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languages:
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licenses:
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multilinguality:
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pretty_name: arm-sum
size_categories:
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task_categories:
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task_ids:
- summarization | Yeva/arm-summary | [
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pretty_name: arm-sum
size_categories:
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dc0ec99ef8ed960e323385b2a4c44b34dd8ec113 |
# Dataset Card for MASC: MASSIVE ARABIC SPEECH CORPUS
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset St... | abdusah/masc | [
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"language:ar",
"license:cc-by-nc-4.0",
"region:us"
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|
# Dataset Card for MASC: MASSIVE ARABIC SPEECH CORPUS
## Table of Contents
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- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
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89794f9658be92aa76015bd9ae1665e95423f092 |
# Dataset Card for MASC: MASSIVE ARABIC SPEECH CORPUS
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
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## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
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84a8e6a1c9e5e77c1e1893a61ad136fe9d0f8fa1 | # AutoNLP Dataset for project: prodigy-10
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
## Dataset Descritpion
This dataset... | abhishek/autonlp-data-prodigy-10 | [
"language:en",
"region:us"
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| AutoNLP Dataset for project: prodigy-10
=======================================
Table of content
----------------
* Dataset Description
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
Dataset Descritpion
-------------------
This dataset has been automatically processed by AutoNL... | [
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https://jobs.americanbar.org/profile/cbr-watch-zack-snyders-justice-league-2021-full-movie-hd-online-free/1596037/
https://jobs.americanbar.org/profile/cbr-watch-tom-jerry-2021-full-movie-hd-online-free/1596053/
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21ffe292d98a385daecaa4069a96d4bdcfa5728d |
# Dataset Card for Samanantar
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-struct... | ai4bharat/samanantar | [
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... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["en", "as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"], "license": ["cc-by-nc-4.0"], "multilinguality": ["translation"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["text-ge... | 2022-12-07T15:33:46+00:00 | [
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# Dataset Card for Samanantar
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
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0462fb87f7824d11f1d4849f24aa265289e04816 | This dataset is associated with FabNER paper. https://link.springer.com/article/10.1007/s10845-021-01807-x
Kindly cite if you use it. | akumar33/manufacturing | [
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| This dataset is associated with FabNER paper. URL
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b5ecd28e4639b2a38fcb5cf3229d76224887635c |
# Dataset Card for Carbon-24
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structu... | albertvillanova/carbon_24 | [
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"arxiv:... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["machine-generated"], "language": ["cif"], "license": ["mit"], "multilinguality": ["other-crystallography"], "size_categories": ["unknown"], "source_datasets": [], "task_categories": ["other"], "task_ids": [], "pretty_name": "Carbon-24", "tags": ["ma... | 2022-10-24T14:25:03+00:00 | [
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# Dataset Card for Carbon-24
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
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- Dataset Structure
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- Dataset Creation
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476cc83b6db0c85c8a0cabaa4fbdb17fd062fc47 | # Dataset Card for pmc_open_access
## Dataset Description
### Dataset Summary
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| # Dataset Card for pmc_open_access
## Dataset Description
### Dataset Summary
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f72e0cbcd52596bac666dead2f266f3e3bafe407 |
# Dataset Card for SAT
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
... | albertvillanova/sat | [
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====================
Table of Contents
-----------------
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+ Supported Tasks and Leaderboards
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fc55183e7e4403d36027c13914f4403e151528d1 |
# Dataset Description
## Chuvash-Russian parallel corpus
1M parallel sentences. Manually aligned
## Chuvash-English parallel corpus.
200K parallel sentences. Automatically aligned
## Contributions
For additional details contact [@AlAntonov](https://github.com/AlAntonov). | alexantonov/chuvash_parallel | [
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# Dataset Description
## Chuvash-Russian parallel corpus
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## Chuvash-English parallel corpus.
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## Contributions
For additional details contact @AlAntonov. | [
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"## Chuvash-Russian parallel corpus\n\n1M parallel sentences. Manually aligned",
"## Chuvash-English parallel corpus.\n\n200K parallel sentences. Automatically aligned",
"## Contributions... | [
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f935af6895c7590932f5ac4f4764e4319b0c18ed | This is a dataset containing just stories of the CoQA dataset with their respective ids. This can be used in the pretraining phase for the MLM tasks. | alistvt/coqa-stories | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-20T22:17:46+00:00 | [] | [] | TAGS
#region-us
| This is a dataset containing just stories of the CoQA dataset with their respective ids. This can be used in the pretraining phase for the MLM tasks. | [] | [
"TAGS\n#region-us \n"
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6
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3baec930b2f10cc837af55dcbbeab240c6643ad2 |
# klej-cdsc-e
## Description
Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness (**CDSC-R**) and entailment (**CDSC-E**). The dataset may be used to evaluate compositional distributional semantics models of Polish. The dataset was presented at ACL 2017.
Althou... | allegro/klej-cdsc-e | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:expert-generated",
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"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:cc-by-nc-sa-4.0",
"region:us... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["pl"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["natural-language... | 2022-08-30T05:58:29+00:00 | [] | [
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| klej-cdsc-e
===========
Description
-----------
Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness (CDSC-R) and entailment (CDSC-E). The dataset may be used to evaluate compositional distributional semantics models of Polish. The dataset was presented at ACL 20... | [
"### Loading",
"### Evaluation"
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dd7c3c3bb336738c853ea17c64b85d876e6714a9 |
# klej-dyk
## Description
The Czy wiesz? (eng. Did you know?) the dataset consists of almost 5k question-answer pairs obtained from Czy wiesz... section of Polish Wikipedia. Each question is written by a Wikipedia collaborator and is answered with a link to a relevant Wikipedia article. In huggingface version of thi... | allegro/klej-dyk | [
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"language:pl",
"license:cc-by-sa-3.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["other"], "language": ["pl"], "license": ["cc-by-sa-3.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["open-domain-qa"], "pretty_name": ... | 2022-10-26T08:01:41+00:00 | [] | [
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| klej-dyk
========
Description
-----------
The Czy wiesz? (eng. Did you know?) the dataset consists of almost 5k question-answer pairs obtained from Czy wiesz... section of Polish Wikipedia. Each question is written by a Wikipedia collaborator and is answered with a link to a relevant Wikipedia article. In huggingfa... | [
"### Loading",
"### Evaluation"
] | [
"TAGS\n#task_categories-question-answering #task_ids-open-domain-qa #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Polish #license-cc-by-sa-3.0 #region-us \n",
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] |
9843af31facd613eb091deaa4141df4331d4f918 |
# klej-polemo2-in
## Description
The PolEmo2.0 is a dataset of online consumer reviews from four domains: medicine, hotels, products, and university. It is human-annotated on a level of full reviews and individual sentences. It comprises over 8000 reviews, about 85% from the medicine and hotel domains.
We use the P... | allegro/klej-polemo2-in | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:cc-by-sa-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["other"], "language": ["pl"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pre... | 2022-08-30T05:57:28+00:00 | [] | [
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| klej-polemo2-in
===============
Description
-----------
The PolEmo2.0 is a dataset of online consumer reviews from four domains: medicine, hotels, products, and university. It is human-annotated on a level of full reviews and individual sentences. It comprises over 8000 reviews, about 85% from the medicine and hote... | [
"### Loading",
"### Evaluation"
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"TAGS\n#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Polish #license-cc-by-sa-4.0 #region-us \n",
"### Loading",
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] |
b1a18b27a37cfb366969e1aa5721f8bf6ec5e179 |
# klej-polemo2-out
## Description
The PolEmo2.0 is a dataset of online consumer reviews from four domains: medicine, hotels, products, and university. It is human-annotated on a level of full reviews and individual sentences. It comprises over 8000 reviews, about 85% from the medicine and hotel domains.
We use the ... | allegro/klej-polemo2-out | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:cc-by-sa-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["other"], "language": ["pl"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pre... | 2022-08-30T05:57:07+00:00 | [] | [
"pl"
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#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Polish #license-cc-by-sa-4.0 #region-us
| klej-polemo2-out
================
Description
-----------
The PolEmo2.0 is a dataset of online consumer reviews from four domains: medicine, hotels, products, and university. It is human-annotated on a level of full reviews and individual sentences. It comprises over 8000 reviews, about 85% from the medicine and ho... | [
"### Loading",
"### Evaluation"
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] |
9585582aef37e7747ef174b0ec3b74855da8bad2 |
# klej-psc
## Description
The Polish Summaries Corpus (PSC) is a dataset of summaries for 569 news articles. The human annotators created five extractive summaries for each article by choosing approximately 5% of the original text. A different annotator created each summary. The subset of 154 articles was also suppl... | allegro/klej-psc | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:5K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:cc-by-sa-3.0",
"paraphrase-classification",
"region:us"
... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["other"], "language": ["pl"], "license": ["cc-by-sa-3.0"], "multilinguality": ["monolingual"], "size_categories": ["5K", "1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": [], "pretty_name": "Polish S... | 2022-10-26T08:01:54+00:00 | [] | [
"pl"
] | TAGS
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| klej-psc
========
Description
-----------
The Polish Summaries Corpus (PSC) is a dataset of summaries for 569 news articles. The human annotators created five extractive summaries for each article by choosing approximately 5% of the original text. A different annotator created each summary. The subset of 154 articl... | [
"### Loading",
"### Evaluation"
] | [
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"### Loading",
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1588ec454efa1a09f29cd18ddd04fe05fc8653a2 |
# C4
## Dataset Description
- **Paper:** https://arxiv.org/abs/1910.10683
### Dataset Summary
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](https://www.tensorflow.org/datasets/catalog... | allenai/c4 | [
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"size_categories:1... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["af", "am", "ar", "az", "be", "bg", "bn", "ca", "ceb", "co", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fil", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "haw", "he", "hi", "hmn", "ht", "hu", "hy", "id",... | 2024-01-09T19:14:03+00:00 | [
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... | TAGS
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==
Dataset Description
-------------------
* Paper: URL
### Dataset Summary
A colossal, cleaned version of Common Crawl's web crawl corpus. Based on Common Crawl dataset: "URL".
This is the processed version of Google's C4 dataset
We prepared five variants of the data: 'en', 'en.noclean', 'en.noblocklist... | [
"### Dataset Summary\n\n\nA colossal, cleaned version of Common Crawl's web crawl corpus. Based on Common Crawl dataset: \"URL\".\n\n\nThis is the processed version of Google's C4 dataset\n\n\nWe prepared five variants of the data: 'en', 'en.noclean', 'en.noblocklist', 'realnewslike', and 'multilingual' (mC4).\n\n\... | [
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1bf636269d478d390cbdab0a604a0d232ff86434 |
# Dataset Card for SciCo
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- ... | allenai/scico | [
"task_categories:token-classification",
"task_ids:coreference-resolution",
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"multilinguality:monolingual",
"language:en",
"license:apache-2.0",
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"structure-prediction",
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] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["domain experts"], "language": ["en"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "task_categories": ["token-classification"], "task_ids": ["coreference-resolution"], "paperswithcode_id": "scico", "tags": ["cross-document-coreference-resolution", "structure-prediction"]} | 2023-01-10T20:23:18+00:00 | [] | [
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| Dataset Card for SciCo
======================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Data
+ Annotations
+ Pe... | [
"### Dataset Summary\n\n\nSciCo consists of clusters of mentions in context and a hierarchy over them.\nThe corpus is drawn from computer science papers, and the concept mentions are methods and tasks from across CS.\nScientific concepts pose significant challenges: they often take diverse forms (e.g., class-condit... | [
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b898f74f38fcc62ba4918063ce990cf3113b487f | # Dataset Card for [Haber Tweetlerinin Duygu Analizi Ve Siniflandirma]
Github repo
[repo](https://github.com/alperbayram/Duygu_Analizi_ve_Metin_Siniflandirma)
## Dataset Description
Twitter verileri üzerinde Türkçe Bert modelleri kullanarak yapılan duygu analizi ve metin sınıflandırma işlemleri ve görselleştirilmesi. ... | alperbayram/HaberTweetlerininDuyguAnaliziVeSiniflandirma | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-27T11:56:20+00:00 | [] | [] | TAGS
#region-us
| Dataset Card for [Haber Tweetlerinin Duygu Analizi Ve Siniflandirma]
====================================================================
Github repo
repo
Dataset Description
-------------------
Twitter verileri üzerinde Türkçe Bert modelleri kullanarak yapılan duygu analizi ve metin sınıflandırma işlemleri ve gö... | [
"### Dataset Curators\n\n\nalper bayram",
"### Languages\n\n\n[TR]"
] | [
"TAGS\n#region-us \n",
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6,
9,
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"passage: TAGS\n#region-us \n### Dataset Curators\n\n\nalper bayram### Languages\n\n\n[TR]"
] |
53e91b2f22da49eb9579fb96cb8842922a4cd83c | # References
- [alper bayram](https://github.com/alperbayram)
| alperbayram/Tweet_Siniflandirma | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"size_categories:unknown",
"language:tr",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["crowdsourced", "expert-generated"], "language_creators": ["crowdsourced"], "language": ["tr"], "size_categories": ["unknown"], "source_datasets": [], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pretty_name": "Turkish Sentiment Dataset"} | 2022-10-25T09:02:12+00:00 | [] | [
"tr"
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#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-crowdsourced #annotations_creators-expert-generated #language_creators-crowdsourced #size_categories-unknown #language-Turkish #region-us
| # References
- alper bayram
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] |
bae10b86115c9807026d3fb2ad6d78e894f79d02 |
language:
- tr
# negatif 54%
# pozitif 46%
| alperbayram/TwitterDuygu | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-11-19T21:00:07+00:00 | [] | [] | TAGS
#region-us
|
language:
- tr
# negatif 54%
# pozitif 46%
| [
"# negatif 54%",
"# pozitif 46%"
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"# pozitif 46%"
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3bfb8811b6b14e4cb8f12939b01a0a85e188871b | # AutoNLP Dataset for project: user-review-classification
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
## Dataset Descritpi... | alperiox/autonlp-data-user-review-classification | [
"task_categories:text-classification",
"language:en",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "task_categories": ["text-classification"]} | 2022-10-25T08:07:13+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #language-English #region-us
| AutoNLP Dataset for project: user-review-classification
=======================================================
Table of content
----------------
* Dataset Description
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
Dataset Descritpion
-------------------
This dataset has been a... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------",
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"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
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003479f50b25b728910462fba3e8de35c4934c63 | # AutoNLP Dataset for project: alberti-stanza-names
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
## Dataset Descritpion
Th... | alvp/autonlp-data-alberti-stanza-names | [
"task_categories:text-classification",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"task_categories": ["text-classification"]} | 2021-11-19T13:26:10+00:00 | [] | [] | TAGS
#task_categories-text-classification #region-us
| AutoNLP Dataset for project: alberti-stanza-names
=================================================
Table of content
----------------
* Dataset Description
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
Dataset Descritpion
-------------------
This dataset has been automatically... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------",
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"### Dataset Splits\n\n\nThis d... | [
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da5c716709eee5177ea77101e9a6c6f35accac76 | # AutoNLP Dataset for project: alberti-stanzas-finetuning
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
## Dataset Descritpi... | alvp/autonlp-data-alberti-stanzas-finetuning | [
"task_categories:text-classification",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"task_categories": ["text-classification"]} | 2021-11-19T12:46:22+00:00 | [] | [] | TAGS
#task_categories-text-classification #region-us
| AutoNLP Dataset for project: alberti-stanzas-finetuning
=======================================================
Table of content
----------------
* Dataset Description
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
Dataset Descritpion
-------------------
This dataset has been a... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------",
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"### Dataset Splits\n\n\nThis d... | [
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448b3e949474ee824c977cbc7667f9ed7ef02cb8 |
# Dataset Card for Smart Contracts
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-s... | andstor/smart_contracts | [
"task_categories:text-generation",
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"arxiv:2309.09826",
"doi:10.57967/hf/1182",
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|
# Dataset Card for Smart Contracts
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- flattened
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67974a09f5d96f559845954d31eb186854ef4a53 | # Medical Histories Ru-ru
Medical Histories from Russian medical textbooks.
A text dataset with medical histories.
All dates were masked into <DATE>. | anechaev/ru_med_history | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-12T08:51:53+00:00 | [] | [] | TAGS
#region-us
| # Medical Histories Ru-ru
Medical Histories from Russian medical textbooks.
A text dataset with medical histories.
All dates were masked into <DATE>. | [
"# Medical Histories Ru-ru\n\nMedical Histories from Russian medical textbooks.\nA text dataset with medical histories. \nAll dates were masked into <DATE>."
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"passage: TAGS\n#region-us \n# Medical Histories Ru-ru\n\nMedical Histories from Russian medical textbooks.\nA text dataset with medical histories. \nAll dates were masked into <DATE>."
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8eee77773d24963cf379374d79f5b4cad53f045e | [Deep learning the collisional cross sections of the peptide universe from a million experimental values](https://www.nature.com/articles/s41467-021-21352-8)
[Data](http://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD017703) generated from [MaxQuant](http://coxdocs.org/doku.php?id=maxquant:start) output
``... | animesh/autonlp-data-peptides | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-10-12T08:08:03+00:00 | [] | [] | TAGS
#region-us
| Deep learning the collisional cross sections of the peptide universe from a million experimental values
Data generated from MaxQuant output
Code
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7c5506f3a1c8dd91d6218e50df1478b19c298bad |
# Dataset Card for BSARD
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
... | maastrichtlawtech/bsard | [
"task_categories:text-retrieval",
"task_categories:text-classification",
"task_ids:document-retrieval",
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"size_categories:1K<n<10K",
"source_datasets:original",
"langu... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["fr"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-retrieval", "text-classification"], "task_ids": ["document-re... | 2024-02-16T11:23:21+00:00 | [
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======================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Data
... | [
"### Dataset Summary\n\n\nThe Belgian Statutory Article Retrieval Dataset (BSARD) is a French native dataset for studying legal information retrieval. BSARD consists of more than 22,600 statutory articles from Belgian law and about 1,100 legal questions posed by Belgian citizens and labeled by experienced jurists w... | [
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4bb9fd7e7def03162cf2be1c5641bb0f21c6114d |
# Dataset Card for common_language
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-insta... | anton-l/common_language | [
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"language:ar",
"language:br",
"language:ca",
"language:cnh",
"language:cs",
"language:cv",
"language:cy",
"language:de"... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["ar", "br", "ca", "cnh", "cs", "cv", "cy", "de", "dv", "el", "en", "eo", "es", "et", "eu", "fa", "fr", "fy", "ia", "id", "it", "ja", "ka", "kab", "ky", "lv", "mn", "mt", "nl", "pl", "pt", "rm", "ro", "ru", "rw", "sah", "sl", ... | 2022-10-21T15:20:41+00:00 | [] | [
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=================================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Dat... | [
"### Dataset Summary\n\n\nThis dataset is composed of speech recordings from languages that were carefully selected from the CommonVoice database. The total duration of audio recordings is 45.1 hours (i.e., 1 hour of material for each language). The dataset has been extracted from CommonVoice to train language-id s... | [
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a4918158e431f54fe008405bcf20aac4d48f1334 |
# Dataset Card for SUPERB
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)... | anton-l/superb | [
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"task_ids:speaker-identification",
"task_ids:intent-classification",
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"annotations_creators:other",
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"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"source_datasets:extended|libris... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["other"], "language_creators": ["other"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original", "extended|librispeech_asr", "extended|other-librimix", "extended|other-speech_commands"], "task_categories":... | 2022-07-04T09:48:08+00:00 | [
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=======================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Dat... | [
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9748209f61d82b9359a960915ffe76946b02877a | # Disclaimer
This is a tiny subset of the SUPERB dataset, which is intended only for demo purposes!
See the full dataset here: https://huggingface.co/datasets/superb
| anton-l/superb_demo | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-04-14T12:54:54+00:00 | [] | [] | TAGS
#region-us
| # Disclaimer
This is a tiny subset of the SUPERB dataset, which is intended only for demo purposes!
See the full dataset here: URL
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f663f00289d96702470a9118e2e3a2fa3adaf2fb |
# Estonian Question Answering dataset
* Dataset for extractive question answering in Estonian. It is based on Wikipedia articles, pre-filtered via PageRank. Annotation was done by one person.
* Train set includes 776 context-question-answer triplets. There are several possible answers per question, each in a separate... | anukaver/EstQA | [
"language:et",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": "et"} | 2021-04-29T14:34:29+00:00 | [] | [
"et"
] | TAGS
#language-Estonian #region-us
|
# Estonian Question Answering dataset
* Dataset for extractive question answering in Estonian. It is based on Wikipedia articles, pre-filtered via PageRank. Annotation was done by one person.
* Train set includes 776 context-question-answer triplets. There are several possible answers per question, each in a separate... | [
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6eebb4e70e0fcc9eaa4fe84318e3ade850105f2c | kbd: web sites dump deduplicated latin script – 835K sentences
ru: wiki dump deduplicated – 835K sentences | anzorq/kbd-ru-1.67M-temp | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-14T12:00:11+00:00 | [] | [] | TAGS
#region-us
| kbd: web sites dump deduplicated latin script – 835K sentences
ru: wiki dump deduplicated – 835K sentences | [] | [
"TAGS\n#region-us \n"
] | [
6
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2df1df40b21de9dba19a05cf5b1e349743253868 | test | anzorq/kbd-ru-temp | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-06T23:24:50+00:00 | [] | [] | TAGS
#region-us
| test | [] | [
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c633b5c257a7adc28f782b1d5c5b60f9f391a31f | Online Privacy Policy QnA Dataset
| arjunth2001/online_privacy_qna | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-11-10T08:53:10+00:00 | [] | [] | TAGS
#region-us
| Online Privacy Policy QnA Dataset
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
59c7622ea1cf5ab07568ba8e161379129c79f7c1 |
# Dataset Card for "lmqg/qg_jaquad"
## Dataset Description
- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
- **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
- **Point of Contact:** [Asahi Ushio](http://asahiush... | lmqg/qg_jaquad | [
"task_categories:text-generation",
"task_ids:language-modeling",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:SkelterLabsInc/JaQuAD",
"language:ja",
"license:cc-by-sa-3.0",
"question-generation",
"arxiv:2210.03992",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": "ja", "license": "cc-by-sa-3.0", "multilinguality": "monolingual", "size_categories": "10K<n<100K", "source_datasets": "SkelterLabsInc/JaQuAD", "task_categories": ["text-generation"], "task_ids": ["language-modeling"], "pretty_name": "JaQuAD for question generation", "tags": ["question-generation"]} | 2022-12-02T18:51:27+00:00 | [
"2210.03992"
] | [
"ja"
] | TAGS
#task_categories-text-generation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-SkelterLabsInc/JaQuAD #language-Japanese #license-cc-by-sa-3.0 #question-generation #arxiv-2210.03992 #region-us
| Dataset Card for "lmqg/qg\_jaquad"
==================================
Dataset Description
-------------------
* Repository: URL
* Paper: URL
* Point of Contact: Asahi Ushio
### Dataset Summary
This is a subset of QG-Bench, a unified question generation benchmark proposed in
"Generative Language Models for Parag... | [
"### Dataset Summary\n\n\nThis is a subset of QG-Bench, a unified question generation benchmark proposed in\n\"Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference\".\nThis is JaQuAD dataset compiled for question generation (QG) task. The... | [
"TAGS\n#task_categories-text-generation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-SkelterLabsInc/JaQuAD #language-Japanese #license-cc-by-sa-3.0 #question-generation #arxiv-2210.03992 #region-us \n",
"### Dataset Summary\n\n\nThis is a subset of QG-Bench... | [
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"passage: TAGS\n#task_categories-text-generation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-SkelterLabsInc/JaQuAD #language-Japanese #license-cc-by-sa-3.0 #question-generation #arxiv-2210.03992 #region-us \n### Dataset Summary\n\n\nThis is a subset of QG-Be... |
57bdaee4b743773b6eb5c4e38490757d18a92ca0 |
# Dataset Card for "lmqg/qg_squad"
## Dataset Description
- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
- **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
- **Point of Contact:** [Asahi Ushio](http://asahiushio... | lmqg/qg_squad | [
"task_categories:text-generation",
"task_ids:language-modeling",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:squad",
"language:en",
"license:cc-by-4.0",
"question-generation",
"arxiv:2210.03992",
"arxiv:1705.00106",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": "en", "license": "cc-by-4.0", "multilinguality": "monolingual", "size_categories": "10K<n<100K", "source_datasets": "squad", "task_categories": ["text-generation"], "task_ids": ["language-modeling"], "pretty_name": "SQuAD for question generation", "tags": ["question-generation"]} | 2022-12-02T18:51:10+00:00 | [
"2210.03992",
"1705.00106"
] | [
"en"
] | TAGS
#task_categories-text-generation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-squad #language-English #license-cc-by-4.0 #question-generation #arxiv-2210.03992 #arxiv-1705.00106 #region-us
| Dataset Card for "lmqg/qg\_squad"
=================================
Dataset Description
-------------------
* Repository: URL
* Paper: URL
* Point of Contact: Asahi Ushio
### Dataset Summary
This is a subset of QG-Bench, a unified question generation benchmark proposed in
"Generative Language Models for Paragra... | [
"### Dataset Summary\n\n\nThis is a subset of QG-Bench, a unified question generation benchmark proposed in\n\"Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference\".\nThis is SQuAD dataset for question generation (QG) task. The split\nof... | [
"TAGS\n#task_categories-text-generation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-squad #language-English #license-cc-by-4.0 #question-generation #arxiv-2210.03992 #arxiv-1705.00106 #region-us \n",
"### Dataset Summary\n\n\nThis is a subset of QG-Bench, ... | [
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0f614d85fea423bf8579b3f7a622f51df835f414 |
# MERLIN corpus
Project URL: https://merlin-platform.eu/C_mcorpus.php
Dataset URL: https://clarin.eurac.edu/repository/xmlui/handle/20.500.12124/6
The MERLIN corpus is a written learner corpus for Czech, German, and Italian that has been designed to illustrate the Common European Framework of Reference for Language... | aseifert/merlin | [
"multilinguality:translation",
"size_categories:unknown",
"language:cz",
"language:de",
"language:it",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": [], "language_creators": [], "language": ["cz", "de", "it"], "license": [], "multilinguality": ["translation"], "size_categories": ["unknown"], "source_datasets": [], "task_categories": ["conditional-text-generation"], "task_ids": ["machine-translation"], "pretty_name": "merlin"} | 2022-10-21T15:21:58+00:00 | [] | [
"cz",
"de",
"it"
] | TAGS
#multilinguality-translation #size_categories-unknown #language-cz #language-German #language-Italian #region-us
|
# MERLIN corpus
Project URL: URL
Dataset URL: URL
The MERLIN corpus is a written learner corpus for Czech, German, and Italian that has been designed to illustrate the Common European Framework of Reference for Languages (CEFR) with authentic learner data. The corpus contains learner texts produced in standardized ... | [
"# MERLIN corpus\n\nProject URL: URL\n\nDataset URL: URL\n\nThe MERLIN corpus is a written learner corpus for Czech, German, and Italian that has been designed to illustrate the Common European Framework of Reference for Languages (CEFR) with authentic learner data. The corpus contains learner texts produced in sta... | [
"TAGS\n#multilinguality-translation #size_categories-unknown #language-cz #language-German #language-Italian #region-us \n",
"# MERLIN corpus\n\nProject URL: URL\n\nDataset URL: URL\n\nThe MERLIN corpus is a written learner corpus for Czech, German, and Italian that has been designed to illustrate the Common Euro... | [
35,
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"passage: TAGS\n#multilinguality-translation #size_categories-unknown #language-cz #language-German #language-Italian #region-us \n# MERLIN corpus\n\nProject URL: URL\n\nDataset URL: URL\n\nThe MERLIN corpus is a written learner corpus for Czech, German, and Italian that has been designed to illustrate the Common E... |
23b4b8e85eba06d7737a5cc8180f91dedff0c7c8 |
# PIE synthetic dataset
Repo: https://github.com/awasthiabhijeet/PIE
Paper: https://aclanthology.org/D19-1435.pdf | aseifert/pie-synthetic | [
"multilinguality:translation",
"size_categories:unknown",
"language:en",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": [], "language_creators": [], "language": ["en"], "license": [], "multilinguality": ["translation"], "size_categories": ["unknown"], "source_datasets": [], "task_categories": ["conditional-text-generation"], "task_ids": ["machine-translation"], "pretty_name": "pie-synthetic"} | 2022-07-07T10:55:53+00:00 | [] | [
"en"
] | TAGS
#multilinguality-translation #size_categories-unknown #language-English #region-us
|
# PIE synthetic dataset
Repo: URL
Paper: URL | [
"# PIE synthetic dataset\n\nRepo: URL\n\nPaper: URL"
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813f30b157f1b66b44b224fa33c116cb493d27cc |
# Dataset Card Creation Guide
## Table of Contents
- [Dataset Card Creation Guide](#dataset-card-creation-guide)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboa... | asi/wikitext_fr | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:fr",
"license:cc-by-sa-4.0",
"arxiv:1609.07843",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["fr"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["sequence-modeling"], "task_ids": ["language-modeling"], "pretty_name": "W... | 2022-10-21T15:23:07+00:00 | [
"1609.07843"
] | [
"fr"
] | TAGS
#task_ids-language-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #language-French #license-cc-by-sa-4.0 #arxiv-1609.07843 #region-us
| Dataset Card Creation Guide
===========================
Table of Contents
-----------------
* Dataset Card Creation Guide
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
+ Dataset Structure
- Data Instances
- Data Fields
- Data Splits
+ Data... | [
"### Dataset Summary\n\n\nWikitext-fr language modeling dataset consists of over 70 million tokens extracted from the set of french Wikipedia articles that are classified as \"quality articles\" or \"good articles\". It is designed to mirror the english benchmark from Stephen Merity, Caiming Xiong, James Bradbury, ... | [
"TAGS\n#task_ids-language-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #language-French #license-cc-by-sa-4.0 #arxiv-1609.07843 #region-us \n",
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3d2607f6782402be6ba0df77356d852410a71f04 | # AutoNLP Dataset for project: antisemitism-2
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
## Dataset Descritpion
This dat... | astarostap/autonlp-data-antisemitism-2 | [
"task_categories:text-classification",
"language:en",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "task_categories": ["text-classification"]} | 2022-10-25T08:07:21+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #language-English #region-us
| AutoNLP Dataset for project: antisemitism-2
===========================================
Table of content
----------------
* Dataset Description
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
Dataset Descritpion
-------------------
This dataset has been automatically processed b... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis da... | [
"TAGS\n#task_categories-text-classification #language-English #region-us \n",
"### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the f... | [
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"passage: TAGS\n#task_categories-text-classification #language-English #region-us \n### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------### Data Instances\n\n\nA sample from this dataset looks as follows:### Dataset Fields\n\n\nThe dataset has the following ... |
9af8812fde540df25170724cc989bbd008f79478 | # Dataset Card for Rheumatology Abstracts
## Data Source
This dataset comes from PubMed, derived from my fork of the pymed package (no longer maintained). My fork can be found at https://github.com/cmcmaster1/pymed
## Data Structure
The dataset is split into train (80%) and test (20%) files (CSV). Each file contains t... | austin/rheum_abstracts | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-04T05:10:23+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for Rheumatology Abstracts
## Data Source
This dataset comes from PubMed, derived from my fork of the pymed package (no longer maintained). My fork can be found at URL
## Data Structure
The dataset is split into train (80%) and test (20%) files (CSV). Each file contains three columns:
- id
- abstract (m... | [
"# Dataset Card for Rheumatology Abstracts",
"## Data Source\nThis dataset comes from PubMed, derived from my fork of the pymed package (no longer maintained). My fork can be found at URL",
"## Data Structure\nThe dataset is split into train (80%) and test (20%) files (CSV). Each file contains three columns:\n-... | [
"TAGS\n#region-us \n",
"# Dataset Card for Rheumatology Abstracts",
"## Data Source\nThis dataset comes from PubMed, derived from my fork of the pymed package (no longer maintained). My fork can be found at URL",
"## Data Structure\nThe dataset is split into train (80%) and test (20%) files (CSV). Each file c... | [
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"passage: TAGS\n#region-us \n# Dataset Card for Rheumatology Abstracts## Data Source\nThis dataset comes from PubMed, derived from my fork of the pymed package (no longer maintained). My fork can be found at URL## Data Structure\nThe dataset is split into train (80%) and test (20%) files (CSV). Each file contains t... |
fc6deba7bfad6cae99a6a5ed82344f9481209b91 | <S>AAAAAAAAAAAAAAAA</s> <h1/onmouseover=alert(1)>aaaaaaaaaaaaa
| avanishcobaltest/datasetavanish | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-10T17:43:26+00:00 | [] | [] | TAGS
#region-us
| <S>AAAAAAAAAAAAAAAA</s> <h1/onmouseover=alert(1)>aaaaaaaaaaaaa
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
fabb9115e9f173c9aaa4897e5b2f3a49e74758a0 | ## Load mono corpora from OPUS
OPUS provides many parallel corpora, but it has more data for a single language. This enables you to load any raw mono corpus from [opus.nlpl.eu](https://opus.nlpl.eu/). Please check [opus.nlpl.eu](https://opus.nlpl.eu/) for the available corpora and licenses. The targeted corpus is call... | badranx/opus_raw | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-28T14:19:19+00:00 | [] | [] | TAGS
#region-us
| ## Load mono corpora from OPUS
OPUS provides many parallel corpora, but it has more data for a single language. This enables you to load any raw mono corpus from URL. Please check URL for the available corpora and licenses. The targeted corpus is called raw corpus on OPUS.
To use it, you need the name of the corpus, ... | [
"## Load mono corpora from OPUS\n\nOPUS provides many parallel corpora, but it has more data for a single language. This enables you to load any raw mono corpus from URL. Please check URL for the available corpora and licenses. The targeted corpus is called raw corpus on OPUS.\n\nTo use it, you need the name of the... | [
"TAGS\n#region-us \n",
"## Load mono corpora from OPUS\n\nOPUS provides many parallel corpora, but it has more data for a single language. This enables you to load any raw mono corpus from URL. Please check URL for the available corpora and licenses. The targeted corpus is called raw corpus on OPUS.\n\nTo use it,... | [
6,
161,
4,
27
] | [
"passage: TAGS\n#region-us \n## Load mono corpora from OPUS\n\nOPUS provides many parallel corpora, but it has more data for a single language. This enables you to load any raw mono corpus from URL. Please check URL for the available corpora and licenses. The targeted corpus is called raw corpus on OPUS.\n\nTo use ... |
be2fcc045e5f4a9a645527ffbf5ea627218f7c5e | # A More Natural PersonaChat
## Dataset Summary
This dataset is a true-cased version of the PersonaChat dataset by Zhang et al. (2018).
The original PersonaChat dataset is all lower case, and has extra space around each
clause/sentence separating punctuation mark. This version of the dataset has more of a
natural lan... | bavard/personachat_truecased | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-04-23T12:28:30+00:00 | [] | [] | TAGS
#region-us
| A More Natural PersonaChat
==========================
Dataset Summary
---------------
This dataset is a true-cased version of the PersonaChat dataset by Zhang et al. (2018).
The original PersonaChat dataset is all lower case, and has extra space around each
clause/sentence separating punctuation mark. This version ... | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
96db30fff0964b6fa1ae9e3c713a1e2f42081360 |
# Bazinga! A Dataset for Multi-Party Dialogues Structuring
[Read paper](http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.367.pdf) | [Watch video description](https://www.youtube.com/watch?v=R5m2OF7ksO4)
This dataset provides audio soundtracks and time-coded manual transcripts of episodes of the followin... | bazinga/bazinga | [
"language:en",
"speaker-diarization",
"speaker-identification",
"automatic-speech-recognition",
"named-entity-detection",
"addressee-detection",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "tags": ["speaker-diarization", "speaker-identification", "automatic-speech-recognition", "named-entity-detection", "addressee-detection"]} | 2022-06-20T07:33:34+00:00 | [] | [
"en"
] | TAGS
#language-English #speaker-diarization #speaker-identification #automatic-speech-recognition #named-entity-detection #addressee-detection #region-us
|
# Bazinga! A Dataset for Multi-Party Dialogues Structuring
Read paper | Watch video description
This dataset provides audio soundtracks and time-coded manual transcripts of episodes of the following TV and movies series:
24, Battlestar Galactica, Breaking Bad, Buffy The Vampire Slayer, ER, Friends, Game Of Thrones,... | [
"# Bazinga! A Dataset for Multi-Party Dialogues Structuring\n\nRead paper | Watch video description\n\nThis dataset provides audio soundtracks and time-coded manual transcripts of episodes of the following TV and movies series:\n\n24, Battlestar Galactica, Breaking Bad, Buffy The Vampire Slayer, ER, Friends, Game O... | [
"TAGS\n#language-English #speaker-diarization #speaker-identification #automatic-speech-recognition #named-entity-detection #addressee-detection #region-us \n",
"# Bazinga! A Dataset for Multi-Party Dialogues Structuring\n\nRead paper | Watch video description\n\nThis dataset provides audio soundtracks and time-c... | [
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"passage: TAGS\n#language-English #speaker-diarization #speaker-identification #automatic-speech-recognition #named-entity-detection #addressee-detection #region-us \n"
] |
b03a838013ad69fa852d95323fe8f612bccccef2 |
# Dataset Card for mC4-es-sampled
## Table of Contents
- [Dataset Card for mC4-es-sampled](#dataset-card-for-mc4-es-sampled)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-... | bertin-project/mc4-es-sampled | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"size_categories:n<1K",
"size_categories:1K<n<10K",
"size_categories:10K<n<100K",
"size_categories:100K<n<1M",
"size_categories:1M<n<10M",
... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["es"], "license": ["odc-by"], "size_categories": ["n<1K", "1K<n<10K", "10K<n<100K", "100K<n<1M", "1M<n<10M", "10M<n<100M", "100M<n<1B"], "source_datasets": ["mc4", "bertin-project/mc4-sampling"], "task_categories": ["text-generatio... | 2023-03-16T08:56:10+00:00 | [
"1910.10683",
"2207.06814"
] | [
"es"
] | TAGS
#task_categories-text-generation #task_categories-fill-mask #task_ids-language-modeling #annotations_creators-no-annotation #language_creators-found #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 #size_cat... | Dataset Card for mC4-es-sampled
===============================
Table of Contents
-----------------
* Dataset Card for mC4-es-sampled
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
+ Dataset Structure
- Data Instances
- Data Fields
- Data Sp... | [
"### Dataset Summary\n\n\nThis dataset is the result of applying perplexity sampling to the Spanish portion of mC4 using 'mc4-sampling'. Please, refer to BERTIN Project.\n\n\nYou can load the mC4 Spanish sampled like this:\n\n\nAlternatively, you can bypass the 'datasets' library and quickly download (~1.5hrs, depe... | [
"TAGS\n#task_categories-text-generation #task_categories-fill-mask #task_ids-language-modeling #annotations_creators-no-annotation #language_creators-found #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 #si... | [
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99745f2a45f9a2672546eaa8abb8481a0dbfbd9f |
# Dataset Card for mC4-sampling
## Table of Contents
- [Dataset Card for mC4-sampling](#dataset-card-for-mc4-sampling)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Sampling](#dataset-sampling)
- [Supported Tas... | bertin-project/mc4-sampling | [
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# Dataset Card for mC4-sampling
## Table of Contents
- Dataset Card for mC4-sampling
- Table of Contents
- Dataset Description
- Dataset Summary
- Dataset Sampling
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Add... | [
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9f8542604b9332fc59b6abce30c84fca67dec62a | Work In progress! | bhadresh-savani/web_split | [
"region:us"
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#region-us
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fc4fb9e46f37bfe9ba27571358897924e8258bdc |
# Dataset Card for [SentiHood]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-struc... | bhavnicksm/sentihood | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"task_ids:multi-class-classification",
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"multilinguality:monolingual",
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"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"arxiv:1610.03771",
... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": [], "language_creators": [], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification", "multi-class-classification", "na... | 2022-10-25T08:07:23+00:00 | [
"1610.03771"
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|
# Dataset Card for [SentiHood]
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Pers... | [
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83897de5e66d71057570e94a8665af42d6adfe12 |
# Dataset Card for the Buckeye Corpus (buckeye_asr)
## 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-insta... | bhigy/buckeye_asr | [
"task_categories:automatic-speech-recognition",
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"language_creators:crowdsourced",
"multilinguality:monolingual",
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"language:en",
"license:other",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["automatic-speech-recognition"], "task_ids": ["speech-recognition"], "p... | 2022-10-24T14:32:04+00:00 | [] | [
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|
# Dataset Card for the Buckeye Corpus (buckeye_asr)
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
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255b4bb51b0eeceec18b06cb372b73f2b5910550 |
# Dataset Card for P3
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
-... | bigscience/P3 | [
"task_categories:other",
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"license:apache-2.0",
"arxiv:2110.08207",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["crowdsourced", "expert-generated"], "language": ["en"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["100M<n<1B"], "task_categories": ["other"], "pretty_name": "P3"} | 2023-02-01T13:38:41+00:00 | [
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|
# Dataset Card for P3
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Additional Info... | [
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d8ed6544788253c114d64a2ba69c0b6c0f2ffa2d | # QA-Align
This dataset contains QA-Alignments --- fine-grained annotations of cross-text content overlap.
The task input is two sentences from two documents, roughly talking about the same event, along with their QA-SRL annotations
which capture verbal predicate-argument relations in question-answer format. The out... | biu-nlp/qa_align | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-11-19T01:01:40+00:00 | [] | [] | TAGS
#region-us
| # QA-Align
This dataset contains QA-Alignments --- fine-grained annotations of cross-text content overlap.
The task input is two sentences from two documents, roughly talking about the same event, along with their QA-SRL annotations
which capture verbal predicate-argument relations in question-answer format. The out... | [
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80e6b8ce552fc15f9ee698b414d677db1d6567fd | # QA-SRL 2020 (Gold Standard)
The dataset contains question-answer pairs to model verbal predicate-argument structure.
The questions start with wh-words (Who, What, Where, What, etc.) and contain a verb predicate in the sentence; the answers are phrases in the sentence.
This dataset, a.k.a "QASRL-GS" (Gold Standard) ... | biu-nlp/qa_srl2020 | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-10-17T19:49:01+00:00 | [] | [] | TAGS
#region-us
| # QA-SRL 2020 (Gold Standard)
The dataset contains question-answer pairs to model verbal predicate-argument structure.
The questions start with wh-words (Who, What, Where, What, etc.) and contain a verb predicate in the sentence; the answers are phrases in the sentence.
This dataset, a.k.a "QASRL-GS" (Gold Standard) ... | [
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5499db7c8223f09187bc8b4bc81d689758ceb5f8 | # QANom
This dataset contains question-answer pairs to model the predicate-argument structure of deverbal nominalizations.
The questions start with wh-words (Who, What, Where, What, etc.) and contain the verbal form of a nominalization from the sentence;
the answers are phrases in the sentence.
See the paper for ... | biu-nlp/qanom | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-10-18T08:50:01+00:00 | [] | [] | TAGS
#region-us
| # QANom
This dataset contains question-answer pairs to model the predicate-argument structure of deverbal nominalizations.
The questions start with wh-words (Who, What, Where, What, etc.) and contain the verbal form of a nominalization from the sentence;
the answers are phrases in the sentence.
See the paper for ... | [
"# QANom \n\nThis dataset contains question-answer pairs to model the predicate-argument structure of deverbal nominalizations. \nThe questions start with wh-words (Who, What, Where, What, etc.) and contain the verbal form of a nominalization from the sentence; \nthe answers are phrases in the sentence. \n\nSee the... | [
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b7c9fe729920578a60d6a294a6f6a81496d6c6fc |
### Dataset Summary
This dataset contains 190,335 Russian Q&A posts from a medical related forum.
### Dataset Fields
* date: date and time of the asked question, like '26 Октября 2018, 08:30'
* categ: question category
* theme: question topic
* desc: question text
* ans: question answers separated with ';\n'
* spec10... | blinoff/medical_qa_ru_data | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ru",
"license:unknown",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": [], "language_creators": [], "language": ["ru"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["closed-domain-qa"], "pretty_name": "Medical Q&A Russian Data"} | 2022-07-02T05:24:13+00:00 | [] | [
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|
### Dataset Summary
This dataset contains 190,335 Russian Q&A posts from a medical related forum.
### Dataset Fields
* date: date and time of the asked question, like '26 Октября 2018, 08:30'
* categ: question category
* theme: question topic
* desc: question text
* ans: question answers separated with ';\n'
* spec10... | [
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4949de27eaa80078f2253d1d254709a5e06a47a7 | The dataset is in the form of a json lines file with 10,657 examples, where an example consists of text (extracted from the first 13,000 rows of OSCAR unshuffled English dataset) and metadata fields (entities).
Structure of an example.
```
{
"text": "This is exactly the sort of article to raise the profile of the... | bs-modeling-metadata/OSCAR_Entity_13_000 | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-09-15T13:20:53+00:00 | [] | [] | TAGS
#region-us
| The dataset is in the form of a json lines file with 10,657 examples, where an example consists of text (extracted from the first 13,000 rows of OSCAR unshuffled English dataset) and metadata fields (entities).
Structure of an example.
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
f6cba351f9d1893a3b60f76455cdbd64fc0239c7 | The dataset is in the form of a json lines file with 1,20,000 examples, where an example consists of text (extracted from C4 English dataset) and metadata fields (website description extracted from Wikipedia).
Example:
```
{
"text": "US10289222B2 - Handling of touch events in a browser environment - Google Patents... | bs-modeling-metadata/website_metadata_c4 | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-11-24T14:04:30+00:00 | [] | [] | TAGS
#region-us
| The dataset is in the form of a json lines file with 1,20,000 examples, where an example consists of text (extracted from C4 English dataset) and metadata fields (website description extracted from Wikipedia).
Example:
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
da29f2b2fc7c86176813b8a6440f73e0823f05d3 | # Dataset Card for the args.me corpus
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Usage](#dataset-usage)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#langu... | cakiki/args_me | [
"task_categories:text-retrieval",
"task_ids:document-retrieval",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"license:cc-by-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["crowdsourced"], "language": ["'en-US'"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["text-retrieval"], "task_ids": ["document-retrieval"], "pre... | 2022-10-25T08:07:25+00:00 | [] | [
"'en-US'"
] | TAGS
#task_categories-text-retrieval #task_ids-document-retrieval #annotations_creators-machine-generated #language_creators-crowdsourced #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #license-cc-by-4.0 #region-us
| # Dataset Card for the URL corpus
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Dataset Usage
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
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aba728f708a01b22a508061490cf389dd15f6ca2 | ## Dataset Summary
Contains 15 Harry Potter trivia questions in Squadv2 format, 3 of which are unanswerable.
## Model Performance
[Test Notebook](https://colab.research.google.com/drive/1VFUJKV7eun68XgQDAHSHsbvoM_CGHzWA?usp=sharing)
| Model | exact | f1 |
| ----------- | ----------- | ----------- |
| Albert Ba... | caltonji/harrypotter_squad_v2_2 | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-12-31T20:01:23+00:00 | [] | [] | TAGS
#region-us
| Dataset Summary
---------------
Contains 15 Harry Potter trivia questions in Squadv2 format, 3 of which are unanswerable.
Model Performance
-----------------
Test Notebook
Model: Albert Base (twmkn9/albert-base-v2-squad2), exact: 46.6667, f1: 46.6667
Model: Albert XXLarge (ahotrod/albert\_xxlargev1\_squad2\_512... | [] | [
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1059be355e830b808093595856135651e770d22c |
**QR-AN Dataset: a classification and generation dataset of french Parliament questions-answers.**
This is a dataset for theme/topic classification, made of questions and answers from https://www2.assemblee-nationale.fr/recherche/resultats_questions . \
It contains 188 unbalanced classes, 80k questions-answers divi... | cassandra-themis/QR-AN | [
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QR-AN Dataset: a classification and generation dataset of french Parliament questions-answers.
This is a dataset for theme/topic classification, made of questions and answers from URL . \
It contains 188 unbalanced classes, 80k questions-answers divided into 3 splits: train (60k), val (10k) and test (10k). \
Can b... | [] | [
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d83da9653ef2a5f823c3693a28018e3009464522 |
# Dataset Card for AfriBERTa's Corpus
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Loading Dataset](#loading-dataset)
- [Dataset Structure](#dataset-... | castorini/afriberta-corpus | [
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# Dataset Card for AfriBERTa's Corpus
## Table of Contents
- Dataset Description
- Dataset Summary
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- Loading Dataset
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- Data Fields
- Data Splits
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3a3aa212bbe94a8cc0dc858710a3dad49d532054 |
# Dataset Summary
Mr. TyDi is a multi-lingual benchmark dataset built on TyDi, covering eleven typologically diverse languages. It is designed for monolingual retrieval, specifically to evaluate ranking with learned dense representations.
This dataset stores documents of Mr. TyDi. To access the queries and judgments,... | castorini/mr-tydi-corpus | [
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# Dataset Summary
Mr. TyDi is a multi-lingual benchmark dataset built on TyDi, covering eleven typologically diverse languages. It is designed for monolingual retrieval, specifically to evaluate ranking with learned dense representations.
This dataset stores documents of Mr. TyDi. To access the queries and judgments,... | [
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1d43c80218d06d0ef80f5b172ccabd848b948bc1 |
# Dataset Summary
Mr. TyDi is a multi-lingual benchmark dataset built on TyDi, covering eleven typologically diverse languages. It is designed for monolingual retrieval, specifically to evaluate ranking with learned dense representations.
This dataset stores the queries, judgements, and example training data of Mr. T... | castorini/mr-tydi | [
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# Dataset Summary
Mr. TyDi is a multi-lingual benchmark dataset built on TyDi, covering eleven typologically diverse languages. It is designed for monolingual retrieval, specifically to evaluate ranking with learned dense representations.
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73205571221e7eac6953ed884e05c8625e06272c | # Dataset Summary
The repo provides queries generated for the MS MARCO V1 document corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, generates questi... | castorini/msmarco_v1_doc_doc2query-t5_expansions | [
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| # Dataset Summary
The repo provides queries generated for the MS MARCO V1 document corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, generates questi... | [
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4254f0bda2a6e562cb2e53001220e0f1f981d2b8 | # Dataset Summary
The repo provides queries generated for the MS MARCO V1 document segmented corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, genera... | castorini/msmarco_v1_doc_segmented_doc2query-t5_expansions | [
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aca81f4eabebd63c46026565b9123b17269bb1c4 | # Dataset Summary
The repo provides queries generated for the MS MARCO V1 passage corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, generates questio... | castorini/msmarco_v1_passage_doc2query-t5_expansions | [
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cb336701cbfdf1de2df51de8315b27fcec566c56 | # Dataset Summary
The repo provides queries generated for the MS MARCO v2 document corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, generates questi... | castorini/msmarco_v2_doc_doc2query-t5_expansions | [
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The repo provides queries generated for the MS MARCO v2 document corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, generates questi... | [
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61325a80b2ff2b81642bd532483dc51d0b46a8fb | # Dataset Summary
The repo provides queries generated for the MS MARCO v2 document segmented corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, genera... | castorini/msmarco_v2_doc_segmented_doc2query-t5_expansions | [
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| # Dataset Summary
The repo provides queries generated for the MS MARCO v2 document segmented corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, genera... | [
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22a0c06017015ef75b33d066711b1ebc2ddb7e8e | # Dataset Summary
The repo provides queries generated for the MS MARCO v2 passage corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, generates questio... | castorini/msmarco_v2_passage_doc2query-t5_expansions | [
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The repo provides queries generated for the MS MARCO v2 passage corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that when given an input document, generates questio... | [
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cc0700180b0a2f2618a039cb4827e51948986b6e | # Dataset Summary
The repo provides answer, title and sentence expansions for the Natural Questions corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
```
{
"id": "1",
"predicted_answers": ["312"], "predicted_titles": ["Invisible Man"... | castorini/nq_gar-t5_expansions | [
"language:en",
"license:apache-2.0",
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"en"
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#language-English #license-apache-2.0 #region-us
| # Dataset Summary
The repo provides answer, title and sentence expansions for the Natural Questions corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
An example data entry of the test split looks as follows:
# Load Dataset
An example to l... | [
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"# Dataset Structure\nThere are dev and test folds\n\nAn example data entry of the dev split looks as follows:\n\n\nAn example ... | [
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5e899a9b63776d2982c72aa242cc35ecdb7073a4 | # Dataset Summary
The repo provides answer,title and sentence expansions for the Trivia QA corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
```
{
"id": "1",
"predicted_answers": ["Bz"], "predicted_titles": ["Vehicle regist... | castorini/triviaqa_gar-t5_expansions | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["English"], "license": "Apache License 2.0"} | 2022-02-17T00:58:32+00:00 | [] | [
"English"
] | TAGS
#region-us
| # Dataset Summary
The repo provides answer,title and sentence expansions for the Trivia QA corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
An example data entry of the test split looks as follows:
# Load Dataset
An example ... | [
"# Dataset Summary\r\nThe repo provides answer,title and sentence expansions for the Trivia QA corpus with gar-T5.",
"# Dataset Structure\r\nThere are dev and test folds\r\n\r\nAn example data entry of the dev split looks as follows:\r\n\r\n\r\nAn example data entry of the test split looks as follows:",
"# Load... | [
"TAGS\n#region-us \n",
"# Dataset Summary\r\nThe repo provides answer,title and sentence expansions for the Trivia QA corpus with gar-T5.",
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f9bd92144ed76200d6eb3ce73a8bd4eba9ffdc85 |
**Arxiv Classification: a classification of Arxiv Papers (11 classes).**
This dataset is intended for long context classification (documents have all > 4k tokens). \
Copied from "Long Document Classification From Local Word Glimpses via Recurrent Attention Learning"
```
@ARTICLE{8675939,
author={He, Jun and Wang, ... | ccdv/arxiv-classification | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:topic-classification",
"size_categories:10K<n<100K",
"language:en",
"long context",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": "en", "size_categories": "10K<n<100K", "task_categories": ["text-classification"], "task_ids": ["multi-class-classification", "topic-classification"], "tags": ["long context"]} | 2022-10-22T08:23:50+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #size_categories-10K<n<100K #language-English #long context #region-us
|
Arxiv Classification: a classification of Arxiv Papers (11 classes).
This dataset is intended for long context classification (documents have all > 4k tokens). \
Copied from "Long Document Classification From Local Word Glimpses via Recurrent Attention Learning"
* See: URL
* See: URL
It contains 11 slightly un... | [] | [
"TAGS\n#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #size_categories-10K<n<100K #language-English #long context #region-us \n"
] | [
58
] | [
"passage: TAGS\n#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #size_categories-10K<n<100K #language-English #long context #region-us \n"
] |
f70ea0378deb9b1c8fa1032168dc4ea7d77f3259 |
# Arxiv dataset for summarization
Dataset for summarization of long documents.\
Adapted from this [repo](https://github.com/armancohan/long-summarization).\
Note that original data are pre-tokenized so this dataset returns " ".join(text) and add "\n" for paragraphs. \
This dataset is compatible with the [`run_summari... | ccdv/arxiv-summarization | [
"task_categories:summarization",
"task_categories:text-generation",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"language:en",
"conditional-text-generation",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "task_categories": ["summarization", "text-generation"], "task_ids": [], "tags": ["conditional-text-generation"], "train-eval-index": [{"config": "document", "task": "summarization", "task_id": "summarization", "splits": {"eval_s... | 2022-12-08T06:58:05+00:00 | [] | [
"en"
] | TAGS
#task_categories-summarization #task_categories-text-generation #multilinguality-monolingual #size_categories-100K<n<1M #language-English #conditional-text-generation #region-us
| Arxiv dataset for summarization
===============================
Dataset for summarization of long documents.
Adapted from this repo.
Note that original data are pre-tokenized so this dataset returns " ".join(text) and add "\n" for paragraphs.
This dataset is compatible with the 'run\_summarization.py' scrip... | [
"### Data Fields\n\n\n* 'id': paper id\n* 'article': a string containing the body of the paper\n* 'abstract': a string containing the abstract of the paper",
"### Data Splits\n\n\nThis dataset has 3 splits: *train*, *validation*, and *test*. \n\nToken counts are white space based.\n\n\n\nCite original article\n... | [
"TAGS\n#task_categories-summarization #task_categories-text-generation #multilinguality-monolingual #size_categories-100K<n<1M #language-English #conditional-text-generation #region-us \n",
"### Data Fields\n\n\n* 'id': paper id\n* 'article': a string containing the body of the paper\n* 'abstract': a string conta... | [
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dc2ce3bd19d8e323365bc1a244f3dd32e02d4f22 |
**Copy of the [cnn_dailymail](https://huggingface.co/datasets/cnn_dailymail) dataset fixing the "NotADirectoryError: [Errno 20]".**
# Dataset Card for CNN Dailymail Dataset
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards... | ccdv/cnn_dailymail | [
"task_categories:summarization",
"task_categories:text-generation",
"annotations_creators:no-annotation",
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"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"conditional-text-generation",
"region... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["en"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["summarization", "text-generation"], "task_ids": [], "paperswithcode_id": ... | 2022-10-24T19:31:59+00:00 | [] | [
"en"
] | TAGS
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| Copy of the cnn\_dailymail dataset fixing the "NotADirectoryError: [Errno 20]".
Dataset Card for CNN Dailymail Dataset
======================================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data In... | [
"### Dataset Summary\n\n\nThe CNN / DailyMail Dataset is an English-language dataset containing just over 300k unique news articles as written by journalists at CNN and the Daily Mail. The current version supports both extractive and abstractive summarization, though the original version was created for machine rea... | [
"TAGS\n#task_categories-summarization #task_categories-text-generation #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-apache-2.0 #conditional-text-generation #region-us \n",
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b949637ab41c9f668a4b83cea46c80b489c02290 |
# GovReport dataset for summarization
Dataset for summarization of long documents.\
Adapted from this [repo](https://github.com/luyang-huang96/LongDocSum) and this [paper](https://arxiv.org/pdf/2104.02112.pdf)\
This dataset is compatible with the [`run_summarization.py`](https://github.com/huggingface/transformers/tr... | ccdv/govreport-summarization | [
"task_categories:summarization",
"task_categories:text-generation",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:en",
"conditional-text-generation",
"arxiv:2104.02112",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "task_categories": ["summarization", "text-generation"], "task_ids": [], "tags": ["conditional-text-generation"]} | 2022-10-24T19:32:47+00:00 | [
"2104.02112"
] | [
"en"
] | TAGS
#task_categories-summarization #task_categories-text-generation #multilinguality-monolingual #size_categories-10K<n<100K #language-English #conditional-text-generation #arxiv-2104.02112 #region-us
| GovReport dataset for summarization
===================================
Dataset for summarization of long documents.
Adapted from this repo and this paper
This dataset is compatible with the 'run\_summarization.py' script from Transformers if you add this line to the 'summarization\_name\_mapping' variable:
#... | [
"### Data Fields\n\n\n* 'id': paper id\n* 'report': a string containing the body of the report\n* 'summary': a string containing the summary of the report",
"### Data Splits\n\n\nThis dataset has 3 splits: *train*, *validation*, and *test*. \n\nToken counts with a RoBERTa tokenizer.\n\n\n\nCite original article... | [
"TAGS\n#task_categories-summarization #task_categories-text-generation #multilinguality-monolingual #size_categories-10K<n<100K #language-English #conditional-text-generation #arxiv-2104.02112 #region-us \n",
"### Data Fields\n\n\n* 'id': paper id\n* 'report': a string containing the body of the report\n* 'summar... | [
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2f38a1dfdecfacee0184d74eaeafd3c0fb49d2a6 |
**Patent Classification: a classification of Patents and abstracts (9 classes).**
This dataset is intended for long context classification (non abstract documents are longer that 512 tokens). \
Data are sampled from "BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization." by Eva Sharma, Chen Li... | ccdv/patent-classification | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:topic-classification",
"size_categories:10K<n<100K",
"language:en",
"long context",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": "en", "size_categories": "10K<n<100K", "task_categories": ["text-classification"], "task_ids": ["multi-class-classification", "topic-classification"], "tags": ["long context"]} | 2022-10-22T08:25:36+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #size_categories-10K<n<100K #language-English #long context #region-us
|
Patent Classification: a classification of Patents and abstracts (9 classes).
This dataset is intended for long context classification (non abstract documents are longer that 512 tokens). \
Data are sampled from "BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization." by Eva Sharma, Chen Li and... | [] | [
"TAGS\n#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #size_categories-10K<n<100K #language-English #long context #region-us \n"
] | [
58
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"passage: TAGS\n#task_categories-text-classification #task_ids-multi-class-classification #task_ids-topic-classification #size_categories-10K<n<100K #language-English #long context #region-us \n"
] |
26155ccf2b18393a38a05fafc26c66a068974839 |
# PubMed dataset for summarization
Dataset for summarization of long documents.\
Adapted from this [repo](https://github.com/armancohan/long-summarization).\
Note that original data are pre-tokenized so this dataset returns " ".join(text) and add "\n" for paragraphs. \
This dataset is compatible with the [`run_summar... | ccdv/pubmed-summarization | [
"task_categories:summarization",
"task_categories:text-generation",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"language:en",
"conditional-text-generation",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "task_categories": ["summarization", "text-generation"], "task_ids": [], "tags": ["conditional-text-generation"]} | 2022-10-24T19:33:04+00:00 | [] | [
"en"
] | TAGS
#task_categories-summarization #task_categories-text-generation #multilinguality-monolingual #size_categories-100K<n<1M #language-English #conditional-text-generation #region-us
| PubMed dataset for summarization
================================
Dataset for summarization of long documents.
Adapted from this repo.
Note that original data are pre-tokenized so this dataset returns " ".join(text) and add "\n" for paragraphs.
This dataset is compatible with the 'run\_summarization.py' scr... | [
"### Data Fields\n\n\n* 'id': paper id\n* 'article': a string containing the body of the paper\n* 'abstract': a string containing the abstract of the paper",
"### Data Splits\n\n\nThis dataset has 3 splits: *train*, *validation*, and *test*. \n\nToken counts are white space based.\n\n\n\nCite original article\n... | [
"TAGS\n#task_categories-summarization #task_categories-text-generation #multilinguality-monolingual #size_categories-100K<n<1M #language-English #conditional-text-generation #region-us \n",
"### Data Fields\n\n\n* 'id': paper id\n* 'article': a string containing the body of the paper\n* 'abstract': a string conta... | [
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464088ad69bd568eba869f3af6bc2f16a9cd9a5c | ## Dataset Description
- **Homepage:** cdleong.github.io
# Dataset Summary:
Pig-latin machine and English parallel machine translation corpus.
Based on [The Project Gutenberg EBook of "De Bello Gallico" and Other Commentaries](https://www.gutenberg.org/ebooks/10657)
Converted to pig-latin with https://github.com/... | cdleong/piglatin-mt | [
"task_categories:translation",
"multilinguality:translation",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "license": ["mit"], "multilinguality": ["translation"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["translation"], "task_ids": [], "language_details": "eng and engyay"} | 2022-10-24T18:22:09+00:00 | [] | [
"en"
] | TAGS
#task_categories-translation #multilinguality-translation #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #region-us
| ## Dataset Description
- Homepage: URL
# Dataset Summary:
Pig-latin machine and English parallel machine translation corpus.
Based on The Project Gutenberg EBook of "De Bello Gallico" and Other Commentaries
Converted to pig-latin with URL
Blank lines removed.
## Dataset Structure
### Data Instances
### D... | [
"## Dataset Description\n\n- Homepage: URL",
"# Dataset Summary: \nPig-latin machine and English parallel machine translation corpus. \n\nBased on The Project Gutenberg EBook of \"De Bello Gallico\" and Other Commentaries\n\nConverted to pig-latin with URL\n\nBlank lines removed.",
"## Dataset Structure",
"##... | [
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edb6563c1ba616922132466f1a969807bba8651e |
## Dataset Description
- **Homepage:** https://zenodo.org/record/4661645
TEMPORARY TEST DATASET
Not for actual use! Attempting to test out a dataset script for loading https://zenodo.org/record/4661645
| cdleong/temp_africaNLP_keyword_spotting_for_african_languages | [
"language:wo",
"language:fuc",
"language:srr",
"language:mnk",
"language:snk",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["wo", "fuc", "srr", "mnk", "snk"]} | 2022-10-25T08:07:32+00:00 | [] | [
"wo",
"fuc",
"srr",
"mnk",
"snk"
] | TAGS
#language-Wolof #language-Pulaar #language-Serer #language-Mandinka #language-Soninke #region-us
|
## Dataset Description
- Homepage: URL
TEMPORARY TEST DATASET
Not for actual use! Attempting to test out a dataset script for loading URL
| [
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] |
2784446f8e97c8a4a2ce7242bb8a7537b36ff3dc | This dataset has 336 pieces of quotes from William Shakespeare and Taylor Swift (labeled) for supervised classification.
Source: https://www.kaggle.com/kellylougheed/tswift-vs-shakespeare | cemigo/taylor_vs_shakes | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-03-14T23:45:59+00:00 | [] | [] | TAGS
#region-us
| This dataset has 336 pieces of quotes from William Shakespeare and Taylor Swift (labeled) for supervised classification.
Source: URL | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
321516f50bdcc1214fa75164c545478976ed84bd | <p align="center"><img src="https://huggingface.co/datasets/cfilt/HiNER-collapsed/raw/main/cfilt-dark-vec.png" alt="Computation for Indian Language Technology Logo" width="150" height="150"/></p>
# IITB-English-Hindi Parallel Corpus
[![License: CC BY-NC 4.0](https://img.shields.io/badge/License-CC%20BY--NC%204.0-ligh... | cfilt/iitb-english-hindi | [
"language:en",
"language:hi",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en", "hi"]} | 2023-12-30T12:00:15+00:00 | [] | [
"en",
"hi"
] | TAGS
#language-English #language-Hindi #region-us
| <p align="center"><img src="URL alt="Computation for Indian Language Technology Logo" width="150" height="150"/></p>
# IITB-English-Hindi Parallel Corpus
![License: CC BY-NC 4.0](URL
![Twitter Follow](URL
![Twitter Follow](URL
## About
The IIT Bombay English-Hindi corpus contains parallel corpus for English-Hindi a... | [
"# IITB-English-Hindi Parallel Corpus\n\n![License: CC BY-NC 4.0](URL \n![Twitter Follow](URL\n![Twitter Follow](URL",
"## About\n\nThe IIT Bombay English-Hindi corpus contains parallel corpus for English-Hindi as well as monolingual Hindi corpus collected from a variety of existing sources and corpora developed ... | [
"TAGS\n#language-English #language-Hindi #region-us \n",
"# IITB-English-Hindi Parallel Corpus\n\n![License: CC BY-NC 4.0](URL \n![Twitter Follow](URL\n![Twitter Follow](URL",
"## About\n\nThe IIT Bombay English-Hindi corpus contains parallel corpus for English-Hindi as well as monolingual Hindi corpus collecte... | [
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"passage: TAGS\n#language-English #language-Hindi #region-us \n# IITB-English-Hindi Parallel Corpus\n\n
## Getting Started
```python
import matplotlib.pyplot as plt
import numpy as np
from datasets import load_dataset
# load dataset
dataset = load_datase... | cgarciae/point-cloud-mnist | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-10-31T23:09:55+00:00 | [] | [] | TAGS
#region-us
| # Point CLoud MNIST
A point cloud version of the original MNIST.
!sample
## Getting Started
## Format
* 'points': '(batch, point, 3)' array of uint8.
* 'label': '(batch, 1)' array of uint8.
Where 'point' is the number of points in the point cloud. Points have no order and were shuffled when creating the data. E... | [
"# Point CLoud MNIST\n\nA point cloud version of the original MNIST.\n\n!sample",
"## Getting Started",
"## Format\n\n* 'points': '(batch, point, 3)' array of uint8.\n* 'label': '(batch, 1)' array of uint8.\n\nWhere 'point' is the number of points in the point cloud. Points have no order and were shuffled when ... | [
"TAGS\n#region-us \n",
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"## Getting Started",
"## Format\n\n* 'points': '(batch, point, 3)' array of uint8.\n* 'label': '(batch, 1)' array of uint8.\n\nWhere 'point' is the number of points in the point cloud. Points have no orde... | [
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"passage: TAGS\n#region-us \n# Point CLoud MNIST\n\nA point cloud version of the original MNIST.\n\n!sample## Getting Started## Format\n\n* 'points': '(batch, point, 3)' array of uint8.\n* 'label': '(batch, 1)' array of uint8.\n\nWhere 'point' is the number of points in the point cloud. Points have no order and wer... |
c3d46ee0b1969347cb803449156be9a59e275ae7 |
## Dataset Description
- **Homepage:** [scielo.org](https://search.livros.scielo.org/search/?fb=&where=BOOK&filter%5Bis_comercial_filter%5D%5B%5D=f)
### Dataset Summary
This dataset contains all text from open-access PDFs on [scielo.org](https://search.livros.scielo.org/search/?fb=&where=BOOK&filter%5Bis_comercial... | chenghao/scielo_books | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"language:pt",
"language:es",
"license:cc-by-nc-sa-3.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["en", "pt", "es"], "license": ["cc-by-nc-sa-3.0"], "multilinguality": ["multilingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["sequence-modeling"], "task_ids": ["language-modeling"]} | 2022-07-01T17:34:59+00:00 | [] | [
"en",
"pt",
"es"
] | TAGS
#task_ids-language-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-multilingual #size_categories-n<1K #source_datasets-original #language-English #language-Portuguese #language-Spanish #license-cc-by-nc-sa-3.0 #region-us
|
## Dataset Description
- Homepage: URL
### Dataset Summary
This dataset contains all text from open-access PDFs on URL. As of Dec. 5 2021, the total number of books available is 962. Some of them are not in native PDF format (e.g. scanned images) though.
### Supported Tasks and Leaderboards
- 'sequence-modeling'... | [
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"### Supported Tasks and Leaderboards\n\n- 's... | [
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d51bd8aa4dcb0d95600de289e7c6ea761d412c2d |
# Dataset Card for [KsponSpeech]
## Table of Contents
- [Table of Contents](#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... | cheulyop/ksponspeech | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]} | 2021-10-02T03:27:13+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for [KsponSpeech]
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Pe... | [
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b1e632ba5e39486891c9ade0d6ba70561993c91d | This data can help in solving contradiction detection problem. this data is picked from kaggle.
reference - Contradictory, My DWatson | chitra/contradictionNLI | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-12-29T10:45:19+00:00 | [] | [] | TAGS
#region-us
| This data can help in solving contradiction detection problem. this data is picked from kaggle.
reference - Contradictory, My DWatson | [] | [
"TAGS\n#region-us \n"
] | [
6
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"passage: TAGS\n#region-us \n"
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de949e03d6bdecb42f9300fb9be8f5a9b5acf5f4 | This is extracted from telugu subset from https://huggingface.co/datasets/ai4bharat/samanantar - used to create telugu kenLM models for ASR decoding. | chmanoj/ai4bharat__samanantar_processed_te | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-05T04:02:51+00:00 | [] | [] | TAGS
#region-us
| This is extracted from telugu subset from URL - used to create telugu kenLM models for ASR decoding. | [] | [
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6
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24fba98c601fcde47d5a50fe72d54fdf70b69e11 | Dhivehi dataset for MNT | chopey/dhivehi | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-11-30T03:41:11+00:00 | [] | [] | TAGS
#region-us
| Dhivehi dataset for MNT | [] | [
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6051cc3ed097fbbe93c7cc2c480279e230f43e93 |
# Punctuation restoration from read text
Restore punctuation marks from the output of an ASR system.
## Motivation
Speech transcripts generated by Automatic Speech Recognition (ASR) systems typically do not contain any punctuation or capitalization. In longer stretches of automatically recognized speech, the lack o... | clarin-pl/2021-punctuation-restoration | [
"task_categories:automatic-speech-recognition",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:n<1K",
"language:pl",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["pl"], "license": [], "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": [], "task_categories": ["automatic-speech-recognition"], "task_ids": [], "pretty_name": "2021-punctuation-restoration",... | 2022-08-29T15:39:18+00:00 | [] | [
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] | TAGS
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| Punctuation restoration from read text
======================================
Restore punctuation marks from the output of an ASR system.
Motivation
----------
Speech transcripts generated by Automatic Speech Recognition (ASR) systems typically do not contain any punctuation or capitalization. In longer stretches... | [
"### Forced-aligned transcriptions\n\n\nWe use force-aligned transcriptions of the original texts to approximate ASR output. Files in the *.clntmstmp* format contain forced-alignment of the original text together with the audio file read out by a group of volunteers. The files may contain errors resulting from inco... | [
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"passage: ### Forced-aligned transcriptions\n\n\nWe use force-aligned transcriptions of the original ... |
55467c09094ac3a0d8261013f884f8f3247b53a0 |
# AspectEmo
## Description
AspectEmo Corpus is an extended version of a publicly available PolEmo 2.0 corpus of Polish customer reviews used in many projects on the use of different methods in sentiment analysis. The AspectEmo corpus consists of four subcorpora, each containing online customer reviews from the follo... | clarin-pl/aspectemo | [
"task_categories:token-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
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"multilinguality:monolingual",
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"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:mit",
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... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["other"], "language": ["pl"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["1K", "1K<n<10K"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["sentiment-classification"], "prett... | 2022-08-29T15:39:32+00:00 | [] | [
"pl"
] | TAGS
#task_categories-token-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-1K #size_categories-1K<n<10K #source_datasets-original #language-Polish #license-mit #region-us
| AspectEmo
=========
Description
-----------
AspectEmo Corpus is an extended version of a publicly available PolEmo 2.0 corpus of Polish customer reviews used in many projects on the use of different methods in sentiment analysis. The AspectEmo corpus consists of four subcorpora, each containing online customer revi... | [
"### Loading",
"### Evaluation"
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"TAGS\n#task_categories-token-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-1K #size_categories-1K<n<10K #source_datasets-original #language-Polish #license-mit #region-us \n",
"### Loading",
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a20247f8787670ef987fa61e1c9139227c186105 |
# KPWR-NER
## Description
KPWR-NER is a part the Polish Corpus of Wrocław University of Technology (*Korpus Języka Polskiego Politechniki Wrocławskiej*). Its objective is named entity recognition for fine-grained categories of entities. It is the ‘n82’ version of the KPWr, which means that number of classes is restr... | clarin-pl/kpwr-ner | [
"task_categories:other",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:18K",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:cc-by-3.0",
"structure-predict... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["pl"], "license": ["cc-by-3.0"], "multilinguality": ["monolingual"], "size_categories": ["18K", "10K<n<100K"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": ["named-entity-recognition"], "pretty_name... | 2023-01-30T22:54:02+00:00 | [] | [
"pl"
] | TAGS
#task_categories-other #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-18K #size_categories-10K<n<100K #source_datasets-original #language-Polish #license-cc-by-3.0 #structure-prediction #region-us
| KPWR-NER
========
Description
-----------
KPWR-NER is a part the Polish Corpus of Wrocław University of Technology (*Korpus Języka Polskiego Politechniki Wrocławskiej*). Its objective is named entity recognition for fine-grained categories of entities. It is the ‘n82’ version of the KPWr, which means that number of... | [
"### Loading",
"### Evaluation"
] | [
"TAGS\n#task_categories-other #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-18K #size_categories-10K<n<100K #source_datasets-original #language-Polish #license-cc-by-3.0 #structure-prediction #region-us \n",
"### Lo... | [
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b77d0057aa0d3231fb40bd529a7e164ca887ba9f |
# nkjp-pos
## Description
NKJP-POS is a part the National Corpus of Polish (*Narodowy Korpus Języka Polskiego*). Its objective is part-of-speech tagging, e.g. nouns, verbs, adjectives, adverbs, etc. During the creation of corpus, texts of were annotated by humans from various sources, covering many domains and genre... | clarin-pl/nkjp-pos | [
"task_categories:other",
"task_ids:part-of-speech",
"annotations_creators:expert-generated",
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"size_categories:unknown",
"source_datasets:original",
"language:pl",
"license:gpl-3.0",
"structure-prediction",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["other"], "language": ["pl"], "license": ["gpl-3.0"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": ["part-of-speech"], "pretty_name": "nkjp-pos", "tags":... | 2023-01-30T22:53:57+00:00 | [] | [
"pl"
] | TAGS
#task_categories-other #task_ids-part-of-speech #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-unknown #source_datasets-original #language-Polish #license-gpl-3.0 #structure-prediction #region-us
| nkjp-pos
========
Description
-----------
NKJP-POS is a part the National Corpus of Polish (*Narodowy Korpus Języka Polskiego*). Its objective is part-of-speech tagging, e.g. nouns, verbs, adjectives, adverbs, etc. During the creation of corpus, texts of were annotated by humans from various sources, covering many ... | [
"### Loading",
"### Evaluation"
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"TAGS\n#task_categories-other #task_ids-part-of-speech #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-unknown #source_datasets-original #language-Polish #license-gpl-3.0 #structure-prediction #region-us \n",
"### Loading",
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] |
802e35d2b12bae84bb07911d841e8f046dc2fcef |
# Polemo2
## Description
The PolEmo2.0 is a dataset of online consumer reviews from four domains: medicine, hotels, products, and university. It is human-annotated on a level of full reviews and individual sentences. Current version (PolEmo 2.0) contains 8,216 reviews having 57,466 sentences. Each text and sentence ... | clarin-pl/polemo2-official | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:8K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:cc-by-sa-4.0",
"reg... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["other"], "language": ["pl"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["8K", "1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"]... | 2022-08-29T15:40:01+00:00 | [] | [
"pl"
] | TAGS
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| Polemo2
=======
Description
-----------
The PolEmo2.0 is a dataset of online consumer reviews from four domains: medicine, hotels, products, and university. It is human-annotated on a level of full reviews and individual sentences. Current version (PolEmo 2.0) contains 8,216 reviews having 57,466 sentences. Each te... | [
"### Loading",
"### Evaluation"
] | [
"TAGS\n#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-other #multilinguality-monolingual #size_categories-8K #size_categories-1K<n<10K #source_datasets-original #language-Polish #license-cc-by-sa-4.0 #region-us \n",
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52483dba0ff23291271ee9249839865e3c3e7e50 |
# Offensive language dataset of Croatian comments FRENK 1.0
English subset of the [FRENK dataset](http://hdl.handle.net/11356/1433). Also available on HuggingFace dataset hub: [Croatian subset](https://huggingface.co/datasets/5roop/FRENK-hate-hr), [Slovenian subset](https://huggingface.co/datasets/5roop/FRENK-hate-s... | classla/FRENK-hate-en | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"license:other",
"hate-speech-detection",
"offensive-language",
"arxiv:1906.02045",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "license": ["other"], "size_categories": ["1K<n<10K"], "task_categories": ["text-classification"], "task_ids": [], "tags": ["hate-speech-detection", "offensive-language"]} | 2022-10-21T06:52:06+00:00 | [
"1906.02045"
] | [
"en"
] | TAGS
#task_categories-text-classification #size_categories-1K<n<10K #language-English #license-other #hate-speech-detection #offensive-language #arxiv-1906.02045 #region-us
|
# Offensive language dataset of Croatian comments FRENK 1.0
English subset of the FRENK dataset. Also available on HuggingFace dataset hub: Croatian subset, Slovenian subset.
## Dataset Description
- Homepage: URL
- Repository: URL
- Paper: URL
- Project page URL
## Description of the original dataset
The ori... | [
"# Offensive language dataset of Croatian comments FRENK 1.0\n\nEnglish subset of the FRENK dataset. Also available on HuggingFace dataset hub: Croatian subset, Slovenian subset.",
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e7fc9f3d8d6c5640a26679d8a50b1666b02cc41f |
# Offensive language dataset of Croatian comments FRENK 1.0
Croatian subset of the [FRENK dataset](http://hdl.handle.net/11356/1433). Also available on HuggingFace dataset hub: [English subset](https://huggingface.co/datasets/5roop/FRENK-hate-en), [Slovenian subset](https://huggingface.co/datasets/5roop/FRENK-hate-s... | classla/FRENK-hate-hr | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:hr",
"license:other",
"hate-speech-detection",
"offensive-language",
"arxiv:1906.02045",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["hr"], "license": ["other"], "size_categories": ["1K<n<10K"], "task_categories": ["text-classification"], "task_ids": [], "tags": ["hate-speech-detection", "offensive-language"]} | 2022-10-21T06:46:28+00:00 | [
"1906.02045"
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"hr"
] | TAGS
#task_categories-text-classification #size_categories-1K<n<10K #language-Croatian #license-other #hate-speech-detection #offensive-language #arxiv-1906.02045 #region-us
|
# Offensive language dataset of Croatian comments FRENK 1.0
Croatian subset of the FRENK dataset. Also available on HuggingFace dataset hub: English subset, Slovenian subset.
## Dataset Description
- Homepage: URL
- Repository: URL
- Paper: URL
- Project page URL
## Description of the original dataset
>The origi... | [
"# Offensive language dataset of Croatian comments FRENK 1.0\n\nCroatian subset of the FRENK dataset. Also available on HuggingFace dataset hub: English subset, Slovenian subset.",
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"passage: TAGS\n#task_categories-text-classification #size_categories-1K<n<10K #language-Croatian #license-other #hate-speech-detection #offensive-language #arxiv-1906.02045 #region-us \n# Offensive language dataset of Croatian comments FRENK 1.0\n\nCroatian subset of the FRENK dataset. Also available on HuggingFac... |
37c8b42c63d4eb75f549679158a85eb5bd984caa |
Slovenian subset of the [FRENK dataset](http://hdl.handle.net/11356/1433). Also available on HuggingFace dataset hub: [English subset](https://huggingface.co/datasets/5roop/FRENK-hate-en), [Croatian subset](https://huggingface.co/datasets/5roop/FRENK-hate-hr).
## Dataset Description
- **Homepage:** http://hdl.hand... | classla/FRENK-hate-sl | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:sl",
"license:other",
"hate-speech-detection",
"offensive-language",
"arxiv:1906.02045",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["sl"], "license": ["other"], "size_categories": ["1K<n<10K"], "task_categories": ["text-classification"], "task_ids": [], "tags": ["hate-speech-detection", "offensive-language"]} | 2022-10-21T06:46:11+00:00 | [
"1906.02045"
] | [
"sl"
] | TAGS
#task_categories-text-classification #size_categories-1K<n<10K #language-Slovenian #license-other #hate-speech-detection #offensive-language #arxiv-1906.02045 #region-us
|
Slovenian subset of the FRENK dataset. Also available on HuggingFace dataset hub: English subset, Croatian subset.
## Dataset Description
- Homepage: URL
- Repository: URL
- Paper: URL
- Project page URL
## Description of the original dataset
>The original FRENK dataset consists of comments to Facebook posts (n... | [
"## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL\n- Project page URL",
"## Description of the original dataset\n\n>The original FRENK dataset consists of comments to Facebook posts (news articles) of mainstream media outlets from Croatia, Great Britain, and Slovenia, on the topics of mi... | [
"TAGS\n#task_categories-text-classification #size_categories-1K<n<10K #language-Slovenian #license-other #hate-speech-detection #offensive-language #arxiv-1906.02045 #region-us \n",
"## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL\n- Project page URL",
"## Description of the original ... | [
61,
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358,
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46
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"passage: TAGS\n#task_categories-text-classification #size_categories-1K<n<10K #language-Slovenian #license-other #hate-speech-detection #offensive-language #arxiv-1906.02045 #region-us \n## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL\n- Project page URL## Description of the original dat... |
f3f3a4708e6f8b92915ab02c20ac7fb829e45173 | The COPA-HR dataset (Choice of plausible alternatives in Croatian) is a translation
of the English COPA dataset (https://people.ict.usc.edu/~gordon/copa.html) by following the
XCOPA dataset translation methodology (https://arxiv.org/abs/2005.00333). The dataset consists of 1000 premises
(My body cast a shadow over t... | classla/copa_hr | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"language:hr",
"license:cc-by-sa-4.0",
"causal-reasoning",
"textual-entailment",
"commonsense-reasoning",
"arxiv:2005.00333",
"arxiv:2104.09243",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["hr"], "license": ["cc-by-sa-4.0"], "task_categories": ["text-classification"], "task_ids": ["natural-language-inference"], "tags": ["causal-reasoning", "textual-entailment", "commonsense-reasoning"]} | 2022-10-25T06:32:15+00:00 | [
"2005.00333",
"2104.09243"
] | [
"hr"
] | TAGS
#task_categories-text-classification #task_ids-natural-language-inference #language-Croatian #license-cc-by-sa-4.0 #causal-reasoning #textual-entailment #commonsense-reasoning #arxiv-2005.00333 #arxiv-2104.09243 #region-us
| The COPA-HR dataset (Choice of plausible alternatives in Croatian) is a translation
of the English COPA dataset (URL by following the
XCOPA dataset translation methodology (URL The dataset consists of 1000 premises
(My body cast a shadow over the grass), each given a question (What is the cause?), and two choices
(... | [] | [
"TAGS\n#task_categories-text-classification #task_ids-natural-language-inference #language-Croatian #license-cc-by-sa-4.0 #causal-reasoning #textual-entailment #commonsense-reasoning #arxiv-2005.00333 #arxiv-2104.09243 #region-us \n"
] | [
87
] | [
"passage: TAGS\n#task_categories-text-classification #task_ids-natural-language-inference #language-Croatian #license-cc-by-sa-4.0 #causal-reasoning #textual-entailment #commonsense-reasoning #arxiv-2005.00333 #arxiv-2104.09243 #region-us \n"
] |
708662e326e2e0ee4ce0fb7fa4e41db6c93771f0 |
The hr500k training corpus contains 506,457 Croatian tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation, named entities and dependency syntax.
On the sentence level, the dataset contains 20159 training samples, 1963 validation samples and 2672 test s... | classla/hr500k | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:part-of-speech",
"language:hr",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["hr"], "license": ["cc-by-sa-4.0"], "task_categories": ["other"], "task_ids": ["lemmatization", "named-entity-recognition", "part-of-speech"], "tags": ["structure-prediction", "normalization", "tokenization"]} | 2022-10-25T06:32:05+00:00 | [] | [
"hr"
] | TAGS
#task_categories-other #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-part-of-speech #language-Croatian #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us
|
The hr500k training corpus contains 506,457 Croatian tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation, named entities and dependency syntax.
On the sentence level, the dataset contains 20159 training samples, 1963 validation samples and 2672 test s... | [] | [
"TAGS\n#task_categories-other #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-part-of-speech #language-Croatian #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us \n"
] | [
81
] | [
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] |
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