR
license:
- mit
multilinguality:
- monolingual
pretty_name: QNLI for Turkish
size_categories:
- unknown
source_datasets:
- extended|glue
task_categories:
- text-classification
task_ids:
- natural-language-inference
--- |
nlpyeditepe | null | null | null | false | 1 | false | nlpyeditepe/tr_rte | 2022-07-01T15:28:27.000Z | null | false | 0996e5fe4b8d41d9ce4c899a0f04d2f801f1fc33 | [] | [
"annotations_creators:found",
"language_creators:machine-generated",
"language:tr-TR",
"license:mit",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:extended|glue",
"task_categories:text-classification",
"task_ids:natural-language-inference"
] | https://huggingface.co/datasets/nlpyeditepe/tr_rte/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- machine-generated
language:
- tr-TR
license:
- mit
multilinguality:
- monolingual
pretty_name: RTE for Turkish
size_categories:
- unknown
source_datasets:
- extended|glue
task_categories:
- text-classification
task_ids:
- natural-language-inference
--- |
nntadotzip | null | null | null | false | 2 | false | nntadotzip/iuQAchatbot | 2022-01-20T07:25:26.000Z | null | false | f9172c55616145ca31d33872003249043c8f805c | [] | [] | https://huggingface.co/datasets/nntadotzip/iuQAchatbot/resolve/main/README.md | annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
- found
languages:
- en
licenses:
- cc-by-4.0
multilinguality:
- monolingual
paperswithcode_id: squad
pretty_name: SQuAD
size_categories:
- 10K<n<100K
source_datasets:
- extended|wikipedia
task_categories:
- question-answering
task_ids:
- extractive... |
notional | null | null | null | false | 1 | false | notional/notional-python | 2022-10-21T13:39:56.000Z | null | false | 65563031418b17855bf1f0c5252faa7c674109f0 | [] | [
"annotations_creators:no-annotation",
"language:py",
"language_creators:found",
"license:unknown",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_ids:language-modeling",
"task_ids:code-generation"
] | https://huggingface.co/datasets/notional/notional-python/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language:
- py
language_creators:
- found
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- code-generation
- conditional-text-generation
task_ids:
- language-modeling
- code-generation
---
# Dataset ... |
nucklehead | null | null | null | false | 2 | false | nucklehead/ht-voice-dataset | 2021-04-14T12:34:47.000Z | null | false | 7314a5b74f065dca9d690a5494d3145b531f1d85 | [] | [] | https://huggingface.co/datasets/nucklehead/ht-voice-dataset/resolve/main/README.md | # Ansanb done vwa an Kreyòl pou antrene DeepSPeech.
Dataset sa a gen plis pase 7 è tan anrejistreman vwa ak prèske 100 moun an Kreyòl pou bati sistèm ASR ak TTS pou lang Kreyòl la.
Pifò nan done yo soti nan "CMU Haitian Creole Speech Recognition Database" la.
Done sa yo gentan filtre epi òganize pou ka antrene modè... |
oelkrise | null | null | null | false | 2 | false | oelkrise/CRT | 2021-03-28T15:32:38.000Z | null | false | a5c0dce3bed22d5a2fffb5a26b6f9c349e6b8f6c | [] | [] | https://huggingface.co/datasets/oelkrise/CRT/resolve/main/README.md | egrfdfaffd |
omar-sharif | null | null | null | false | 1 | false | omar-sharif/BAD-Bengali-Aggressive-Text-Dataset | 2022-02-24T15:42:02.000Z | null | false | 2b4f7179a68a023d210c30b5b093b178b5686760 | [] | [] | https://huggingface.co/datasets/omar-sharif/BAD-Bengali-Aggressive-Text-Dataset/resolve/main/README.md | ## Novel Aggressive Text Dataset in Bengali
## Tackling Cyber-Aggression: Identification and Fine-Grained Categorization of Aggressive Texts on Social Media using Weighted Ensemble of Transformers
**Author:** Omar Sharif and Mohammed Moshiul Hoque
**Related Papers:**
[Paper1 in Neurocomputing Journal](ht... |
openclimatefix | null | @InProceedings{eumetsat:ocf_uk_hrv,
title = {EUMETSAT SEVIRI RSS UK HRV},
author={EUMETSAT, with preparation by Open Climate Fix
},
year={2022}
} | The EUMETSAT Spinning Enhanced Visible and InfraRed Imager (SEVIRI) rapid scanning service (RSS) takes an image of the northern third of the Meteosat disc every five minutes (see the EUMETSAT website for more information on SEVIRI RSS ). The original EUMETSAT dataset contains data from 2008 to the present day from 12 ... | false | 2 | false | openclimatefix/eumetsat_uk_hrv | 2022-08-04T11:40:24.000Z | null | false | 6bd475ffbfaef79351083a387c49bb03fc4575d7 | [] | [] | https://huggingface.co/datasets/openclimatefix/eumetsat_uk_hrv/resolve/main/README.md | [Needs More Information]
# Dataset Card for EUMETSAT UK HRV
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#da... |
openclimatefix | null | null | null | false | 2 | false | openclimatefix/gfs | 2022-02-14T13:09:42.000Z | null | false | b99847afc7bd0a90dece766d0dee1c0ae4d420c4 | [] | [
"license:mit"
] | https://huggingface.co/datasets/openclimatefix/gfs/resolve/main/README.md | ---
license: mit
---
|
openclimatefix | null | null | null | false | 2 | false | openclimatefix/goes-l2 | 2022-02-06T10:21:15.000Z | null | false | a0b8e0658b37bdd81b39e6af5e5cd97d52efd685 | [] | [
"license:mit"
] | https://huggingface.co/datasets/openclimatefix/goes-l2/resolve/main/README.md | ---
license: mit
---
|
openclimatefix | null | null | null | false | 25 | false | openclimatefix/goes-mrms | 2022-02-10T17:26:40.000Z | null | false | ee4a07d09306bbf49880de047ab450fb809ba4c8 | [] | [] | https://huggingface.co/datasets/openclimatefix/goes-mrms/resolve/main/README.md | # Dataset Card for Goes-MRMS
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](... |
openclimatefix | null | @InProceedings{noaa,
title = {GOES-16 and GOES-17 data},
author={NOAA
},
year={2022}
} | The National Oceanic and Atmospheric Administration (NOAA) operates a constellation of Geostationary Operational Environmental Satellites (GOES) to provide continuous weather imagery and monitoring of meteorological and space environment data for the protection of life and property across the United States. GOES satell... | false | 1 | false | openclimatefix/goes | 2022-05-09T16:05:54.000Z | null | false | 074e673ccd419ae07caa72b4584e8dd82b8bcdf7 | [] | [
"license:mit"
] | https://huggingface.co/datasets/openclimatefix/goes/resolve/main/README.md | ---
license: mit
---
|
openclimatefix | null | null | null | false | 2 | false | openclimatefix/hrrr | 2022-02-05T17:38:23.000Z | null | false | 427e4798c7f8638c90a436c54364190c0a7f2729 | [] | [
"license:mit"
] | https://huggingface.co/datasets/openclimatefix/hrrr/resolve/main/README.md | ---
license: mit
---
|
openclimatefix | null | @article{ravuris2021skillful,
author={Suman Ravuri and Karel Lenc and Matthew Willson and Dmitry Kangin and Remi Lam and Piotr Mirowski and Megan Fitzsimons and Maria Athanassiadou and Sheleem Kashem and Sam Madge and Rachel Prudden Amol Mandhane and Aidan Clark and Andrew Brock and Karen Simonyan and Raia Hadsell an... | This dataset contains UK Nimrod rainfall radar data for 2016-2019 as used in the Skillful Precipitation Nowcasting Using Deep Generative Model of Radar paper by DeepMind. | false | 184 | false | openclimatefix/nimrod-uk-1km | 2022-06-08T14:49:03.000Z | null | false | f433a990cca7574d4ed4687e7fa969ccad0dbeb3 | [] | [] | https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/resolve/main/README.md | [Needs More Information]
# Dataset Card for UK Nimrod 1km Rainfall Radar Dataset
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
-... |
orisuchy | null | null | null | false | 2 | false | orisuchy/Descriptive_Sentences_He | 2022-03-03T10:19:56.000Z | null | false | af9b3be1603dbb85d9b98d3b8db844ed317c85e5 | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/orisuchy/Descriptive_Sentences_He/resolve/main/README.md | ---
license: afl-3.0
---
|
ought | null | null | null | false | 4 | false | ought/raft-submission | 2022-06-22T10:02:06.000Z | null | false | 0db66732f368d727d5ec941e95189872a127f336 | [] | [] | https://huggingface.co/datasets/ought/raft-submission/resolve/main/README.md | # RAFT Submission Template
Welcome to the [RAFT benchmark](https://raft.elicit.org/)! RAFT is a few-shot classification benchmark that tests language models:
- across multiple domains (lit review, tweets, customer interaction, etc.)
- on economically valuable classification tasks (someone inherently cares about the t... |
ought | null | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | Large pre-trained language models have shown promise for few-shot learning, completing text-based tasks given only a few task-specific examples. Will models soon solve classification tasks that have so far been reserved for human research assistants?
[RAFT](https://raft.elicit.org) is a few-shot classification benchm... | false | 8,108 | false | ought/raft | 2022-10-25T09:54:19.000Z | null | false | 9ee50172ea9afda2f1033c6f1b986e568b862fb3 | [] | [
"arxiv:2109.14076",
"annotations_creators:expert-generated",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"source_datasets:extended|ade_corpus_v2",
... | https://huggingface.co/datasets/ought/raft/resolve/main/README.md | ---
annotations_creators:
- expert-generated
- crowdsourced
language_creators:
- expert-generated
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
- extended|ade_corpus_v2
- extended|banking77
task_categories:
- text-classification
task_ids:
- multi-c... |
papluca | null | null | null | false | 255 | false | papluca/language-identification | 2022-07-15T10:11:23.000Z | null | false | aa56583bf2bc52b0565770607d6fc3faebecf9e2 | [] | [
"language:ar",
"language:bg",
"language:de",
"language:el",
"language:en",
"language:es",
"language:fr",
"language:hi",
"language:it",
"language:ja",
"language:nl",
"language:pl",
"language:pt",
"language:ru",
"language:sw",
"language:th",
"language:tr",
"language:ur",
"language:... | https://huggingface.co/datasets/papluca/language-identification/resolve/main/README.md | ---
annotations_creators: []
language_creators: []
language:
- ar
- bg
- de
- el
- en
- es
- fr
- hi
- it
- ja
- nl
- pl
- pt
- ru
- sw
- th
- tr
- ur
- vi
- zh
license: []
multilinguality:
- multilingual
pretty_name: Language Identification dataset
size_categories:
- unknown
source_datasets:
- extended|amazon_reviews_... |
pariajm | null | null | null | false | 2 | false | pariajm/sharif_emotional_speech_dataset | 2022-10-24T16:49:19.000Z | null | false | 34264380029d9aca8c6031b072d6fab6e1f97d10 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:fa",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:radio-plays",
"task_categories:automatic-speech-recognition",
"task_ids:speech-recognition"
] | https://huggingface.co/datasets/pariajm/sharif_emotional_speech_dataset/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: Sharif Emotional Speech Dataset (ShEMO)
size_categories:
- 1K<n<10K
source_datasets:
- radio-plays
task_categories:
- automatic-speech-recognition
task_ids:... |
parivartanayurveda | null | null | null | false | 1 | false | parivartanayurveda/Malesexproblemsayurvedictreatment | 2021-02-24T12:23:37.000Z | null | false | 18c0e0854a2e9e36b19f8524f272d861dbafc9ab | [] | [] | https://huggingface.co/datasets/parivartanayurveda/Malesexproblemsayurvedictreatment/resolve/main/README.md | Best ayurvedic medicine for erectile dysfunction. More Info :- https://www.parivartanayurveda.com/male-sexual-problems.php |
pasinit | null | @inproceedings{raganato-etal-2020-xl-wic,
title={XL-WiC: A Multilingual Benchmark for Evaluating Semantic Contextualization},
author={Raganato, Alessandro and Pasini, Tommaso and Camacho-Collados, Jose and Pilehvar, Mohammad Taher},
booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Lan... | A system's task on any of the XL-WiC datasets is to identify the intended meaning of a word in a context of a given language. XL-WiC is framed as a binary classification task. Each instance in XL-WiC has a target word w, either a verb or a noun, for which two contexts are provided. Each of these contexts triggers a spe... | false | 54 | false | pasinit/xlwic | 2022-10-25T09:54:22.000Z | null | false | cca3cfb747db5bf97b95126ec79d5b7d743f9654 | [] | [
"annotations_creators:expert-generated",
"extended:original",
"language_creators:found",
"language:en",
"language:bg",
"language:zh",
"language:hr",
"language:da",
"language:nl",
"language:et",
"language:fa",
"language:ja",
"language:ko",
"language:it",
"language:fr",
"language:de",
... | https://huggingface.co/datasets/pasinit/xlwic/resolve/main/README.md | ---
annotations_creators:
- expert-generated
extended:
- original
language_creators:
- found
language:
- en
- bg
- zh
- hr
- da
- nl
- et
- fa
- ja
- ko
- it
- fr
- de
license:
- cc-by-nc-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification... |
peixian | null | @article{DBLP:journals/corr/abs-1805-04508,
author = {Svetlana Kiritchenko and
Saif M. Mohammad},
title = {Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems},
journal = {CoRR},
volume = {abs/1805.04508},
year = {2018},
url = {http://arxiv.org/abs/... | Automatic machine learning systems can inadvertently accentuate and perpetuate inappropriate human biases. Past work on examining inappropriate biases has largely focused on just individual systems and resources. Further, there is a lack of benchmark datasets for examining inappropriate biases in system predictions. He... | false | 4 | false | peixian/equity_evaluation_corpus | 2022-10-20T23:35:15.000Z | null | false | 0f68047bb0d5d17e273ea7bd87b8964cdbe00028 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:unknown",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"tags:gender-classification"
] | https://huggingface.co/datasets/peixian/equity_evaluation_corpus/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
tags:
- gender-classification
---
# Dataset Card for equity-eva... |
peixian | null | @inproceedings{voigt-etal-2018-rtgender,
title = "{R}t{G}ender: A Corpus for Studying Differential Responses to Gender",
author = "Voigt, Rob and
Jurgens, David and
Prabhakaran, Vinodkumar and
Jurafsky, Dan and
Tsvetkov, Yulia",
booktitle = "Proceedings of the Eleventh Internatio... | RtGender is a corpus for studying responses to gender online, including posts and responses from Facebook, TED, Fitocracy, and Reddit where the gender of the source poster/speaker is known. | false | 3 | false | peixian/rtGender | 2022-10-25T09:54:24.000Z | null | false | 74ef139a2d70372a878e406056ff37b1f0d561a5 | [] | [
"annotations_creators:crowdsourced",
"language_creators:found",
"language:en",
"license:unknown",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-label-classification"
] | https://huggingface.co/datasets/peixian/rtGender/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-label-classification
---
# Dataset Card for rtGender
## Table of Conte... |
persiannlp | null | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | A Persian textual entailment task (deciding `sent1` entails `sent2`). | false | 82 | false | persiannlp/parsinlu_entailment | 2022-10-22T15:13:00.000Z | null | false | c49b2d8fa0d6476520695c52207690b7ec854043 | [] | [
"arxiv:2012.06154",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:fa",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|translated|mnli",
"task_ids:textual-entailment",
"task_ids:natural-langu... | https://huggingface.co/datasets/persiannlp/parsinlu_entailment/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|translated|mnli
task_categories:
- textual-entailment
- natural-language-inference
task_ids:
- textual-entai... |
persiannlp | null | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | A Persian query paraphrasing task (paraphrase or not, given two questions).
The questions are partly mined using Google auto-complete, and partly translated from Quora paraphrasing dataset. | false | 15 | false | persiannlp/parsinlu_query_paraphrasing | 2022-10-22T15:13:22.000Z | null | false | ec675bb3ac50c1a52317c101fe1d724b4601f47a | [] | [
"arxiv:2012.06154",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:fa",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|quora|google",
"task_ids:query-paraphrasing"
] | https://huggingface.co/datasets/persiannlp/parsinlu_query_paraphrasing/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|quora|google
task_categories:
- query-paraphrasing
task_ids:
- query-paraphrasing
---
# Dataset Card for Pe... |
persiannlp | null | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | A Persian reading comprehenion task (generating an answer, given a question and a context paragraph).
The questions are mined using Google auto-complete, their answers and the corresponding evidence documents are manually annotated by native speakers. | false | 10 | false | persiannlp/parsinlu_reading_comprehension | 2022-10-25T09:54:26.000Z | null | false | 701cb4096c7e12695123c254f757ed56b12c49b8 | [] | [
"arxiv:2012.06154",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:fa",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|wikipedia|google",
"task_categories:question-answering",
"task_ids:extra... | https://huggingface.co/datasets/persiannlp/parsinlu_reading_comprehension/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|wikipedia|google
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# Dataset Card for Per... |
persiannlp | null | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | A Persian sentiment analysis task (deciding whether a given sentence contains a particular sentiment). | false | 22 | false | persiannlp/parsinlu_sentiment | 2022-10-22T15:13:40.000Z | null | false | abecf6a01a45174b7aa9b861fcc4a586cc4c7f9d | [] | [
"arxiv:2012.06154",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:fa",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|translated|mnli",
"task_ids:sentiment-analysis"
] | https://huggingface.co/datasets/persiannlp/parsinlu_sentiment/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|translated|mnli
task_categories:
- sentiment-analysis
task_ids:
- sentiment-analysis
---
# Dataset Card for... |
persiannlp | null | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | A Persian translation dataset (English -> Persian). | false | 63 | false | persiannlp/parsinlu_translation_en_fa | 2022-10-24T16:50:37.000Z | null | false | aac51e2d1d2d464c7c0a123ffbe66c43fb30c8e7 | [] | [
"arxiv:2012.06154",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:fa",
"license:cc-by-nc-sa-4.0",
"multilinguality:fa",
"multilinguality:en",
"size_categories:1K<n<10K",
"source_datasets:extended",
"task_categories:translation",
"task_ids:translation"
] | https://huggingface.co/datasets/persiannlp/parsinlu_translation_en_fa/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- fa
- en
size_categories:
- 1K<n<10K
source_datasets:
- extended
task_categories:
- translation
task_ids:
- translation
---
# Dataset Card for PersiNLU (Machine Translation)
#... |
persiannlp | null | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | A Persian translation dataset (Persian -> English). | false | 2 | false | persiannlp/parsinlu_translation_fa_en | 2022-10-24T17:01:27.000Z | null | false | a22208a3da5b794d4d5d472942327ca17ca0e806 | [] | [
"arxiv:2012.06154",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:fa",
"license:cc-by-nc-sa-4.0",
"multilinguality:fa",
"multilinguality:en",
"size_categories:1K<n<10K",
"source_datasets:extended",
"task_categories:translation",
"task_ids:translation"
] | https://huggingface.co/datasets/persiannlp/parsinlu_translation_fa_en/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- fa
- en
size_categories:
- 1K<n<10K
source_datasets:
- extended
task_categories:
- translation
task_ids:
- translation
---
# Dataset Card for PersiNLU (Machine Translation)
#... |
peterhsu | null | null | null | false | 1 | false | peterhsu/github-issues | 2022-01-07T09:16:29.000Z | null | false | 4996d1a68fc5c56f6b888180d6f4a7d98a0cd5e2 | [] | [] | https://huggingface.co/datasets/peterhsu/github-issues/resolve/main/README.md | annotations_creators:
- no-annotation
language_creators:
- found
languages:
- en
licenses:
- unknown
multilinguality:
- monolingual
pretty_name: Practice
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-classification
- text-retrieval
task_ids:
- multi-class-classification
- multi-label-cl... |
phongdtd | null | null | \ | false | 1 | false | phongdtd/VinDataVLSP | 2022-01-26T06:49:13.000Z | null | false | 8a731c1701fe9261accecdeee010c82202e7ef40 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/phongdtd/VinDataVLSP/resolve/main/README.md | ---
license: apache-2.0
---
|
phongdtd | null | null | \ | false | 1 | false | phongdtd/youtube_casual_audio | 2022-11-01T13:23:24.000Z | null | false | 22ddd6021c9c6cae167842867026230685ce3973 | [] | [
"multilinguality:190K<n<200K",
"source_datasets:extended|youtube",
"task_categories:automatic-speech-recognition",
"Pretty_name:Youtube Casual Audio",
"Annotations_creators:crowdsourced",
"Language_creators:datlq",
"Languages:vi",
"Licenses:cc0-1.0"
] | https://huggingface.co/datasets/phongdtd/youtube_casual_audio/resolve/main/README.md | ---
multilinguality:
vi:
- 190K<n<200K
source_datasets:
- extended|youtube
task_categories:
- automatic-speech-recognition
task_ids: []
Pretty_name: Youtube Casual Audio
Annotations_creators:
- crowdsourced
Language_creators:
- datlq
Languages:
- vi
Licenses:
- cc0-1.0
---
# Dataset Card for common_voice
## Table... |
pierreguillou | null | null | null | false | 17 | false | pierreguillou/lener_br_finetuning_language_model | 2022-10-25T09:54:32.000Z | lener-br | false | 59d44d489b64b128c388a5f27c4fa66dd6c3a080 | [] | [
"language:pt",
"multilinguality:monolingual",
"task_ids:language-modeling",
"datasets:lener_br",
"tags:lener_br"
] | https://huggingface.co/datasets/pierreguillou/lener_br_finetuning_language_model/resolve/main/README.md | ---
language:
- pt
multilinguality:
- monolingual
task_ids:
- language-modeling
paperswithcode_id: lener-br
pretty_name: LeNER-Br language modeling
datasets:
- lener_br
tags:
- lener_br
---
# Dataset Card for "LeNER-Br language modeling"
## Dataset Summary
The LeNER-Br language modeling dataset is a collection of le... |
pierresi | null | @article{park2019cord,
title={CORD: A Consolidated Receipt Dataset for Post-OCR Parsing},
author={Park, Seunghyun and Shin, Seung and Lee, Bado and Lee, Junyeop and Surh, Jaeheung and Seo, Minjoon and Lee, Hwalsuk}
booktitle={Document Intelligence Workshop at Neural Information Processing Systems}
year={2019}
} | https://github.com/clovaai/cord/ | false | 1 | false | pierresi/cord | 2021-10-13T16:47:07.000Z | null | false | d15dadc66c01f73d66f8b9947ebfc7db06cbb38e | [] | [] | https://huggingface.co/datasets/pierresi/cord/resolve/main/README.md | CORD: A Consolidated Receipt Dataset for Post-OCR Parsing. |
pietrolesci | null | @inproceedings{Zhang2015CharacterlevelCN,
title={Character-level Convolutional Networks for Text Classification},
author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
booktitle={NIPS},
year={2015}
} | 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... | false | 101 | false | pietrolesci/ag_news | 2022-10-08T13:03:42.000Z | ag-news | false | 00422e4eaf5c0265df0a3b5cbf9ebbac364958e7 | [] | [
"annotations_creators:found",
"language_creators:found",
"language:en",
"license:unknown",
"multilingualism:monolingual",
"size_categories:100K<n<1M",
"source_datasets:ag_news",
"task_categories:text-classification",
"task_ids:topic-classification"
] | https://huggingface.co/datasets/pietrolesci/ag_news/resolve/main/README.md | ---
YAML tags:
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilingualism:
- monolingual
paperswithcode_id: ag-news
pretty_name: ag_news
size_categories:
- 100K<n<1M
source_datasets:
- ag_news
task_categories:
- text-classification
task_ids:
- topic-classification
---
#... |
pile-of-law | null | @misc{hendersonkrass2022pileoflaw,
url = {https://arxiv.org/abs/2207.00220},
author = {Henderson, Peter and Krass, Mark S. and Zheng, Lucia and Guha, Neel and Manning, Christopher D. and Jurafsky, Dan and Ho, Daniel E.},
title = {Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Sourc... | We curate a large corpus of legal and administrative data. The utility of this data is twofold: (1) to aggregate legal and administrative data sources that demonstrate different norms and legal standards for data filtering; (2) to collect a dataset that can be used in the future for pretraining legal-domain language mo... | false | 1,485 | false | pile-of-law/pile-of-law | 2022-07-14T06:13:16.000Z | null | false | 4232278db7c57ef28ad2ee1a667e646b0f308fb5 | [] | [
"arxiv:2207.00220",
"annotations_creators:no-annotation",
"language_creators:found",
"language:en",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"task_categories:fill-mask",
"task_ids:masked-language-modeling"
] | https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
pretty_name: pile-of-law
size_categories:
- 10M<n<100M
source_datasets: []
task_categories:
- fill-mask
task_ids:
- masked-language-modeling
viewer: false
---
# Dataset Card for... |
pmc | null | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | The PMC Open Access Subset includes more than 3.4 million journal articles and preprints that are made available under
license terms that allow reuse.
Not all articles in PMC are available for text mining and other reuse, many have copyright protection, however articles
in the PMC Open Access Subset are made availabl... | false | 3 | false | pmc/open_access | 2022-10-25T14:32:29.000Z | null | false | d8916155e305a52ac9de76681a09fbab29bc45d5 | [] | [
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"language:en",
"license:cc0-1.0",
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"license:cc-by-nc-4.0",
"license:cc-by-nc-sa-4.0",
"license:cc-by-nc-nd-4.0",
"license:other",
"license:unknown",
... | https://huggingface.co/datasets/pmc/open_access/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- cc0-1.0
- cc-by-4.0
- cc-by-sa-4.0
- cc-by-nd-4.0
- cc-by-nc-4.0
- cc-by-nc-sa-4.0
- cc-by-nc-nd-4.0
- other
- unknown
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_cat... |
MLCommons | null | @inproceedings{mazumder2021multilingual,
title={Multilingual Spoken Words Corpus},
author={Mazumder, Mark and Chitlangia, Sharad and Banbury, Colby and Kang, Yiping and Ciro, Juan Manuel and Achorn, Keith and Galvez, Daniel and Sabini, Mark and Mattson, Peter and Kanter, David and others},
booktitle={Thirty-fifth... | Multilingual Spoken Words Corpus is a large and growing audio dataset of spoken
words in 50 languages collectively spoken by over 5 billion people, for academic
research and commercial applications in keyword spotting and spoken term search,
licensed under CC-BY 4.0. The dataset contains more than 340,000 keywords,
tot... | false | 28 | false | MLCommons/ml_spoken_words | 2022-10-24T08:45:19.000Z | null | false | 273f583343799b0a55f39e9f3bc8fdc3c01f44a8 | [] | [
"annotations_creators:machine-generated",
"language_creators:other",
"language:ar",
"language:as",
"language:br",
"language:ca",
"language:cnh",
"language:cs",
"language:cv",
"language:cy",
"language:de",
"language:dv",
"language:el",
"language:en",
"language:eo",
"language:es",
"lan... | https://huggingface.co/datasets/MLCommons/ml_spoken_words/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- other
language:
- ar
- as
- br
- ca
- cnh
- cs
- cv
- cy
- de
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- el
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- eo
- es
- et
- eu
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- fr
- fy
- ga
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- ia
- id
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- ka
- ky
- lt
- lv
- mn
- mt
- nl
- or
- pl
- pt
- rm
- ro
- ru
- rw
- sah
- sk
- sl
- sv
- ta
- tr
- tt
- uk
... |
pritamdeka | null | null | null | false | 2 | false | pritamdeka/cord-19-abstract | 2022-02-01T23:58:54.000Z | null | false | c2280ffaf80629ba1b1be5dad6b08b93cd395371 | [] | [] | https://huggingface.co/datasets/pritamdeka/cord-19-abstract/resolve/main/README.md | # Dataset Card for [pritamdeka/cord-19-abstract]
## Dataset Description
### Dataset Summary
This is a modified [cord19](https://huggingface.co/datasets/cord19) dataset which contains only the abstract field. This can be used directly for language modelling tasks.
### Languages
English
### Citation Information... |
pritamdeka | null | null | null | false | 1 | false | pritamdeka/cord-19-fulltext | 2022-02-05T02:29:13.000Z | null | false | 53f4c17ae8f06d9aabeae7230194e1528f9cd7aa | [] | [] | https://huggingface.co/datasets/pritamdeka/cord-19-fulltext/resolve/main/README.md | # Dataset Card for [pritamdeka/cord-19-fulltext]
## Dataset Description
### Dataset Summary
This is a modified [cord19](https://huggingface.co/datasets/cord19) dataset which contains only the fulltext field. This can be used directly for language modelling tasks.
### Languages
English
### Citation Information... |
priya3301 | null | null | null | false | 1 | false | priya3301/Graduation_admission | 2021-05-14T15:42:30.000Z | null | false | d1d759e8c2ab06e5958a2054d1987ea046f261c8 | [] | [] | https://huggingface.co/datasets/priya3301/Graduation_admission/resolve/main/README.md | |
prk | null | \
@article{2016arXiv160605250R,
author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
Konstantin and {Liang}, Percy},
title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
journal = {arXiv e-prints},
year = 2016,
eid = {arXiv:16... | \
combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers
to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but
also determine when no answer is supported by the paragraph and abstain fr... | false | 1 | false | prk/testsq | 2022-02-25T13:52:13.000Z | null | false | be260110deb051db63b66038bbb00a5ebfe996c6 | [] | [] | https://huggingface.co/datasets/prk/testsq/resolve/main/README.md | |
project2you | null | null | null | false | 1 | false | project2you/asr | 2021-12-02T08:08:08.000Z | null | false | d4ab94cacce28137358c0ad2de765e2fafa98653 | [] | [] | https://huggingface.co/datasets/project2you/asr/resolve/main/README.md | Common Voice 7
วันที่ 2021-07-21
ขนาด5 GB
รุ่น th_255h_2021-07-21
จำนวนชั่วโมงทั้งหมดที่ตรวจสอบ133
จำนวนชั่วโมงโดยรวม255
สัญญาอนุญาตCC-0
จำนวนเสียง7,212
รูปแบบเสียงMP3
|
projecte-aina | null | AnCora Catalan NER.
This is a dataset for Named Eentity Reacognition (NER) from Ancora corpus adapted for
Machine Learning and Language Model evaluation purposes.
Since multiwords (including Named Entites) in the original Ancora corpus are aggregated as
... | false | 1 | false | projecte-aina/ancora-ca-ner | 2022-11-16T15:27:39.000Z | null | false | 4b11fdf4b81e7c03b2dfa465a283a990e4cfaa51 | [] | [
"arxiv:2107.07903",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ca",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:unknown"
] | https://huggingface.co/datasets/projecte-aina/ancora-ca-ner/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: ancora-ca-ner
size_categories:
- unknown
source_datasets: []
task_categories: []
task_ids: []
---
# Dataset Card for AnCora-Ca-NER
## Dataset Description
- **Websit... | |
projecte-aina | null | @misc{degibert2022sequencetosequence,
title={Sequence-to-Sequence Resources for Catalan},
author={Ona de Gibert and Ksenia Kharitonova and Blanca Calvo Figueras and Jordi Armengol-Estapé and Maite Melero},
year={2022},
eprint={2202.06871},
archivePrefix={arXiv},
primaryClass={cs.CL}... | CaSum is a summarization dataset. It is extracted from a newswire corpus crawled from the Catalan News Agency. The corpus consists of 217,735 instances that are composed by the headline and the body. | false | 1 | false | projecte-aina/casum | 2022-11-10T12:54:49.000Z | null | false | c3cc8d5903cee19458e6410833fb04bbe3f589de | [] | [
"arxiv:2202.06871",
"annotations_creators:machine-generated",
"language_creators:expert-generated",
"language:ca",
"license:cc-by-nc-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"task_categories:summarization"
] | https://huggingface.co/datasets/projecte-aina/casum/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- expert-generated
language:
- ca
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets: []
task_categories:
- summarization
task_ids: []
pretty_name: casum
---
# Dataset Card for CaSum
## Table of Contents
- ... |
projecte-aina | null | @inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de ... | The Catalan General Crawling Corpus is a 435-million-token web corpus of Catalan built from the web. It has been obtained by crawling the 500 most popular .cat and .ad domains during July 2020. It consists of 434.817.705 tokens, 19.451.691 sentences and 1.016.114 documents. Documents are separated by single new lines. ... | false | 1 | false | projecte-aina/catalan_general_crawling | 2022-11-10T13:03:33.000Z | null | false | af5d51b39545ee0cb2a88a64ec67931ec738bf38 | [] | [
"arxiv:2107.07903",
"annotations_creators:no-annotation",
"language_creators:found",
"language:ca",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"task_categories:fill-mask"
] | https://huggingface.co/datasets/projecte-aina/catalan_general_crawling/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Catalan General Crawling
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- fill-mask
task_ids: []
---
# Dataset Card for Catalan General Crawling... |
projecte-aina | null | @inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de ... | The Catalan Government Crawling Corpus is a 39-million-token web corpus of Catalan built from the web. It has been obtained by crawling the .gencat domain and subdomains, belonging to the Catalan Government during September and October 2020. It consists of 39.117.909 tokens, 1.565.433 sentences and 71.043 documents. Do... | false | 1 | false | projecte-aina/catalan_government_crawling | 2022-11-10T13:00:45.000Z | null | false | a7246da17b5710522410cc416d071f49488155a7 | [] | [
"arxiv:2107.07903",
"annotations_creators:no-annotation",
"language_creators:found",
"language:ca",
"license:cc0-1.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:fill-mask"
] | https://huggingface.co/datasets/projecte-aina/catalan_government_crawling/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc0-1.0
multilinguality:
- monolingual
pretty_name: Catalan Government Crawling
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- fill-mask
task_ids: []
---
# Dataset Card for Catalan Government Cr... |
projecte-aina | null | @inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de ... | The Catalan Textual Corpus is a 1760-million-token web corpus of Catalan built from several sources: existing corpus such as DOGC, CaWac (non-dedup version), Oscar (unshuffled version), Open Subtitles, Catalan Wikipedia; and three brand new crawlings: the Catalan General Crawling, obtained by crawling the 500 most popu... | false | 2 | false | projecte-aina/catalan_textual_corpus | 2022-11-10T12:59:31.000Z | null | false | a38fffc6ed9eab968b0f5bfc030e8f05f34509e4 | [] | [
"arxiv:2107.07903",
"annotations_creators:no-annotation",
"language_creators:found",
"language:ca",
"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"source_datasets:extended|opus_dogc",
"source_datasets:extended|cawac",
"source_dat... | https://huggingface.co/datasets/projecte-aina/catalan_textual_corpus/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: Catalan Textual Corpus
size_categories:
- 10M<n<100M
source_datasets:
- original
- extended|opus_dogc
- extended|cawac
- extended|oscar
- extended|open_subtitles
- exte... |
projecte-aina | null | @dataset{kulebi_baybars_2021_5541827,
author = {Külebi, Baybars},
title = {{ParlamentParla - Speech corpus of Catalan
Parliamentary sessions}},
month = oct,
year = 2021,
publisher = {Zenodo},
version = {v2.0},
doi = {10.5281/zenodo.5541827},... | This is the ParlamentParla speech corpus for Catalan prepared by Col·lectivaT. The audio segments were extracted from recordings the Catalan Parliament (Parlament de Catalunya) plenary sessions, which took place between 2007/07/11 - 2018/07/17. We aligned the transcriptions with the recordings and extracted the corpus.... | false | 6 | false | projecte-aina/parlament_parla | 2022-11-10T12:51:41.000Z | null | false | 3b73f758a1bae3305271ebd8947b37a6647a8dbb | [] | [
"annotations_creators:found",
"language_creators:found",
"language:ca",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:automatic-speech-recognition",
"task_categories:text-generation",
"t... | https://huggingface.co/datasets/projecte-aina/parlament_parla/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
clean:
- 10K<n<100K
other:
- 100K<n<1M
source_datasets:
- original
task_categories:
- automatic-speech-recognition
- text-generation
task_ids:
- language-modeling
- sp... |
projecte-aina | null | Rodriguez-Penagos, Carlos Gerardo, Armentano-Oller, Carme, Gonzalez-Agirre, Aitor, & Gibert Bonet, Ona. (2021).
Semantic Textual Similarity in Catalan (Version 1.0.1) [Data set].
Zenodo. http://doi.org/10.5281/zenodo.4761434 | Semantic Textual Similarity in Catalan.
STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan.
It consists of more than 3000 sentence pairs, annotated with the semantic similarity between them,
using a scale from 0 (no similarity at all) to 5... | false | 1 | false | projecte-aina/sts-ca | 2022-11-16T15:24:02.000Z | null | false | c51d11e45e780bce09f4f71e1dbf4c3c1181c041 | [] | [
"arxiv:2107.07903",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ca",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"task_categories:text-classification",
"task_ids:semantic-similarity-scoring",
"task_ids:text-scoring"
] | https://huggingface.co/datasets/projecte-aina/sts-ca/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets: []
task_categories:
- text-classification
task_ids:
- semantic-similarity-scoring
- text-scoring
pretty_name: sts-ca
---
# Dataset Card ... |
projecte-aina | null | @inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
... | TECA consists of two subsets of textual entailment in Catalan, *catalan_TE1* and *vilaweb_TE*, which contain 14997 and 6166 pairs of premises and hypotheses, annotated according to the inference relation they have (implication, contradiction or neutral). This dataset was developed by BSC TeMU as part of the AINA projec... | false | 3 | false | projecte-aina/teca | 2022-11-10T12:58:08.000Z | null | false | c7cdb32a1ade077ad15ddd65279fecf8d4728368 | [] | [
"arxiv:2107.07903",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ca",
"license:cc-by-nc-nd-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"task_categories:text-classification",
"task_ids:natural-language-inference"
] | https://huggingface.co/datasets/projecte-aina/teca/resolve/main/README.md | ---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-nc-nd-4.0
multilinguality:
- monolingual
pretty_name: teca
size_categories:
- unknown
source_datasets: []
task_categories:
- text-classification
task_ids:
- natural-language-inference
---
# Dataset Card... |
projecte-aina | null | Carrino, Casimiro Pio, Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
TeCla: Text Classification Catalan dataset (Version 1.0) [Data set].
Zenodo. http://doi.org/10.5281/zenodo.4627198 | TeCla: Text Classification Catalan dataset
Catalan News corpus for Text classification, crawled from ACN (Catalan News Agency) site: www.acn.cat
Corpus de notícies en català per a classificació textual, extret del web de l'Agència Catalana de Notícies - www.acn.cat | false | 4 | false | projecte-aina/tecla | 2022-11-16T15:26:50.000Z | null | false | 654ddfc2364c5439797259e06d0357df16cd39a1 | [] | [
"arxiv:2107.07903",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ca",
"license:cc-by-nc-nd-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"task_categories:text-classification",
"task_ids:multi-class-classification"
] | https://huggingface.co/datasets/projecte-aina/tecla/resolve/main/README.md | ---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-nc-nd-4.0
multilinguality:
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pretty_name: tecla
size_categories:
- unknown
source_datasets: []
task_categories:
- text-classification
task_ids:
- multi-class-classification
---
# Dataset Card ... |
projecte-aina | null | Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
VilaQuAD: an extractive QA dataset for catalan, from Vilaweb newswire text
[Data set]. Zenodo. https://doi.org/10.5281/zenodo.4562337 | This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).
VilaQuad articles are extracted from the daily Vilaweb (www.vilaweb.cat) and used under CC-by-nc-sa-nd (https://creativecommons.org/licenses/by-nc-nd/3.0/deed.ca) licence.
This dataset ca... | false | 1 | false | projecte-aina/vilaquad | 2022-11-16T15:28:53.000Z | null | false | 0e042fcd5f1c7ff593ce465f3f8877ee985914b2 | [] | [
"arxiv:2107.07903",
"arxiv:1606.05250",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ca",
"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:question-answering",
"task_ids:extractive-qa"... | https://huggingface.co/datasets/projecte-aina/vilaquad/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
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pretty_name: VilaQuAD
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# Dataset Card for VilaQuAD
##... |
projecte-aina | null | @misc{degibert2022sequencetosequence,
title={Sequence-to-Sequence Resources for Catalan},
author={Ona de Gibert and Ksenia Kharitonova and Blanca Calvo Figueras and Jordi Armengol-Estapé and Maite Melero},
year={2022},
eprint={2202.06871},
archivePrefix={arXiv},
primaryClass={cs.CL}... | VilaSum is a summarization dataset for evaluation. It is extracted from a newswire corpus crawled from Vilaweb. The corpus consists of 13,843 instances that are composed by the headline and the body. | false | 1 | false | projecte-aina/vilasum | 2022-11-10T12:50:36.000Z | null | false | 42c59625386b88e5e004dec1f85cba37d69b07fb | [] | [
"arxiv:2202.06871",
"annotations_creators:machine-generated",
"language_creators:expert-generated",
"language:ca",
"license:cc-by-nc-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"task_categories:summarization"
] | https://huggingface.co/datasets/projecte-aina/vilasum/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- expert-generated
language:
- ca
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets: []
task_categories:
- summarization
task_ids: []
pretty_name: casum
---
# Dataset Card for VilaSum
## Table of Contents
... |
projecte-aina | null | Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
ViquiQuAD: an extractive QA dataset from Catalan Wikipedia (Version ViquiQuad_v.1.0.1)
[Data set]. Zenodo. http://doi.org/10.5281/zenodo.4761412 | ViquiQuAD: an extractive QA dataset from Catalan Wikipedia.
This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations)
articles in the Catalan Wikipedia "Viquipèdia" (ca.wikipedia.org), and 1 to 5 questions with their
answer for each fragment. Viquipedia articles are used u... | false | 1 | false | projecte-aina/viquiquad | 2022-11-16T15:28:11.000Z | null | false | df5fe3916d430e37aecc1446f1b995c8f7136d8c | [] | [
"arxiv:2107.07903",
"arxiv:1606.05250",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ca",
"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:question-answering",
"task_ids:extractive-q... | https://huggingface.co/datasets/projecte-aina/viquiquad/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
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pretty_name: ViquiQuAD
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# ViquiQuAD, An extractive Q... |
projecte-aina | null | ADD CITATION | professional translation into Catalan of Winograd NLI dataset as published in GLUE Benchmark.
The Winograd NLI dataset presents 855 sentence pairs,
in which the first sentence contains an ambiguity and the second one a possible interpretation of it.
The label indicates if ... | false | 1 | false | projecte-aina/wnli-ca | 2022-11-16T15:25:12.000Z | null | false | 23761fd18c32531ab63271267bf1fb99e3ad909a | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:ca",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:extended|glue",
"task_categories:text-classification",
"task_ids:natural-language-inference"
] | https://huggingface.co/datasets/projecte-aina/wnli-ca/resolve/main/README.md | ---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
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pretty_name: wnli-ca
size_categories:
- unknown
source_datasets:
- extended|glue
task_categories:
- text-classification
task_ids:
- natural-language-inference
---
# ... |
projecte-aina | null | Carlos Gerardo Rodriguez-Penagos, & Carme Armentano-Oller. (2021). XQuAD-ca [Data set].
Zenodo. http://doi.org/10.5281/zenodo.4757559 | Professional translation into Catalan of XQuAD dataset (https://github.com/deepmind/xquad).
XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating
cross-lingual question answering performance.
The dataset consists of a subset of 240... | false | 2 | false | projecte-aina/xquad-ca | 2022-11-16T15:29:39.000Z | null | false | 6286f625078d7059f9f6a1086811edf06f8d1a79 | [] | [
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"language_creators:found",
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"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"task_categories:question-answering",
"task_ids:extractive-qa"
] | https://huggingface.co/datasets/projecte-aina/xquad-ca/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: xquad-ca
size_categories:
- unknown
source_datasets: []
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# Dataset Card for XQuAD-Ca
## Table of... |
pstroe | null | null | null | false | 8 | false | pstroe/cc100-latin | 2022-11-02T14:28:12.000Z | null | false | 1df6ec7dce31491d28f5af112c6ad3a70716a159 | [] | [] | https://huggingface.co/datasets/pstroe/cc100-latin/resolve/main/README.md | ## Latin part of cc100 corpus
This dataset contains parts of the Latin part of the [cc100](http://data.statmt.org/cc-100/) dataset. It was used to train a [RoBERTa-based LM model](https://huggingface.co/pstroe/roberta-base-latin-cased) with huggingface.
### Preprocessing
I undertook the following preprocessing steps:... |
puffy310 | null | null | null | false | 2 | false | puffy310/yandset | 2022-03-01T06:18:16.000Z | null | false | 1e7db1d2e6e0984ff24efa50133d3adc90205429 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/puffy310/yandset/resolve/main/README.md | ---
license: apache-2.0
---
|
pulmo | null | null | null | false | 1 | false | pulmo/chest_xray | 2021-07-25T15:10:08.000Z | null | false | c8cfe7c55b5245ef9b48edd2ca37e1a1df6a04ff | [] | [] | https://huggingface.co/datasets/pulmo/chest_xray/resolve/main/README.md | COVID-19 image data collection |
qa4pc | null | null | null | false | 1 | false | qa4pc/QA4PC | 2021-11-23T11:22:13.000Z | null | false | f05fdf09596bd7fcf8b2c14cb93305e7b7a7fa54 | [] | [] | https://huggingface.co/datasets/qa4pc/QA4PC/resolve/main/README.md | ## QA4PC Dataset (paper: Cross-Policy Compliance Detection via Question Answering)
### Train Sets
To create training set or entailment and QA tasks, download and convert the ShARC data using the following commands:
```
wget https://sharc-data.github.io/data/sharc1-official.zip
unzip sharc1-official.zip
python create... |
qanastek | null | @misc{
universaldependencies,
title={UniversalDependencies/UD_French-GSD},
url={https://github.com/UniversalDependencies/UD_French-GSD}, journal={GitHub},
author={UniversalDependencies}
}
@inproceedings{mcdonald-etal-2013-universal,
title = {{U}niversal {D}ependency Annotation for Multilingual Pars... | null | false | 4 | false | qanastek/ANTILLES | 2022-10-24T17:13:19.000Z | null | false | 9a6b58c803ec27ad00117420022761b2a69cf526 | [] | [
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"language:fr",
"language_bcp47:fr-FR",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:token-classification",
"task_ids:part-of-speech-tagging"
] | https://huggingface.co/datasets/qanastek/ANTILLES/resolve/main/README.md | ---
annotations_creators:
- machine-generated
- expert-generated
language_creators:
- found
language:
- fr
language_bcp47:
- fr-FR
pretty_name: ANTILLES
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- part-of-speech-tagging
---
# ANTILLES : An Open French Li... |
qanastek | null | @article{10.1007/s10579-014-9277-0,
author = {Steinberger, Ralf and Ebrahim, Mohamed and Poulis, Alexandros and Carrasco-Benitez, Manuel and Schl\"{u}ter, Patrick and Przybyszewski, Marek and Gilbro, Signe},
title = {An Overview of the European Union's Highly Multilingual Parallel Corpora},
year = {2014},
issue_date = ... | null | false | 1 | false | qanastek/ECDC | 2022-10-23T04:59:32.000Z | null | false | 30a7e525efbb3094204e7e9a49bc46fd0ec7afb6 | [] | [
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"license:other",
"multilinguality:en-sv",
"multilinguality:en-pl",
"multilinguality:en-hu",
"multilinguality:en-lt",
"multilinguality:en-sk",
"multilinguality:en-ga",
"m... | https://huggingface.co/datasets/qanastek/ECDC/resolve/main/README.md | ---
annotations_creators:
- machine-generated
- expert-generated
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- en-sv
- en-pl
- en-hu
- en-lt
- en-sk
- en-ga
- en-fr
- en-cs
- en-el
- en-it
- en-lv
- en-da
- en-nl
- en-bg
- en-is
- en-ro
- en-no
- en-pt
- en-es
- en-et
- en-mt
- en-sl
- e... |
qanastek | null | @inproceedings{losch-etal-2018-european,
title = "European Language Resource Coordination: Collecting Language Resources for Public Sector Multilingual Information Management",
author = {L{\"o}sch, Andrea and
Mapelli, Val{\'e}rie and
Piperidis, Stelios and
Vasi{\c{l}}jevs, Andrejs and
... | null | false | 4 | false | qanastek/ELRC-Medical-V2 | 2022-10-24T17:15:17.000Z | null | false | 7f5633e7f9903947a9e51ab0e12ff483574aeebf | [] | [
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"language:bg",
"language:cs",
"language:da",
"language:de",
"language:el",
"language:es",
"language:et",
"language:fi",
"language:fr",
"language:ga",
"language:hr"... | https://huggingface.co/datasets/qanastek/ELRC-Medical-V2/resolve/main/README.md | ---
annotations_creators:
- machine-generated
- expert-generated
language_creators:
- found
language:
- en
- bg
- cs
- da
- de
- el
- es
- et
- fi
- fr
- ga
- hr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
- ro
- sk
- sl
- sv
multilinguality:
- multilingual
pretty_name: ELRC-Medical-V2
size_categories:
- 100K<n<1M
source_d... |
qanastek | null | @inproceedings{tiedemann-2012-parallel,
title = Parallel Data, Tools and Interfaces in OPUS,
author = {
Tiedemann, Jorg
},
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)",
month = may,
year = 2012,
address = Istanbul, Turk... | null | false | 18 | false | qanastek/EMEA-V3 | 2022-10-22T15:18:02.000Z | null | false | 783edb3e7341c61ec455b253654550c6bdbdfa89 | [] | [
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"language:bg",
"language:cs",
"language:da",
"language:de",
"language:el",
"language:en",
"language:es",
"language:et",
"language:fi",
"language:fr",
"language:hu",
"language:it"... | https://huggingface.co/datasets/qanastek/EMEA-V3/resolve/main/README.md | ---
annotations_creators:
- machine-generated
- expert-generated
language_creators:
- found
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
- ro
- sk
- sl
- sv
multilinguality:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
-... |
qanastek | null | @inproceedings{bojar-etal-2016-findings,
title = Findings of the 2016 Conference on Machine Translation,
author = {
Bojar, Ondrej and
Chatterjee, Rajen and
Federmann, Christian and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Jimeno Yepes, Antonio and
... | WMT'16 Biomedical Translation Task - PubMed parallel datasets
http://www.statmt.org/wmt16/biomedical-translation-task.html | false | 1 | false | qanastek/WMT-16-PubMed | 2022-10-22T15:20:12.000Z | null | false | d74986fdd2f8aa542ca4b875d9fd37979518a027 | [] | [
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"language:bg",
"language:cs",
"language:da",
"language:de",
"language:el",
"language:en",
"language:es",
"language:et",
"language:fi",
"language:fr",
"language:hu",
"language:it"... | https://huggingface.co/datasets/qanastek/WMT-16-PubMed/resolve/main/README.md | ---
annotations_creators:
- machine-generated
- expert-generated
language_creators:
- found
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
- ro
- sk
- sl
- sv
multilinguality:
- multilingual
pretty_name: WMT-16-PubMed
size_categories:
- 100K<n<1M
source_datasets:
- e... |
qwant | null | @inproceedings{cattan:hal-03336060,
TITLE = {{On the Usability of Transformers-based models for a French Question-Answering task}},
AUTHOR = {Cattan, Oralie and Servan, Christophe and Rosset, Sophie},
URL = {https://hal.archives-ouvertes.fr/hal-03336060},
BOOKTITLE = {{Recent Advances in Natural Language Proces... | SQuAD-fr is a French translated version of the Stanford Question Answering Dataset (SQuAD), the reference corpus to evaluate question answering models' performances in English.
It consists of 100K question-answer pairs on 500+ articles derived from the original English dataset and represents a large-scale dataset for c... | false | 4 | false | qwant/squad_fr | 2022-10-25T09:54:34.000Z | squad | false | 184a0dba68c92beb3c91a816042f1fe0479e3845 | [] | [
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"language:fr-FR",
"license:cc-by-4.0",
"multilinguality:monolingual",
"multilinguality:translation",
"size_categories:10K<n<100K",
"source_datasets:extended|squad",
"task_categories:question-answering",
"task_ids:extr... | https://huggingface.co/datasets/qwant/squad_fr/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- fr-FR
license:
- cc-by-4.0
multilinguality:
- monolingual
- translation
paperswithcode_id: squad
pretty_name: SQuAD-fr
size_categories:
- 10K<n<100K
source_datasets:
- extended|squad
task_categories:
- question-answering
ta... |
rahular | null | @inproceedings{aralikatte-etal-2021-itihasa,
title = "Itihasa: A large-scale corpus for {S}anskrit to {E}nglish translation",
author = "Aralikatte, Rahul and
de Lhoneux, Miryam and
Kunchukuttan, Anoop and
S{\o}gaard, Anders",
booktitle = "Proceedings of the 8th Workshop on Asian Transla... | A Sanskrit-English machine translation dataset. | false | 194 | false | rahular/itihasa | 2022-10-24T18:06:01.000Z | null | false | 56645be151b61e1143597f922ccf666b43a5c02b | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:sa",
"language:en",
"license:apache-2.0",
"multilinguality:translation",
"size_categories:unknown",
"source_datasets:original",
"task_categories:text2text-generation",
"metrics:bleu",
"metrics:sacrebleu",
... | https://huggingface.co/datasets/rahular/itihasa/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- sa
- en
license:
- apache-2.0
multilinguality:
- translation
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text2text-generation
task_ids: []
pretty_name: Itihasa
metrics:
- bleu
- sacrebleu
- rouge... |
rajeshradhakrishnan | null | null | null | false | 1 | false | rajeshradhakrishnan/malayalam_2020_wiki | 2022-07-04T11:01:57.000Z | null | false | 2790b7b6c85e85b97f1b8eda171ba3369cc134b1 | [] | [] | https://huggingface.co/datasets/rajeshradhakrishnan/malayalam_2020_wiki/resolve/main/README.md | ��T h i s d a t a s e t i s f r o m t h e c o m m o n - c r a w l - m a l a y a l a m r e p o : h t t p s : / / g i t h u b . c o m / q b u r s t / c o m m o n - c r a w l - m a l a y a l a m |
rajeshradhakrishnan | null | @article{kunchukuttan2020indicnlpcorpus,
title={AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic Languages},
author={Anoop Kunchukuttan and Divyanshu Kakwani and Satish Golla and Gokul N.C. and Avik Bhattacharyya and Mitesh M. Khapra and Pratyush Kumar},
year={2020},
journal=... | The AI4Bharat-IndicNLP dataset is an ongoing effort to create a collection of large-scale,
general-domain corpora for Indian languages. Currently, it contains 2.7 billion words for 10 Indian languages from two language families.
We share pre-trained word embeddings trained on these corpora.
We create news article cat... | false | 1 | false | rajeshradhakrishnan/malayalam_news | 2022-07-04T05:57:19.000Z | null | false | 7aa5ac224f3acc8600c6c8c648c18b5dd6d3cf41 | [] | [] | https://huggingface.co/datasets/rajeshradhakrishnan/malayalam_news/resolve/main/README.md | ## IndicNLP News Article Classification Dataset
We used the IndicNLP text corpora to create classification datasets comprising news articles and their categories for 9 languages. The dataset is balanced across classes. The following table contains the statistics of our dataset:
| Language | Classes ... |
rajeshradhakrishnan | null | @article{qburst,
title={Common Crawl - Malayalam},
author={n.d},
year={2020},
journal={n.d},
} | Common Crawl - Malayalam. | false | 1 | false | rajeshradhakrishnan/malayalam_wiki | 2022-07-04T12:21:06.000Z | wikitext-2 | false | e4fbbe300e28a65c40334241aa4e9f1c4e155852 | [] | [
"annotations_creators:no-annotation",
"language:en",
"language_creators:crowdsourced",
"license:cc-by-sa-3.0",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"tas... | https://huggingface.co/datasets/rajeshradhakrishnan/malayalam_wiki/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language:
- en
language_creators:
- crowdsourced
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
paperswithcode_id: wikitext-2
pretty_name: rajeshradhakrishnan/malayalam_wiki
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
- fil... |
ranim | null | null | null | false | 1 | false | ranim/Algerian-Arabic | 2022-11-04T18:17:42.000Z | null | false | 036d6b4f0077262f485de3d16085244408af2430 | [] | [] | https://huggingface.co/datasets/ranim/Algerian-Arabic/resolve/main/README.md |
***This dataset contains 1.5k Algerian Arabic sentiment comments classified into two classes
subjective positive, subjective negative.
***This dataset is collected and annotated by RANIM for Arabic NLP Solutions, feel free to use it.
***We appreciate citing our company name "RANIM for Arabic NLP Solutions" when u... |
rays2pix | null | null | null | false | 1 | false | rays2pix/example | 2021-07-05T11:29:59.000Z | null | false | 584b85c66dda5e43f64964267554329ec0675694 | [] | [] | https://huggingface.co/datasets/rays2pix/example/resolve/main/README.md | |
rbawden | null | null | null | false | 249 | false | rbawden/DiaBLa | 2022-10-25T14:21:10.000Z | null | false | 5345895c56a601afe1a98519ce3199be60a27dba | [] | [
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language:en",
"language:fr",
"license:cc-by-sa-4.0",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:translation",
"language_bcp47:en-UK",
"language_bcp47:fr-FR"
] | https://huggingface.co/datasets/rbawden/DiaBLa/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
- fr
license:
- cc-by-sa-4.0
multilinguality:
- translation
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- translation
task_ids: []
pretty_name: DiaBLa
language_bcp47:
- en-UK
- fr-FR
---
# Dataset... |
rewardsignal | null | null | null | false | 4 | false | rewardsignal/reddit_writing_prompts | 2021-06-03T15:22:49.000Z | null | false | 806ef7fb97f3bc4cb4c1ce8af3dc16502aa65dc6 | [] | [] | https://huggingface.co/datasets/rewardsignal/reddit_writing_prompts/resolve/main/README.md | # This repo consists of data downloaded from reddit.com/r/writingprompts
## prompt_responses_full.csv
* There are 193842 prompt responses in the file, and they together represent the 10 years of submissions prior to March, 13th, 2020.
I gather the following metadata for each top-level comment response to a submissi... |
robz | null | null | null | false | 1 | false | robz/test | 2022-02-17T13:54:07.000Z | null | false | 6a4e89d29202fab0ded138253c6193f1ebd98c45 | [] | [] | https://huggingface.co/datasets/robz/test/resolve/main/README.md | # Test Dataset
This is a test dataset |
rocca | null | null | null | false | 1 | false | rocca/sims4-faces | 2022-03-12T06:58:39.000Z | null | false | d4431eb9768d77852272755a3679b1fc28a45062 | [] | [] | https://huggingface.co/datasets/rocca/sims4-faces/resolve/main/README.md | A collection of >200k screenshots from the Sims 4 character creator (face and upper-torso only), using the randomize button.
* There are ~100k masculine faces (`masc` folder), ~100k feminine faces (`fem` folder), ~12k faces with a masculine physical frame and feminine attire/makeup (`masc2fem` folder).
* All images ar... |
ronaldvanos | null | null | null | false | 1 | false | ronaldvanos/testdata | 2021-11-09T12:56:07.000Z | null | false | 1bc98b7baa0108710ff2c0cca45bdf13451fb492 | [] | [] | https://huggingface.co/datasets/ronaldvanos/testdata/resolve/main/README.md | #this is a test dataset and should not be used by anyone
#i am not the owner of the data
|
rookieguy12 | null | null | null | false | 1 | false | rookieguy12/dataset | 2021-11-23T09:00:07.000Z | null | false | 40779edab2b798158e00080373e75c506e7da8c5 | [] | [] | https://huggingface.co/datasets/rookieguy12/dataset/resolve/main/README.md | |
rosettarandd | null | null | null | false | 1 | false | rosettarandd/rosetta_balcanica | 2021-11-14T17:45:31.000Z | null | false | 1ad7203a10de7e474ea9d3f8030207ee46b19c5a | [] | [] | https://huggingface.co/datasets/rosettarandd/rosetta_balcanica/resolve/main/README.md | # Dataset Summary
We present *rosetta-balcanica* a manually extracted multilingual machine translation dataset for low resource
western Balkan languages. The documents were sourced from Organization for Security and Co-operation in Europe (OSCE)
website by applying appropriate language filters. Filtered list of docum... |
roskoN | null | @inproceedings{li2017dailydialog,
title={DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset},
author={Li, Yanran and Su, Hui and Shen, Xiaoyu and Li, Wenjie and Cao, Ziqiang and Niu, Shuzi},
booktitle={Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Lon... | The DailyDialog dataset as provided in the original form with a bit of preprocessing applied to enable dast prototyping.
The splits are as in the original distribution. | false | 32 | false | roskoN/dailydialog | 2021-08-06T14:14:18.000Z | null | false | 5214b2a66405abf87fd229e5c1007985501ffe3e | [] | [] | https://huggingface.co/datasets/roskoN/dailydialog/resolve/main/README.md | # DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
The data is based on the original distribution ([link to original website](http://yanran.li/dailydialog)) ([link to paper](https://aclanthology.org/I17-1099/)).
It is created as a convenience to enablefaster prototyping.
# License
DailyDialog dataset i... |
roskoN | null | @article{lee2019multi,
title={Multi-domain task-completion dialog challenge},
author={Lee, S and Schulz, H and Atkinson, A and Gao, J and Suleman, K and El Asri, L and Adada, M and Huang, M and Sharma, S and Tay, W and others},
journal={Dialog system technology challenges},
volume={8},
pages={9},
year={2019... | The DSTC8 dataset as provided in the original form.
The only difference is that the splits are in separate zip files.
In the orignal output it is one big archive containing all splits. | false | 13 | false | roskoN/dstc8-reddit-corpus | 2021-04-23T00:19:35.000Z | null | false | b43be7fa91a2d03f72682cca175ec5271d89b880 | [] | [] | https://huggingface.co/datasets/roskoN/dstc8-reddit-corpus/resolve/main/README.md | # DSTC8 Reddit Corpus
The data is based of the following repository:
> [https://github.com/microsoft/dstc8-reddit-corpus](https://github.com/microsoft/dstc8-reddit-corpus)
The dataset is created is a convenience to enable skipping the lengthy extraction process. |
s-myk | null | null | null | false | 1 | false | s-myk/test | 2021-09-27T09:55:17.000Z | null | false | 07ad52a2252150dda5dda2ab234915574d6c46b6 | [] | [] | https://huggingface.co/datasets/s-myk/test/resolve/main/README.md | |
s50227harry | null | null | null | false | 2 | false | s50227harry/test1 | 2022-03-01T13:15:42.000Z | null | false | e52b561f896d97568d9c10ecae2816729b2a6036 | [] | [] | https://huggingface.co/datasets/s50227harry/test1/resolve/main/README.md | |
sagnikrayc | null | @inproceedings{richardson-etal-2013-mctest,
title = "{MCT}est: A Challenge Dataset for the Open-Domain Machine Comprehension of Text",
author = "Richardson, Matthew and
Burges, Christopher J.C. and
Renshaw, Erin",
booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural ... | MCTest requires machines to answer multiple-choice reading comprehension questions about fictional stories, directly tackling the high-level goal of open-domain machine comprehension. | false | 672 | false | sagnikrayc/mctest | 2022-10-25T00:16:37.000Z | mctest | false | 00355bee8104a40d80665be0e4570f4a8b2c96f7 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"language_bcp47:en-US",
"tags:explanations-in-question-answering"
] | https://huggingface.co/datasets/sagnikrayc/mctest/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets: []
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_id: mctest
language_bcp47:
- en-US
tags:
- explanatio... |
sagnikrayc | null | @article{dhingra2017quasar,
title={Quasar: Datasets for Question Answering by Search and Reading},
author={Dhingra, Bhuwan and Mazaitis, Kathryn and Cohen, William W},
journal={arXiv preprint arXiv:1707.03904},
year={2017}
} | We present two new large-scale datasets aimed at evaluating systems designed to comprehend a natural language query and extract its answer from a large corpus of text. The Quasar-S dataset consists of 37000 cloze-style (fill-in-the-gap) queries constructed from definitions of software entity tags on the popular website... | false | 18 | false | sagnikrayc/quasar | 2022-10-25T09:54:36.000Z | quasar-1 | false | ef167bca1e2bd18115fb6b6d58e5c888b30f7fde | [] | [
"arxiv:1707.03904",
"annotations_creators:expert-generated",
"language_creators:found",
"language:en-US",
"license:bsd-3-clause",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"task_categories:question-answering",
"task_ids:open-domain-qa",
"task_ids:extractive-qa"
] | https://huggingface.co/datasets/sagnikrayc/quasar/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en-US
license:
- bsd-3-clause
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
-
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
paperswithcode_id: quasar-1
---
# Dataset C... |
sagteam | null | \ | he corpus for the author profiling analysis contains texts in Russian-language which labeled for 5 tasks:
1) gender -- 13530 texts with the labels, who wrote this: text female or male;
2) age -- 13530 texts with the labels, how old the person who wrote the text. This is a number from 12 to 80. In addition, for the clas... | false | 10 | false | sagteam/author_profiling | 2022-08-09T12:33:07.000Z | null | false | 71a7c86c0432a0320f2b825c4064d00e79c4705b | [] | [
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:ru",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:multi-label-c... | https://huggingface.co/datasets/sagteam/author_profiling/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- ru
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: The Corpus for the analysis of author profiling in Russian-language texts.
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classif... |
sc2qa | null | @article{zhou2021generating,
author = {Li Zhou, Kevin Small, Yong Zhang, Sandeep Atluri},
title = "{Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learning}",
conference = {The 2021 Conference on Empirical Methods in Natural Language Processi... | \ | false | 1 | false | sc2qa/sc2q_commoncrawl | 2022-03-30T18:34:35.000Z | null | false | 38bfb57d96df0df3b254f0dcde663b6e8d7e4b5a | [] | [
"arxiv:2109.04689"
] | https://huggingface.co/datasets/sc2qa/sc2q_commoncrawl/resolve/main/README.md | For details, please refer to the following links.
Github repo: https://github.com/amazon-research/SC2QA-DRIL
Paper: [Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learning](https://arxiv.org/pdf/2109.04689.pdf) |
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