sha stringlengths 40 40 | text stringlengths 1 13.4M | id stringlengths 2 117 | tags listlengths 1 7.91k | created_at stringlengths 25 25 | metadata stringlengths 2 875k | last_modified stringlengths 25 25 | arxiv listlengths 0 25 | languages listlengths 0 7.91k | tags_str stringlengths 17 159k | text_str stringlengths 1 447k | text_lists listlengths 0 352 | processed_texts listlengths 1 353 | tokens_length listlengths 1 353 | input_texts listlengths 1 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ba014295e666710c5dfe6215338933ecf235156c | The dataset contains 6273 training samples, 762 validation samples and 749 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent\_id'),
list of tokens ('tokens'), list of normalised word forms ('norms'), list of lemmas ('lemmas'),
list of Multext-East tags ('xpos\_ta... | classla/janes_tag | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:part-of-speech",
"language:si",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["si"], "license": ["cc-by-sa-4.0"], "task_categories": ["other"], "task_ids": ["lemmatization", "part-of-speech"], "tags": ["structure-prediction", "normalization", "tokenization"]} | 2022-10-25T06:31:04+00:00 | [] | [
"si"
] | TAGS
#task_categories-other #task_ids-lemmatization #task_ids-part-of-speech #language-Sinhala #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us
| The dataset contains 6273 training samples, 762 validation samples and 749 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent\_id'),
list of tokens ('tokens'), list of normalised word forms ('norms'), list of lemmas ('lemmas'),
list of Multext-East tags ('xpos\_ta... | [] | [
"TAGS\n#task_categories-other #task_ids-lemmatization #task_ids-part-of-speech #language-Sinhala #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us \n"
] | [
65
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] |
da293b9a70a87a936777e93dd59046ddbc6399ce | This dataset is based on 3,871 Croatian tweets that were segmented into sentences, tokens, and annotated with normalized forms, lemmas, MULTEXT-East tags (XPOS), UPOS tags and morphological features, and named entities.
The dataset contains 6339 training samples (sentences), 815 validation samples and 785 test samples... | classla/reldi_hr | [
"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"]} | 2022-10-25T06:30:56+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
| This dataset is based on 3,871 Croatian tweets that were segmented into sentences, tokens, and annotated with normalized forms, lemmas, MULTEXT-East tags (XPOS), UPOS tags and morphological features, and named entities.
The dataset contains 6339 training samples (sentences), 815 validation samples and 785 test samples... | [] | [
"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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] |
10a37a1a9ea782093646e0b03d5ef05b3e1e11d5 | This dataset is based on 3,748 Serbian tweets that were segmented into sentences, tokens, and annotated with normalized forms, lemmas, MULTEXT-East tags (XPOS), UPOS tags and morphological features, and named entities.
The dataset contains 5462 training samples (sentences), 711 validation samples and 725 test samples.... | classla/reldi_sr | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:part-of-speech",
"language:sr",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["sr"], "license": ["cc-by-sa-4.0"], "task_categories": ["other"], "task_ids": ["lemmatization", "named-entity-recognition", "part-of-speech"], "tags": ["structure-prediction", "normalization", "tokenization"]} | 2022-10-25T06:30:33+00:00 | [] | [
"sr"
] | TAGS
#task_categories-other #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-part-of-speech #language-Serbian #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us
| This dataset is based on 3,748 Serbian tweets that were segmented into sentences, tokens, and annotated with normalized forms, lemmas, MULTEXT-East tags (XPOS), UPOS tags and morphological features, and named entities.
The dataset contains 5462 training samples (sentences), 711 validation samples and 725 test samples.... | [] | [
"TAGS\n#task_categories-other #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-part-of-speech #language-Serbian #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us \n"
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79
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] |
42861d4054bc5fb993e6606e3c70a2957ec52e91 |
The SETimes\_sr training corpus contains 86,726 Serbian tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation, named entities and dependency syntax.
The dataset contains 3177 training samples, 395 validation samples and 319 test samples
across the resp... | classla/setimes_sr | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:part-of-speech",
"language:sr",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["sr"], "license": ["cc-by-sa-4.0"], "task_categories": ["other"], "task_ids": ["lemmatization", "named-entity-recognition", "part-of-speech"], "tags": ["structure-prediction", "normalization", "tokenization"]} | 2022-10-25T06:30:04+00:00 | [] | [
"sr"
] | TAGS
#task_categories-other #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-part-of-speech #language-Serbian #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us
|
The SETimes\_sr training corpus contains 86,726 Serbian tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation, named entities and dependency syntax.
The dataset contains 3177 training samples, 395 validation samples and 319 test samples
across the resp... | [] | [
"TAGS\n#task_categories-other #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-part-of-speech #language-Serbian #license-cc-by-sa-4.0 #structure-prediction #normalization #tokenization #region-us \n"
] | [
79
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] |
446b04c97cb43772a229cebbb8da0ce05ee03d2d | The dataset contains 7432 training samples, 1164 validation samples and 893 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent\_id'),
list of tokens ('tokens'), list of lemmas ('lemmas'),
list of Multext-East tags ('xpos\_tags), list of UPOS tags ('upos\_tags'), l... | classla/ssj500k | [
"task_categories:token-classification",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:parsing",
"task_ids:part-of-speech",
"language:sl",
"license:cc-by-sa-4.0",
"structure-prediction",
"tokenization",
"dependency-parsing",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["sl"], "license": ["cc-by-sa-4.0"], "task_categories": ["token-classification"], "task_ids": ["lemmatization", "named-entity-recognition", "parsing", "part-of-speech"], "tags": ["structure-prediction", "tokenization", "dependency-parsing"]} | 2022-10-28T04:37:22+00:00 | [] | [
"sl"
] | TAGS
#task_categories-token-classification #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-parsing #task_ids-part-of-speech #language-Slovenian #license-cc-by-sa-4.0 #structure-prediction #tokenization #dependency-parsing #region-us
| The dataset contains 7432 training samples, 1164 validation samples and 893 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent\_id'),
list of tokens ('tokens'), list of lemmas ('lemmas'),
list of Multext-East tags ('xpos\_tags), list of UPOS tags ('upos\_tags'), l... | [] | [
"TAGS\n#task_categories-token-classification #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-parsing #task_ids-part-of-speech #language-Slovenian #license-cc-by-sa-4.0 #structure-prediction #tokenization #dependency-parsing #region-us \n"
] | [
95
] | [
"passage: TAGS\n#task_categories-token-classification #task_ids-lemmatization #task_ids-named-entity-recognition #task_ids-parsing #task_ids-part-of-speech #language-Slovenian #license-cc-by-sa-4.0 #structure-prediction #tokenization #dependency-parsing #region-us \n"
] |
dcbb0c37d501225a976dc9e8a12bf0e20c8e2e04 | This is a very good dataset! | clem/autonlp-data-french_word_detection | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-09-14T08:45:38+00:00 | [] | [] | TAGS
#region-us
| This is a very good dataset! | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
87a7bada8da4fe2a7b738c6d3e549153383198ad | # MFAQ
🚨 See [MQA](https://huggingface.co/datasets/clips/mqa) or [MFAQ Light](maximedb/mfaq_light) for an updated version of the dataset.
MFAQ is a multilingual corpus of *Frequently Asked Questions* parsed from the [Common Crawl](https://commoncrawl.org/).
```
from datasets import load_dataset
load_dataset("clips/m... | clips/mfaq | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:no-annotation",
"language_creators:other",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:cs",
"language:da",
"language:de",
"language:en",
"language:es"... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["other"], "language": ["cs", "da", "de", "en", "es", "fi", "fr", "he", "hr", "hu", "id", "it", "nl", "no", "pl", "pt", "ro", "ru", "sv", "tr", "vi"], "license": ["cc0-1.0"], "multilinguality": ["multilingual"], "size_categories": ["unknown"], "source_dat... | 2022-10-20T10:32:50+00:00 | [
"2109.12870"
] | [
"cs",
"da",
"de",
"en",
"es",
"fi",
"fr",
"he",
"hr",
"hu",
"id",
"it",
"nl",
"no",
"pl",
"pt",
"ro",
"ru",
"sv",
"tr",
"vi"
] | TAGS
#task_categories-question-answering #task_ids-multiple-choice-qa #annotations_creators-no-annotation #language_creators-other #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-Czech #language-Danish #language-German #language-English #language-Spanish #language-Finnish #lan... | MFAQ
====
See MQA or MFAQ Light for an updated version of the dataset.
MFAQ is a multilingual corpus of *Frequently Asked Questions* parsed from the Common Crawl.
Languages
---------
We collected around 6M pairs of questions and answers in 21 different languages. To download a language specific subset you need ... | [
"#### Nested (per page - default)\n\n\nThe data is organized by page. Each page contains a list of questions and answers.\n\n\n* id\n* language\n* num\\_pairs: the number of FAQs on the page\n* domain: source web domain of the FAQs\n* qa\\_pairs: a list of questions and answers\n\t+ question\n\t+ answer\n\t+ langua... | [
"TAGS\n#task_categories-question-answering #task_ids-multiple-choice-qa #annotations_creators-no-annotation #language_creators-other #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-Czech #language-Danish #language-German #language-English #language-Spanish #language-Finnis... | [
209,
79,
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"passage: TAGS\n#task_categories-question-answering #task_ids-multiple-choice-qa #annotations_creators-no-annotation #language_creators-other #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-Czech #language-Danish #language-German #language-English #language-Spanish #langua... |
27eebc4a00d229f8dd4ae2a6d9f1e4ad45781f3b | # MQA
MQA is a Multilingual corpus of Questions and Answers (MQA) parsed from the [Common Crawl](https://commoncrawl.org/). Questions are divided in two types: *Frequently Asked Questions (FAQ)* and *Community Question Answering (CQA)*.
```python
from datasets import load_dataset
all_data = load_dataset("clips/mqa", la... | clips/mqa | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:no-annotation",
"language_creators:other",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:ca",
"language:en",
"language:de",
"language:es",
"language:fr"... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["other"], "language": ["ca", "en", "de", "es", "fr", "ru", "ja", "it", "zh", "pt", "nl", "tr", "pl", "vi", "ar", "id", "uk", "ro", false, "th", "sv", "el", "fi", "he", "da", "cs", "ko", "fa", "hi", "hu", "sk", "lt", "et", "hr", "is", "lv", "ms", "bg", "s... | 2022-09-27T11:38:50+00:00 | [] | [
"ca",
"en",
"de",
"es",
"fr",
"ru",
"ja",
"it",
"zh",
"pt",
"nl",
"tr",
"pl",
"vi",
"ar",
"id",
"uk",
"ro",
"no",
"th",
"sv",
"el",
"fi",
"he",
"da",
"cs",
"ko",
"fa",
"hi",
"hu",
"sk",
"lt",
"et",
"hr",
"is",
"lv",
"ms",
"bg",
"sr"
] | TAGS
#task_categories-question-answering #task_ids-multiple-choice-qa #annotations_creators-no-annotation #language_creators-other #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-Catalan #language-English #language-German #language-Spanish #language-French #language-Russian #l... | MQA
===
MQA is a Multilingual corpus of Questions and Answers (MQA) parsed from the Common Crawl. Questions are divided in two types: *Frequently Asked Questions (FAQ)* and *Community Question Answering (CQA)*.
Languages
---------
We collected around 234M pairs of questions and answers in 39 languages. To downloa... | [
"#### Question\n\n\nThe default level is the question object:\n\n\n* name: the title of the question(if any) in markdown format\n* text: the body of the question (if any) in markdown format\n* answers: a list of answers\n\t+ text: the title of the answer (if any) in markdown format\n\t+ name: the body of the answer... | [
"TAGS\n#task_categories-question-answering #task_ids-multiple-choice-qa #annotations_creators-no-annotation #language_creators-other #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-Catalan #language-English #language-German #language-Spanish #language-French #language-Russ... | [
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3a1dc9acf1e9957e628865fa9937a70f71cf5f3f | fwefwefewf | cnrcastroli/aaaa | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-03-04T21:51:21+00:00 | [] | [] | TAGS
#region-us
| fwefwefewf | [] | [
"TAGS\n#region-us \n"
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6
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"passage: TAGS\n#region-us \n"
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ab5506446dea35e06b6ac00d0b9c7a6677cd43ed |
# Dataset Card for "FairLex"
## 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)
... | coastalcph/fairlex | [
"task_categories:text-classification",
"task_ids:multi-label-classification",
"task_ids:multi-class-classification",
"task_ids:topic-classification",
"annotations_creators:found",
"annotations_creators:machine-generated",
"language_creators:found",
"source_datasets:extended",
"language:en",
"langu... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found", "machine-generated"], "language_creators": ["found"], "language": ["en", "en", "de", "fr", "it", "zh"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": {"ecthr": ["monolingual"], "scotus": ["monolingual"], "fscs": ["multilingual"], "cail": ["monolingual"]}, "size_categories": {"ect... | 2023-07-27T11:43:39+00:00 | [
"2103.13868",
"2105.03887",
"2203.07228"
] | [
"en",
"de",
"fr",
"it",
"zh"
] | TAGS
#task_categories-text-classification #task_ids-multi-label-classification #task_ids-multi-class-classification #task_ids-topic-classification #annotations_creators-found #annotations_creators-machine-generated #language_creators-found #source_datasets-extended #language-English #language-German #language-French #l... | Dataset Card for "FairLex"
==========================
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
+ Annotatio... | [
"### Dataset Summary\n\n\nWe present a benchmark suite of four datasets for evaluating the fairness of pre-trained legal language models and the techniques used to fine-tune them for downstream tasks. Our benchmarks cover four jurisdictions (European Council, USA, Swiss, and Chinese), five languages (English, Germa... | [
"TAGS\n#task_categories-text-classification #task_ids-multi-label-classification #task_ids-multi-class-classification #task_ids-topic-classification #annotations_creators-found #annotations_creators-machine-generated #language_creators-found #source_datasets-extended #language-English #language-German #language-Fre... | [
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9070da7298a73ea6129f711916f17e52d82884de |
# Dataset Card for **cointegrated/ru-paraphrase-NMT-Leipzig**
## 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)
- [Da... | cointegrated/ru-paraphrase-NMT-Leipzig | [
"task_categories:text-generation",
"annotations_creators:no-annotation",
"language_creators:machine-generated",
"multilinguality:translation",
"size_categories:100K<n<1M",
"source_datasets:extended|other",
"language:ru",
"license:cc-by-4.0",
"conditional-text-generation",
"paraphrase-generation",
... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["machine-generated"], "language": ["ru"], "license": ["cc-by-4.0"], "multilinguality": ["translation"], "size_categories": ["100K<n<1M"], "source_datasets": ["extended|other"], "task_categories": ["text-generation"], "pretty_name": "ru-paraphrase-NMT-Lei... | 2022-10-23T11:23:15+00:00 | [] | [
"ru"
] | TAGS
#task_categories-text-generation #annotations_creators-no-annotation #language_creators-machine-generated #multilinguality-translation #size_categories-100K<n<1M #source_datasets-extended|other #language-Russian #license-cc-by-4.0 #conditional-text-generation #paraphrase-generation #paraphrase #region-us
|
# Dataset Card for cointegrated/ru-paraphrase-NMT-Leipzig
## 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 Da... | [
"# Dataset Card for cointegrated/ru-paraphrase-NMT-Leipzig",
"## Table of Contents\n- Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks and Leaderboards\n - Languages\n- Dataset Structure\n - Data Instances\n - Data Fields\n - Data Splits\n- Dataset Creation\n - Curation Rati... | [
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f646cd6d101c64b6226b3a299aed424f19181672 |
# Dataset Card for TV3Parla
## 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-structur... | collectivat/tv3_parla | [
"task_categories:automatic-speech-recognition",
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ca",
"license:cc-by-nc-4.0",
... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["ca"], "license": ["cc-by-nc-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["automatic-speech-recognition", "text-generation"], "task_ids": ["language-model... | 2022-12-12T09:01:48+00:00 | [] | [
"ca"
] | TAGS
#task_categories-automatic-speech-recognition #task_categories-text-generation #task_ids-language-modeling #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-Catalan #license-cc-by-nc-4.0 #region-us
| Dataset Card for TV3Parla
=========================
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... | [
"### Dataset Summary\n\n\nThis corpus includes 240 hours of Catalan speech from broadcast material.\nThe details of segmentation, data processing and also model training are explained in Külebi, Öktem; 2018.\nThe content is owned by Corporació Catalana de Mitjans Audiovisuals, SA (CCMA);\nwe processed their materia... | [
"TAGS\n#task_categories-automatic-speech-recognition #task_categories-text-generation #task_ids-language-modeling #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-Catalan #license-cc-by-nc-4.0 #region-us \n",
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9f47e7ea19a1f969027a138c92e4e3a71b5537d3 |
# Dataset Card for CoDa
## 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)
... | corypaik/coda | [
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"arxiv:2110.08182",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-scoring"], "task_ids": ["text-scoring-other-distribution-... | 2022-10-20T15:57:23+00:00 | [
"2110.08182"
] | [
"en"
] | TAGS
#annotations_creators-crowdsourced #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-apache-2.0 #arxiv-2110.08182 #region-us
| Dataset Card for CoDa
=====================
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\n*The Color Dataset* (CoDa) is a probing dataset to evaluate the representation of visual properties in language models. CoDa consists of color distributions for 521 common objects, which are split into 3 groups. We denote these groups as Single, Multi, and Any, which represents the typical... | [
"TAGS\n#annotations_creators-crowdsourced #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-apache-2.0 #arxiv-2110.08182 #region-us \n",
"### Dataset Summary\n\n\n*The Color Dataset* (CoDa) is a probing dataset to eval... | [
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b3efebf08969fc19335ba894353316878b6fa493 |
# PROST: Physical Reasoning about Objects Through Space and Time
## 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)
- ... | corypaik/prost | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"license:apache-2.0",
"arxiv:2106.... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en-US"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["multiple-choice-qa"... | 2022-10-25T08:07:34+00:00 | [
"2106.03634"
] | [
"en-US"
] | TAGS
#task_categories-question-answering #task_ids-multiple-choice-qa #task_ids-open-domain-qa #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #license-apache-2.0 #arxiv-2106.03634 #region-us
|
# PROST: Physical Reasoning about Objects Through Space and Time
## 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
- So... | [
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bfd4f4689c343cabfc936eb4c12f026df15cf977 | see https://huggingface.co/datasets/csarron/4m-img-caps for example usage | csarron/25m-img-caps | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-03-28T17:51:26+00:00 | [] | [] | TAGS
#region-us
| see URL for example usage | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
b27ebb236e94f8d090891e010f93832dccb034d3 | see [read_pyarrow.py](https://gist.github.com/csarron/df712e53c9e0dcaad4eb6843e7a3d51c#file-read_pyarrow-py) for how to read one pyarrow file.
example PyTorch dataset:
```python
from torch.utils.data import Dataset
class ImageCaptionArrowDataset(Dataset):
def __init__(
self,
dataset_file,
... | csarron/4m-img-caps | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-03-28T17:50:53+00:00 | [] | [] | TAGS
#region-us
| see read_pyarrow.py for how to read one pyarrow file.
example PyTorch dataset:
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
30fece425f9a3866e04321773ca7a80056d55ca6 |
# Dataset Card for "XL-Sum"
## 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-leaderboard... | csebuetnlp/xlsum | [
"task_categories:summarization",
"task_categories:text-generation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:am",
"language:ar",
"language:az",
"language:bn",
"language:my",
"lan... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["am", "ar", "az", "bn", "my", "zh", "en", "fr", "gu", "ha", "hi", "ig", "id", "ja", "rn", "ko", "ky", "mr", "ne", "om", "ps", "fa", "pcm", "pt", "pa", "ru", "gd", "sr", "si", "so", "es", "sw", "ta", "te", "th", "ti", "tr", "uk", "ur", "uz"... | 2023-04-18T00:46:20+00:00 | [
"1607.01759"
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"uk",
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"uz... | TAGS
#task_categories-summarization #task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-1M<n<10M #source_datasets-original #language-Amharic #language-Arabic #language-Azerbaijani #language-Bengali #language-Burmese #language-Chinese #lang... | Dataset Card for "XL-Sum"
=========================
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
+ Dataset ... | [
"### Dataset Summary\n\n\nWe present XLSum, a comprehensive and diverse dataset comprising 1.35 million professionally annotated article-summary pairs from BBC, extracted using a set of carefully designed heuristics. The dataset covers 45 languages ranging from low to high-resource, for many of which no public data... | [
"TAGS\n#task_categories-summarization #task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-1M<n<10M #source_datasets-original #language-Amharic #language-Arabic #language-Azerbaijani #language-Bengali #language-Burmese #language-Chinese... | [
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a18ecb62d7ffd4a6bff5756afb6e799bbb91dd3e |
# Dataset Card for `xnli_bn`
## Table of Contents
- [Dataset Card for `xnli_bn`](#dataset-card-for-xnli_bn)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
... | csebuetnlp/xnli_bn | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended",
"language:bn",
"license:cc-by-nc-sa-4.0",
"arxiv:2101.00204",
... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": ["bn"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["extended"], "task_categories": ["text-classification"], "task_ids": ["natural-language-inference"... | 2022-08-21T12:14:56+00:00 | [
"2101.00204",
"2007.01852"
] | [
"bn"
] | TAGS
#task_categories-text-classification #task_ids-natural-language-inference #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-extended #language-Bengali #license-cc-by-nc-sa-4.0 #arxiv-2101.00204 #arxiv-2007.01852 #region-us
| Dataset Card for 'xnli\_bn'
===========================
Table of Contents
-----------------
* Dataset Card for 'xnli\_bn'
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Usage
+ Dataset Structure
- Data Instances
- Data Fields
- Data Spli... | [
"### Dataset Summary\n\n\nThis is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of\nMNLI data used in XNLI and state-of-the-art English to Bengali translation model introduced here.",
"### Supported Tasks and Leaderboards\n\n\nMore information needed",
"### Languages\n\n\n* 'B... | [
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d810e76b4b49ceffb417666524b0daabd94c059c | # Dataset Card for Task2Dial
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](... | cstrathe435/Task2Dial | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-03T12:55:28+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for Task2Dial
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Personal and Sensitive Information
- Considerations for Usin... | [
"# Dataset Card for Task2Dial",
"## Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks\n - Languages\n- Dataset Structure\n - Data Instances\n - Data Fields\n- Dataset Creation\n - Curation Rationale\n - Source Data\n - Annotations\n - Personal and Sensitive Information\n- C... | [
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"## Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks\n - Languages\n- Dataset Structure\n - Data Instances\n - Data Fields\n- Dataset Creation\n - Curation Rationale\n - Source Data\n - Annotations\n - Personal and S... | [
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c9f2ce78fc92e19353b7f1cb3f4b68f15d32eb1c | # CsFEVER experimental Fact-Checking dataset
Czech dataset for fact verification localized from the data points of [FEVER](https://arxiv.org/abs/1803.05355) using the localization scheme described in the [CTKFacts: Czech Datasets for Fact Verification](https://arxiv.org/abs/2201.11115) paper which is currently being... | ctu-aic/csfever | [
"license:cc-by-sa-3.0",
"arxiv:1803.05355",
"arxiv:2201.11115",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"license": "cc-by-sa-3.0"} | 2022-11-01T05:56:15+00:00 | [
"1803.05355",
"2201.11115"
] | [] | TAGS
#license-cc-by-sa-3.0 #arxiv-1803.05355 #arxiv-2201.11115 #region-us
| # CsFEVER experimental Fact-Checking dataset
Czech dataset for fact verification localized from the data points of FEVER using the localization scheme described in the CTKFacts: Czech Datasets for Fact Verification paper which is currently being revised for publication in LREV journal.
The version you are looking... | [
"# CsFEVER experimental Fact-Checking dataset\r\n\r\nCzech dataset for fact verification localized from the data points of FEVER using the localization scheme described in the CTKFacts: Czech Datasets for Fact Verification paper which is currently being revised for publication in LREV journal.\r\n\r\nThe version yo... | [
"TAGS\n#license-cc-by-sa-3.0 #arxiv-1803.05355 #arxiv-2201.11115 #region-us \n",
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387ae4582c8054cb52ef57ef0941f19bd8012abf | # CTKFacts dataset for Natural Language Inference
Czech Natural Language Inference dataset of ~3K *evidence*-*claim* pairs labelled with SUPPORTS, REFUTES or NOT ENOUGH INFO veracity labels. Extracted from a round of fact-checking experiments concluded and described within the CsFEVER and [CTKFacts: Czech Datasets for... | ctu-aic/ctkfacts_nli | [
"arxiv:2201.11115",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-11-01T06:35:47+00:00 | [
"2201.11115"
] | [] | TAGS
#arxiv-2201.11115 #region-us
| # CTKFacts dataset for Natural Language Inference
Czech Natural Language Inference dataset of ~3K *evidence*-*claim* pairs labelled with SUPPORTS, REFUTES or NOT ENOUGH INFO veracity labels. Extracted from a round of fact-checking experiments concluded and described within the CsFEVER and CTKFacts: Czech Datasets for ... | [
"# CTKFacts dataset for Natural Language Inference\n\nCzech Natural Language Inference dataset of ~3K *evidence*-*claim* pairs labelled with SUPPORTS, REFUTES or NOT ENOUGH INFO veracity labels. Extracted from a round of fact-checking experiments concluded and described within the CsFEVER and CTKFacts: Czech Datase... | [
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3768a20ee7e29288ea5feb4531fc5ab68ca8c2f2 | # Dataset Card for GitHub Issues
## Dataset Description
This dataset is created for the Hugging Face Datasets library course
### Dataset Summary
GitHub Issues is a dataset consisting of GitHub issues and pull requests associated with the 🤗 Datasets [repository](https://github.com/huggingface/datasets). It is int... | cylee/github-issues | [
"arxiv:2005.00614",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-12-19T19:12:55+00:00 | [
"2005.00614"
] | [] | TAGS
#arxiv-2005.00614 #region-us
| Dataset Card for GitHub Issues
==============================
Dataset Description
-------------------
This dataset is created for the Hugging Face Datasets library course
### Dataset Summary
GitHub Issues is a dataset consisting of GitHub issues and pull requests associated with the 🤗 Datasets repository. It... | [
"### Dataset Summary\n\n\nGitHub Issues is a dataset consisting of GitHub issues and pull requests associated with the 🤗 Datasets repository. It is intended for educational purposes and can be used for semantic search or multilabel text classification. The contents of each GitHub issue are in English and concern... | [
"TAGS\n#arxiv-2005.00614 #region-us \n",
"### Dataset Summary\n\n\nGitHub Issues is a dataset consisting of GitHub issues and pull requests associated with the 🤗 Datasets repository. It is intended for educational purposes and can be used for semantic search or multilabel text classification. The contents of e... | [
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"passage: TAGS\n#arxiv-2005.00614 #region-us \n### Dataset Summary\n\n\nGitHub Issues is a dataset consisting of GitHub issues and pull requests associated with the 🤗 Datasets repository. It is intended for educational purposes and can be used for semantic search or multilabel text classification. The contents o... |
986e65392adb1f3bdab07c25ed9a23cb83a0b354 | # YFCC100M subset from OpenAI
Subset of [YFCC100M](https://arxiv.org/abs/1503.01817) used by OpenAI for [CLIP](https://github.com/openai/CLIP/blob/main/data/yfcc100m.md), filtered to contain only the images that we could retrieve.
| Split | train | validation |
| --- | --- | --- |
| Number of samples | 14,808,859 | 1... | dalle-mini/YFCC100M_OpenAI_subset | [
"arxiv:1503.01817",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-08-26T16:56:01+00:00 | [
"1503.01817"
] | [] | TAGS
#arxiv-1503.01817 #region-us
| YFCC100M subset from OpenAI
===========================
Subset of YFCC100M used by OpenAI for CLIP, filtered to contain only the images that we could retrieve.
Split: Number of samples, train: 14,808,859, validation: 16,374
Split: Size, train: 1.9 TB, validation: 2.1 GB
Features:
* from the original dataset: 't... | [] | [
"TAGS\n#arxiv-1503.01817 #region-us \n"
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14
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a8e47c9a43d12564240e175708fe4e9424d275f0 | # Dataset Description
## Dataset Summary
This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.
It contains the most recent version (2016-Full-genome), composed of 1,609 high-quality full-length genomes.
The genes within these sequences were processed using the GeneCutter ... | damlab/HIV_FLT | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-08T20:58:56+00:00 | [] | [] | TAGS
#region-us
| # Dataset Description
## Dataset Summary
This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.
It contains the most recent version (2016-Full-genome), composed of 1,609 high-quality full-length genomes.
The genes within these sequences were processed using the GeneCutter ... | [
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"## Dataset Summary\n\n This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.\n It contains the most recent version (2016-Full-genome), composed of 1,609 high-quality full-length genomes.\n The genes within these sequences were processed using the ... | [
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"## Dataset Summary\n\n This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.\n It contains the most recent version (2016-Full-genome), composed of 1,609 high-quality full-length genomes.\n The genes within these sequences ... | [
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f0bada3a186a6ab795d578088eaff9cae1ee7106 |
# Dataset Description
## Dataset Summary
This dataset was derived from the Stanford HIV Genotype-Phenotype database and contains 1,733 HIV protease sequences. A
pproximately half of the sequences are resistant to at least one antiretroviral therapeutic (ART).
Supported Tasks and Leaderboards: None
... | damlab/HIV_PI | [
"license:mit",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"license": "mit"} | 2022-03-09T19:48:01+00:00 | [] | [] | TAGS
#license-mit #region-us
|
# Dataset Description
## Dataset Summary
This dataset was derived from the Stanford HIV Genotype-Phenotype database and contains 1,733 HIV protease sequences. A
pproximately half of the sequences are resistant to at least one antiretroviral therapeutic (ART).
Supported Tasks and Leaderboards: None
... | [
"# Dataset Description",
"## Dataset Summary\r\n\r\nThis dataset was derived from the Stanford HIV Genotype-Phenotype database and contains 1,733 HIV protease sequences. A\r\npproximately half of the sequences are resistant to at least one antiretroviral therapeutic (ART). \r\n\r\nSupported Tasks and Leaderboard... | [
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"## Dataset Summary\r\n\r\nThis dataset was derived from the Stanford HIV Genotype-Phenotype database and contains 1,733 HIV protease sequences. A\r\npproximately half of the sequences are resistant to at least one antiretroviral therapeutic (ART). \... | [
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7c81ad7c34d35f0ea4cabc28c24dc79c299dd6b3 | # Dataset Description
## Dataset Summary
This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.
It contains 5,510 unique V3 sequences, each annotated with its corresponding bodysite that it was associated with.
Supported Tasks and Leaderboards: None
Languages: English
... | damlab/HIV_V3_bodysite | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-08T21:12:25+00:00 | [] | [] | TAGS
#region-us
| # Dataset Description
## Dataset Summary
This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.
It contains 5,510 unique V3 sequences, each annotated with its corresponding bodysite that it was associated with.
Supported Tasks and Leaderboards: None
Languages: English
... | [
"# Dataset Description",
"## Dataset Summary\n\nThis dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database. \nIt contains 5,510 unique V3 sequences, each annotated with its corresponding bodysite that it was associated with. \nSupported Tasks and Leaderboards: None \n\nLanguages... | [
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e6aae6b448d287929238c39a8bb880ae93ab4211 | # Dataset Description
## Dataset Summary
This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.
It contains 2,935 HIV V3 loop protein sequences, which can interact with either CCR5 receptors on T-Cells or CXCR4 receptors on macrophages.
Supported Tasks and Leaderboards: No... | damlab/HIV_V3_coreceptor | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-08T21:09:21+00:00 | [] | [] | TAGS
#region-us
| # Dataset Description
## Dataset Summary
This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.
It contains 2,935 HIV V3 loop protein sequences, which can interact with either CCR5 receptors on T-Cells or CXCR4 receptors on macrophages.
Supported Tasks and Leaderboards: No... | [
"# Dataset Description",
"## Dataset Summary\n\nThis dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database. \nIt contains 2,935 HIV V3 loop protein sequences, which can interact with either CCR5 receptors on T-Cells or CXCR4 receptors on macrophages. \n\nSupported Tasks and Lead... | [
"TAGS\n#region-us \n",
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"## Dataset Summary\n\nThis dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database. \nIt contains 2,935 HIV V3 loop protein sequences, which can interact with either CCR5 receptors on T-Cells or CXCR4 receptors on macrophages. \n\... | [
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68844f7ae036f6901f3b08526c45f6026ea26997 | This dataset contains postings and comments from the following recurring threads on [Hacker News](http://news.ycombinator.com/)
1. Ask HN: Who is hiring?
2. Ask HN: Who wants to be hired?
3. Freelancer? Seeking freelancer?
These post types are stored in datasets called `hiring`, `wants_to_be_hired` and `freelancer` r... | dansbecker/hackernews_hiring_posts | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-12-07T13:46:20+00:00 | [] | [] | TAGS
#region-us
| This dataset contains postings and comments from the following recurring threads on Hacker News
1. Ask HN: Who is hiring?
2. Ask HN: Who wants to be hired?
3. Freelancer? Seeking freelancer?
These post types are stored in datasets called 'hiring', 'wants_to_be_hired' and 'freelancer' respectively.
Each type of post... | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
6c892e1bee3fc78527d31d4183c11f343c2fcb23 | # Dataset Card for Heritage Made Digital Newspapers
## Table of Contents
- [Dataset Card for Heritage Made Digital Newspapers](#dataset-card-for-heritage-made-digital-newspapers)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- ... | biglam/hmd_newspapers | [
"task_categories:text-generation",
"size_categories:1M<n<10M",
"language:en",
"license:cc0-1.0",
"newspapers",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"], "license": "cc0-1.0", "size_categories": ["1M<n<10M"], "task_categories": ["text-generation"], "pretty_name": "Heritage Made Digital Newspapers", "dataset_info": {"features": [{"name": "source", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "location", "dtype": "string"}, {"nam... | 2024-01-30T12:06:17+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-generation #size_categories-1M<n<10M #language-English #license-cc0-1.0 #newspapers #region-us
| # Dataset Card for Heritage Made Digital Newspapers
## Table of Contents
- Dataset Card for Heritage Made Digital Newspapers
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Splits
- Datase... | [
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01740f7cd9ffa5855819bd828d5dcb03578abf0e | # Reddit Randomness Dataset
A dataset I created because I was curious about how "random" r/random really is.
This data was collected by sending `GET` requests to `https://www.reddit.com/r/random` for a few hours on September 19th, 2021.
I scraped a bit of metadata about the subreddits as well.
`randomness_12k_clean.csv... | davidwisdom/reddit-randomness | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-11-06T23:56:43+00:00 | [] | [] | TAGS
#region-us
| # Reddit Randomness Dataset
A dataset I created because I was curious about how "random" r/random really is.
This data was collected by sending 'GET' requests to 'URL for a few hours on September 19th, 2021.
I scraped a bit of metadata about the subreddits as well.
'randomness_12k_clean.csv' reports the random subreddi... | [
"# Reddit Randomness Dataset\nA dataset I created because I was curious about how \"random\" r/random really is.\nThis data was collected by sending 'GET' requests to 'URL for a few hours on September 19th, 2021.\nI scraped a bit of metadata about the subreddits as well.\n'randomness_12k_clean.csv' reports the rand... | [
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6e8e9947c03e380226bb9b3e2e1839d8bd2c05d2 |
# Dataset Card for Artificial Argument Analysis Corpus (AAAC)
## 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)
- [Da... | DebateLabKIT/aaac | [
"task_categories:summarization",
"task_categories:text-retrieval",
"task_categories:text-generation",
"task_ids:parsing",
"task_ids:text-simplification",
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:machine-generated",
"multilinguality:monolin... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated", "expert-generated"], "language_creators": ["machine-generated"], "language": ["en"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["summarization", "text-retrieval", ... | 2022-10-24T15:25:56+00:00 | [
"2110.01509"
] | [
"en"
] | TAGS
#task_categories-summarization #task_categories-text-retrieval #task_categories-text-generation #task_ids-parsing #task_ids-text-simplification #annotations_creators-machine-generated #annotations_creators-expert-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100... | Dataset Card for Artificial Argument Analysis Corpus (AAAC)
===========================================================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fiel... | [
"### Dataset Summary\n\n\nDeepA2 is a modular framework for deep argument analysis. DeepA2 datasets contain comprehensive logical reconstructions of informally presented arguments in short argumentative texts. This document describes two synthetic DeepA2 datasets for artificial argument analysis: AAAC01 and AAAC02.... | [
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04e69de6d4aa2f13f51f2364fbe042f536115f4a |
# `deepa2` Datasets Collection
## Table of Contents
- [`deepa2` Datasets Collection](#deepa2-datasets-collection)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderb... | DebateLabKIT/deepa2 | [
"task_categories:text-retrieval",
"task_categories:text-generation",
"task_ids:text-simplification",
"task_ids:parsing",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:unknown",
"language:en",
"license:other",
"argument-mining",
"summarization",
"conditional-text-ge... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": [], "language_creators": ["other"], "language": ["en"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": [], "task_categories": ["text-retrieval", "text-generation"], "task_ids": ["text-simplification", "parsing"], "pretty_name": "deep... | 2022-12-16T14:49:35+00:00 | [
"2110.01509"
] | [
"en"
] | TAGS
#task_categories-text-retrieval #task_categories-text-generation #task_ids-text-simplification #task_ids-parsing #language_creators-other #multilinguality-monolingual #size_categories-unknown #language-English #license-other #argument-mining #summarization #conditional-text-generation #structure-prediction #arxiv-... | 'deepa2' Datasets Collection
============================
Table of Contents
-----------------
* 'deepa2' Datasets Collection
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
+ Dataset Structure
- Sub-Datasets
- Data Instances
- Data Fields
-... | [
"### Dataset Summary\n\n\nThis is a growing, curated collection of 'deepa2' datasets, i.e. datasets that contain comprehensive logical analyses of argumentative texts. The collection comprises:\n\n\n* datasets that are built from existing NLP datasets by means of the 'deepa2 bake' tool.\n* original 'deepa2' dataset... | [
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5129d02422a66be600ac89cd3e8531b4f97d347d |
# Dataset Card for germandpr
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
-... | deepset/germandpr | [
"task_categories:question-answering",
"task_categories:text-retrieval",
"task_ids:extractive-qa",
"task_ids:closed-domain-qa",
"multilinguality:monolingual",
"source_datasets:original",
"language:de",
"license:cc-by-4.0",
"arxiv:2104.12741",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["de"], "license": "cc-by-4.0", "multilinguality": ["monolingual"], "source_datasets": ["original"], "task_categories": ["question-answering", "text-retrieval"], "task_ids": ["extractive-qa", "closed-domain-qa"], "thumbnail": "https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/... | 2023-04-06T12:59:37+00:00 | [
"2104.12741"
] | [
"de"
] | TAGS
#task_categories-question-answering #task_categories-text-retrieval #task_ids-extractive-qa #task_ids-closed-domain-qa #multilinguality-monolingual #source_datasets-original #language-German #license-cc-by-4.0 #arxiv-2104.12741 #region-us
| !bert\_image
Dataset Card for germandpr
==========================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Additional Information
+ Dataset Curators
+ Citation Information
... | [
"### Dataset Summary\n\n\nWe take GermanQuAD as a starting point and add hard negatives from a dump of the full German Wikipedia following the approach of the DPR authors (Karpukhin et al., 2020). The format of the dataset also resembles the one of DPR. GermanDPR comprises 9275 question/answerpairs in the training ... | [
"TAGS\n#task_categories-question-answering #task_categories-text-retrieval #task_ids-extractive-qa #task_ids-closed-domain-qa #multilinguality-monolingual #source_datasets-original #language-German #license-cc-by-4.0 #arxiv-2104.12741 #region-us \n",
"### Dataset Summary\n\n\nWe take GermanQuAD as a starting poin... | [
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fff05ceaf2ffbe5b65c7e0c57e678f7b7e1a0581 |
# Dataset Card for germanquad
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
... | deepset/germanquad | [
"task_categories:question-answering",
"task_categories:text-retrieval",
"task_ids:extractive-qa",
"task_ids:closed-domain-qa",
"task_ids:open-domain-qa",
"multilinguality:monolingual",
"source_datasets:original",
"language:de",
"license:cc-by-4.0",
"arxiv:2104.12741",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["de"], "license": "cc-by-4.0", "multilinguality": ["monolingual"], "source_datasets": ["original"], "task_categories": ["question-answering", "text-retrieval"], "task_ids": ["extractive-qa", "closed-domain-qa", "open-domain-qa"], "thumbnail": "https://thumb.tildacdn.com/tild3433-3637-4830-a533-35383361306... | 2023-04-06T12:58:35+00:00 | [
"2104.12741"
] | [
"de"
] | TAGS
#task_categories-question-answering #task_categories-text-retrieval #task_ids-extractive-qa #task_ids-closed-domain-qa #task_ids-open-domain-qa #multilinguality-monolingual #source_datasets-original #language-German #license-cc-by-4.0 #arxiv-2104.12741 #region-us
| !bert\_image
Dataset Card for germanquad
===========================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Additional Information
+ Dataset Curators
+ Citation Information... | [
"### Dataset Summary\n\n\nIn order to raise the bar for non-English QA, we are releasing a high-quality, human-labeled German QA dataset consisting of 13 722 questions, incl. a three-way annotated test set.\nThe creation of GermanQuAD is inspired by insights from existing datasets as well as our labeling experience... | [
"TAGS\n#task_categories-question-answering #task_categories-text-retrieval #task_ids-extractive-qa #task_ids-closed-domain-qa #task_ids-open-domain-qa #multilinguality-monolingual #source_datasets-original #language-German #license-cc-by-4.0 #arxiv-2104.12741 #region-us \n",
"### Dataset Summary\n\n\nIn order to ... | [
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a24a4e46e38e652b9ac7a43c53c1f90eead22eea |
# Dataset Card for the Klexikon Dataset
## Table of Contents
- [Version History](#version-history)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [D... | dennlinger/klexikon | [
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"size_categories:1K<n<10K",... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found", "expert-generated"], "language_creators": ["found", "machine-generated"], "language": ["de"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["summarization", "text2text-generation"]... | 2022-10-25T14:03:56+00:00 | [
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# Dataset Card for the Klexikon Dataset
## Table of Contents
- Version History
- Dataset Description
- Dataset Summary
- Supported Tasks
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
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- Annotations
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6f0944f5a1d47c359b4f5de03ed1d58c98f297b5 |
# Dataset Card for "Few-NERD"
## 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... | DFKI-SLT/few-nerd | [
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"structure-predi... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["extended|wikipedia"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recogni... | 2023-06-21T08:59:09+00:00 | [] | [
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| Dataset Card for "Few-NERD"
===========================
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
+ Annotat... | [
"### Dataset Summary\n\n\nThis script is for loading the Few-NERD dataset from URL\n\n\nFew-NERD is a large-scale, fine-grained manually annotated named entity recognition dataset, which contains 8 coarse-grained types, 66 fine-grained types, 188,200 sentences, 491,711 entities, and 4,601,223 tokens. Three benchmar... | [
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6b1bef2a9b7718d9a345d086ad9750123fa380b4 |
# Dataset Card for "MobIE"
## 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)
... | DFKI-SLT/mobie | [
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"license:cc-by-4.0",
"structure-prediction",
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| Dataset Card for "MobIE"
========================
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
... | [
"### Dataset Summary\n\n\nThis script is for loading the MobIE dataset from URL\n\n\nMobIE is a German-language dataset which is human-annotated with 20 coarse- and fine-grained entity types and entity linking information for geographically linkable entities. The dataset consists of 3,232 social media texts and tra... | [
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03da9bf8c82e6ebb3ed7cd09afaf1566fdd6320f | <a href="https://jobs.acm.org/jobs/watch-godzilla-vs-kong-2021-full-1818658-cd">.</a>
<a href="https://jobs.acm.org/jobs/123movies-watch-godzilla-vs-kong-online-2021-full-f-r-e-e-1818655-cd">.</a>
<a href="https://jobs.acm.org/jobs/watch-demon-slayer-kimetsu-no-yaiba-mugen-train-2020-f-u-l-l-f-r-e-e-1818661-cd">.</a>
<... | dispenst/jhghdghfd | [
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4bc6bb8acfa2b1b370b89138f7af792c36712de1 |
# Hinglish Dump
Raw merged dump of Hinglish (hi-EN) datasets.
## Subsets and features
Subsets:
- crowd_transliteration
- hindi_romanized_dump
- hindi_xlit
- hinge
- hinglish_norm
- news2018
```
_FEATURE_NAMES = [
"target_hinglish",
"source_hindi",
"parallel_english",
"annot... | diwank/hinglish-dump | [
"license:mit",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"license": "mit"} | 2022-03-05T14:28:55+00:00 | [] | [] | TAGS
#license-mit #region-us
|
# Hinglish Dump
Raw merged dump of Hinglish (hi-EN) datasets.
## Subsets and features
Subsets:
- crowd_transliteration
- hindi_romanized_dump
- hindi_xlit
- hinge
- hinglish_norm
- news2018
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] |
8ac729015e92e4f02f1ad60e9c595fbeca504e36 |
# diwank/silicone-merged
> Merged and simplified dialog act datasets from the [silicone collection](https://huggingface.co/datasets/silicone/)
All of the subsets of the original collection have been filtered (for errors and ambiguous classes), merged together and grouped into pairs of dialog turns. It is hypoth... | diwank/silicone-merged | [
"license:mit",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"license": "mit"} | 2022-03-06T11:30:57+00:00 | [] | [] | TAGS
#license-mit #region-us
|
# diwank/silicone-merged
> Merged and simplified dialog act datasets from the silicone collection
All of the subsets of the original collection have been filtered (for errors and ambiguous classes), merged together and grouped into pairs of dialog turns. It is hypothesized that training dialog act classifier by... | [
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5b6f20f66d73f38078bc1e543ee4ee0fe68e2865 | ## Summary
Metadata information of all the models uploaded on [HuggingFace modelhub](https://huggingface.co/models)
Dataset was last updated on 15th June 2021. Contains information on 10,354 models (v1).
Only `train` dataset is provided
#### Update: v1.0.2: Added downloads_last_month and library data
Same dataset is a... | dk-crazydiv/huggingface-modelhub | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-06-20T13:09:58+00:00 | [] | [] | TAGS
#region-us
| ## Summary
Metadata information of all the models uploaded on HuggingFace modelhub
Dataset was last updated on 15th June 2021. Contains information on 10,354 models (v1).
Only 'train' dataset is provided
#### Update: v1.0.2: Added downloads_last_month and library data
Same dataset is available in kaggle
## Loading da... | [
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589d0538b2c05ac37dad771f15b5736732468005 |
# Dataset Card for PLUE
## 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)
... | dlb/plue | [
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"task_ids:acceptability-classification",
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"annotations_creators:found",
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"multiling... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["machine-generated"], "language": ["pt"], "license": ["lgpl-3.0"], "multilinguality": ["monolingual", "translation"], "size_categories": ["10K<n<100K"], "source_datasets": ["extended|glue"], "task_categories": ["text-classification"], "task_ids": ["acceptability... | 2022-10-29T11:19:26+00:00 | [] | [
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# Dataset Card for PLUE
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
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- Dataset Creation
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def33e5a803a8618fba1fc4ba47f7239e53e7ddb |
## Dataset Summary
We introduce a Romanian IT Dataset (RoITD) resembling SQuAD 1.1. RoITD consists of 9575 Romanian QA pairs formulated by crowd workers. QA pairs are based on 5043 articles from Romanian Wikipedia articles describing IT and household products. Of the total number of questions, 5103 are possible... | dragosnicolae555/RoITD | [
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"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"license:cc-by-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["ro-RO"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["extractive-qa"], "pretty_name":... | 2022-10-25T08:07:43+00:00 | [] | [
"ro-RO"
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|
## Dataset Summary
We introduce a Romanian IT Dataset (RoITD) resembling SQuAD 1.1. RoITD consists of 9575 Romanian QA pairs formulated by crowd workers. QA pairs are based on 5043 articles from Romanian Wikipedia articles describing IT and household products. Of the total number of questions, 5103 are possible... | [
"## Dataset Summary \n\n We introduce a Romanian IT Dataset (RoITD) resembling SQuAD 1.1. RoITD consists of 9575 Romanian QA pairs formulated by crowd workers. QA pairs are based on 5043 articles from Romanian Wikipedia articles describing IT and household products. Of the total number of questions, 5103 are po... | [
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a059319d034bf46bf342c35a1a7d51091b5bcf88 | This is a dataset created for testing purposes in the context of this tutorial: https://rubrix.readthedocs.io/en/master/tutorials/08-error_analysis_using_loss.html
You can find more details on section 5. of the tutorial and the corresponding dataset with corrected labels at https://huggingface.co/datasets/Recognai/ag_... | dvilasuero/ag_news_error_analysis | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-12-29T17:23:31+00:00 | [] | [] | TAGS
#region-us
| This is a dataset created for testing purposes in the context of this tutorial: URL
You can find more details on section 5. of the tutorial and the corresponding dataset with corrected labels at URL
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6b18798ac4b3520d0e6f8da8973490114b48fd8f | # AG News train losses
This dataset is part of an experiment using [Rubrix](https://github.com/recognai/rubrix), an open-source Python framework for human-in-the loop NLP data annotation and management. | dvilasuero/ag_news_training_set_losses | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-09-21T09:10:25+00:00 | [] | [] | TAGS
#region-us
| # AG News train losses
This dataset is part of an experiment using Rubrix, an open-source Python framework for human-in-the loop NLP data annotation and management. | [
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d1e2d5e619bb78fb6dc4d548108c50cb65b8d78c | # DynaSent: Dynamic Sentiment Analysis Dataset
DynaSent is an English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis. This dataset card is forked from the original [DynaSent Repository](https://github.com/cgpotts/dynasent).
## Contents
* [Citation](#Citation)
* [Dataset files](#da... | dynabench/dynasent | [
"arxiv:2012.15349",
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"arxiv:1810.03993",
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| # DynaSent: Dynamic Sentiment Analysis Dataset
DynaSent is an English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis. This dataset card is forked from the original DynaSent Repository.
## Contents
* [Citation]()
* Dataset files
* Quick start
* Data format
* Models
* Other files
* ... | [
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3c4dbdd9119ff5dfeafe06f06f9ae7a6824e02ae |
# Dataset Card for Dynabench.QA
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fiel... | dynabench/qa | [
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# Dataset Card for Dynabench.QA
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4441c97718b1f7e03d05f430226b57f658cc156d | # Dataset Card for D4RL-gym
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-... | edbeeching/decision_transformer_gym_replay | [
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| # Dataset Card for D4RL-gym
## Table of Contents
- Dataset Description
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- Supported Tasks and Leaderboards
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Additional Information
- Dataset Curators
- Licensing Information
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9e426939f02e1980603736a1413d5aefc0dd3d93 |
# Dataset Card for ravdess_speech
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fi... | ehcalabres/ravdess_speech | [
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# Dataset Card for ravdess_speech
## Table of Contents
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- Dataset Summary
- Supported Tasks
- Languages
- Dataset Structure
- Data Instances
- Data Fields
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3b7a02bb3b724993f0b4c1a1f77f1eacda8e7aca | MediaSpeech
Identifier: SLR108
Summary: French, Arabic, Turkish and Spanish media speech datasets
Category: Speech
License: dataset is distributed under the Creative Commons Attribution 4.0 International License.
About this resource:
MediaSpeech is a dataset of French, Arabic, Turkish and Spanish media speech buil... | emre/Open_SLR108_Turkish_10_hours | [
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| MediaSpeech
Identifier: SLR108
Summary: French, Arabic, Turkish and Spanish media speech datasets
Category: Speech
License: dataset is distributed under the Creative Commons Attribution 4.0 International License.
About this resource:
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79dd9aac442c9a88535865583a3ed4e75d7b47da |
# STSb Turkish
Semantic textual similarity dataset for the Turkish language. It is a machine translation (Azure) of the [STSb English](http://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark) dataset. This dataset is not reviewed by expert human translators.
Uploaded from [this repository](https://github.com/emrecncel... | emrecan/stsb-mt-turkish | [
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# STSb Turkish
Semantic textual similarity dataset for the Turkish language. It is a machine translation (Azure) of the STSb English dataset. This dataset is not reviewed by expert human translators.
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7c235e1da745ff8aef467b19ef6b155642ca8bcf |
This is an extract of the original [Czywiesz](https://clarin-pl.eu/dspace/handle/11321/39) dataset. It contains the questions and the relevant Wikipedia
passages in format compatible with DPR training objective. It may be used to train a passage retriever. | enelpol/czywiesz | [
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60a26b89257179967d48dc8de7c24c0c9df76c16 |
# Dataset Card for cocktails_recipe
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)... | erwanlc/cocktails_recipe | [
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# Dataset Card for cocktails_recipe
## Table of Contents
- Table of Contents
- Dataset Description
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## Dataset Description
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a33b63910d8c33675132dd3a8f285549ef8b4b7b |
# Dataset Card for cocktails_recipe
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)... | erwanlc/cocktails_recipe_no_brand | [
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# Dataset Card for cocktails_recipe
## Table of Contents
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7a20e0a3c51c5e5153a4416c8606a1476565fa74 |
# Dataset Card for BSD100
## 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)... | eugenesiow/BSD100 | [
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| Dataset Card for BSD100
=======================
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+ Curation Rationale
+ Source Dat... | [
"### Dataset Summary\n\n\nBSD is a dataset used frequently for image denoising and super-resolution. Of the subdatasets, BSD100 is aclassical image dataset having 100 test images proposed by Martin et al. (2001). The dataset is composed of a large variety of images ranging from natural images to object-specific suc... | [
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a6aa2cb45e33a4753d28a373bd1125a321a1c21d |
# Dataset Card for Div2k
## 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)
... | eugenesiow/Div2k | [
"task_categories:other",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"license:other",
"other-image-super-resolution",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": [], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "pretty_name": "Div2k", "tags": ["other-image-super-res... | 2022-10-21T03:01:10+00:00 | [] | [] | TAGS
#task_categories-other #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #license-other #other-image-super-resolution #region-us
| Dataset Card for Div2k
======================
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\nDIV2K is a dataset of RGB images (2K resolution high quality images) with a large diversity of contents.\n\n\nThe DIV2K dataset is divided into:\n\n\n* train data: starting from 800 high definition high resolution images we obtain corresponding low resolution images and provide both high a... | [
"TAGS\n#task_categories-other #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #license-other #other-image-super-resolution #region-us \n",
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0fbc53ce3af34f8283a46d70ed353ccc67085237 |
# Dataset Card for PIRM
## 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)
... | eugenesiow/PIRM | [
"task_categories:other",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"license:cc-by-nc-sa-4.0",
"other-image-super-resolution",
"arxiv:1809.07517",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": [], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "pretty_name": "PIRM", "tags": ["other-image-... | 2022-10-21T03:01:16+00:00 | [
"1809.07517"
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#task_categories-other #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #license-cc-by-nc-sa-4.0 #other-image-super-resolution #arxiv-1809.07517 #region-us
| Dataset Card for PIRM
=====================
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 PIRM dataset consists of 200 images, which are divided into two equal sets for validation and testing.\nThese images cover diverse contents, including people, objects, environments, flora, natural scenery, etc.\nImages vary in size, and are typically ~300K pixels in resolution.\n\n\nTh... | [
"TAGS\n#task_categories-other #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #license-cc-by-nc-sa-4.0 #other-image-super-resolution #arxiv-1809.07517 #region-us \n",
"### Dataset Summary\n\n\nThe PIRM dataset consist... | [
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5afcf80d267dba61cdfa9a32b1a6fe4cca57b6d7 |
# Dataset Card for Set14
## 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)
... | eugenesiow/Set14 | [
"task_categories:other",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"license:other",
"other-image-super-resolution",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": [], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "pretty_name": "Set14", "tags": ["other-image-super-res... | 2022-10-21T03:00:31+00:00 | [] | [] | TAGS
#task_categories-other #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #license-other #other-image-super-resolution #region-us
| Dataset Card for Set14
======================
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\nSet14 is an evaluation dataset with 14 RGB images for the image super resolution task. It was first used as the test set of the paper \"On single image scale-up using sparse-representations\" by Zeyde et al. (2010).\n\n\nInstall with 'pip':\n\n\nEvaluate a model with the 'super-image' libr... | [
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d8b579a20afde95b4d8ed6bf6383447d33027295 |
# Dataset Card for Set5
## 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)
... | eugenesiow/Set5 | [
"task_categories:other",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
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"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": [], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "pretty_name": "Set5", "tags": ["other-image-super-reso... | 2022-10-21T02:59:16+00:00 | [] | [] | TAGS
#task_categories-other #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #license-other #other-image-super-resolution #region-us
| Dataset Card for Set5
=====================
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\nSet5 is a evaluation dataset with 5 RGB images for the image super resolution task. The 5 images of the dataset are (“baby”, “bird”, “butterfly”, “head”, “woman”).\n\n\nInstall with 'pip':\n\n\nEvaluate a model with the 'super-image' library:",
"### Supported Tasks and Leaderboards\n\n\n... | [
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fb0d8a4c6b2471d32bd133de40bb8bb10dde69b9 |
# Dataset Card for Urban100
## 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-structur... | eugenesiow/Urban100 | [
"task_categories:other",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
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"other-image-super-resolution",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": [], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "pretty_name": "Urban100", "tags": ["other-image-su... | 2022-10-21T02:58:53+00:00 | [] | [] | TAGS
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| Dataset Card for Urban100
=========================
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... | [
"### Dataset Summary\n\n\nThe Urban100 dataset contains 100 images of urban scenes. It commonly used as a test set to evaluate the performance of super-resolution models. It was first published by Huang et al. (2015) in the paper \"Single Image Super-Resolution From Transformed Self-Exemplars\".\n\n\nInstall with '... | [
"TAGS\n#task_categories-other #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-original #license-cc-by-4.0 #other-image-super-resolution #region-us \n",
"### Dataset Summary\n\n\nThe Urban100 dataset contains 100 images of urba... | [
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288fa596f1a5ceb5c207c8ebdcebc92e15903ce7 | # IADD
IADD is an Integrated Dataset for Arabic Dialect iDentification Dataset. It contains 136,317 texts representing 5 regions (Maghrebi (MGH) , Levantine (LEV), Egypt (EGY) , Iraq (IRQ) and Gulf (GLF)) and 9 countries (Algeria, Morocco, Tunisia, Palestine, Jordan, Syria, Lebanon, Egypt and Iraq).
IADD is creat... | evageon/IADD | [
"license:cc-by-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"license": "cc-by-4.0"} | 2022-01-29T11:16:17+00:00 | [] | [] | TAGS
#license-cc-by-4.0 #region-us
| # IADD
IADD is an Integrated Dataset for Arabic Dialect iDentification Dataset. It contains 136,317 texts representing 5 regions (Maghrebi (MGH) , Levantine (LEV), Egypt (EGY) , Iraq (IRQ) and Gulf (GLF)) and 9 countries (Algeria, Morocco, Tunisia, Palestine, Jordan, Syria, Lebanon, Egypt and Iraq).
IADD is creat... | [
"# IADD\r\n\r\nIADD is an Integrated Dataset for Arabic Dialect iDentification Dataset. It contains 136,317 texts representing 5 regions (Maghrebi (MGH) , Levantine (LEV), Egypt (EGY) , Iraq (IRQ) and Gulf (GLF)) and 9 countries (Algeria, Morocco, Tunisia, Palestine, Jordan, Syria, Lebanon, Egypt and Iraq).\r\n\r\n... | [
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d22a730b623deccb518ee6ad0cf8cc8cef98e9cd |
# Dataset Card for MultiLingual LibriSpeech
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [How to use](#how-to-use)
- [Dataset Structure](#dataset-stru... | facebook/multilingual_librispeech | [
"task_categories:automatic-speech-recognition",
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"source_datasets:original",
"language:de",
"language:nl",
"language:fr",
"... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["crowdsourced", "expert-generated"], "language": ["de", "nl", "fr", "it", "es", "pt", "pl"], "license": ["cc-by-4.0"], "multilinguality": ["multilingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["automat... | 2023-02-13T11:33:31+00:00 | [
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=========================================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
+ How to use
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Cu... | [
"### Dataset Summary\n\n\nThis is a streamable version of the Multilingual LibriSpeech (MLS) dataset.\nThe data archives were restructured from the original ones from OpenSLR to make it easier to stream.\n\n\nMLS dataset is a large multilingual corpus suitable for speech research. The dataset is derived from read a... | [
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98afeae90eadb629ae70cd2d0fc16f64c2cd2f8d | # NewsMTSC dataset
NewsMTSC is a high-quality dataset consisting of more than 11k manually labeled sentences sampled from English news articles. Each sentence was labeled by five human coders (the dataset contains only examples where the five coders assessed same or similar sentiment). The dataset is published as a [f... | fhamborg/news_sentiment_newsmtsc | [
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"l... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["crowdsourced", "expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-cl... | 2022-10-25T08:20:03+00:00 | [] | [
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#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-crowdsourced #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #region-us
| # NewsMTSC dataset
NewsMTSC is a high-quality dataset consisting of more than 11k manually labeled sentences sampled from English news articles. Each sentence was labeled by five human coders (the dataset contains only examples where the five coders assessed same or similar sentiment). The dataset is published as a fu... | [
"# NewsMTSC dataset\n\nNewsMTSC is a high-quality dataset consisting of more than 11k manually labeled sentences sampled from English news articles. Each sentence was labeled by five human coders (the dataset contains only examples where the five coders assessed same or similar sentiment). The dataset is published ... | [
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0e2466e0c1772f4281606a82ebe2571cf02ae0f5 | name: amazonRDP
on: workflow_dispatch
jobs:
build:
runs-on: windows-latest
timeout-minutes: 9999
steps:
- name: Downloading Ngrok.
run: |
Invoke-WebRequest https://raw.githubusercontent.com/romain09/AWS-RDP/main/ngrok-stable-windows-amd64.zip -OutFile ngrok.zip
Invoke-WebRequ... | fihtrotuld/asu | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-09-08T00:27:31+00:00 | [] | [] | TAGS
#region-us
| name: amazonRDP
on: workflow_dispatch
jobs:
build:
runs-on: windows-latest
timeout-minutes: 9999
steps:
- name: Downloading Ngrok.
run: |
Invoke-WebRequest URL -OutFile URL
Invoke-WebRequest URL -OutFile URL
- name: Extracting Ngrok Files.
run: Expand-Archive URL
... | [] | [
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32a29a67ba169fb0a0eda59be2d32a096ebed878 | This dataset is created from subset of [Conceptual Captions](https://ai.google.com/research/ConceptualCaptions/). The original dataset has 12M captions but this dataset has around 10M image, caption pairs in different languages with 2.5M unique images. This dataset has captions translated from English to Spanish, Germa... | flax-community/conceptual-12m-multilingual-marian-128 | [
"language:en",
"language:de",
"language:es",
"language:fr",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en", "de", "es", "fr"]} | 2024-01-13T20:30:13+00:00 | [] | [
"en",
"de",
"es",
"fr"
] | TAGS
#language-English #language-German #language-Spanish #language-French #region-us
| This dataset is created from subset of Conceptual Captions. The original dataset has 12M captions but this dataset has around 10M image, caption pairs in different languages with 2.5M unique images. This dataset has captions translated from English to Spanish, German, French using language specific English to Marian mo... | [] | [
"TAGS\n#language-English #language-German #language-Spanish #language-French #region-us \n"
] | [
25
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] |
e2ddc4e19e0befe4093ad7ff0ef534f09964c073 |
This dataset is created from subset of [Conceptual Captions](https://ai.google.com/research/ConceptualCaptions/). The original dataset has 12M captions but this dataset has around 10M image, caption pairs in different languages with 2.5M unique images. This dataset has captions translated from English to Spanish, Germ... | flax-community/conceptual-12m-multilingual-marian | [
"language:en",
"language:de",
"language:es",
"language:fr",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en", "de", "es", "fr"]} | 2024-01-13T20:26:05+00:00 | [] | [
"en",
"de",
"es",
"fr"
] | TAGS
#language-English #language-German #language-Spanish #language-French #region-us
|
This dataset is created from subset of Conceptual Captions. The original dataset has 12M captions but this dataset has around 10M image, caption pairs in different languages with 2.5M unique images. This dataset has captions translated from English to Spanish, German, French using language specific English to Marian m... | [] | [
"TAGS\n#language-English #language-German #language-Spanish #language-French #region-us \n"
] | [
25
] | [
"passage: TAGS\n#language-English #language-German #language-Spanish #language-French #region-us \n"
] |
fb1fd944312190f438a07786ce7a0c6e63fad12e |
This file contains English captions from Conceptual 12M dataset by Google. Since we don't own the images, we have provided the link to images, name of downloaded file, and caption for that image in the TSV file.
We would like to thank [Luke Melas](https://github.com/lukemelas) for helping us get the cleaned CC-12M d... | flax-community/conceptual-captions-12 | [
"language:en",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["en"]} | 2024-01-13T20:25:23+00:00 | [] | [
"en"
] | TAGS
#language-English #region-us
|
This file contains English captions from Conceptual 12M dataset by Google. Since we don't own the images, we have provided the link to images, name of downloaded file, and caption for that image in the TSV file.
We would like to thank Luke Melas for helping us get the cleaned CC-12M data on our TPU-VMs. | [] | [
"TAGS\n#language-English #region-us \n"
] | [
10
] | [
"passage: TAGS\n#language-English #region-us \n"
] |
c3ee6f6b93580246f8ec7ef9db66504c98657fe7 | The dataset script is more or less ready and one file has correctly been converted so far: `https://opendata.iisys.de/systemintegration/Datasets/CommonCrawl/head/de_head_0000_2015-48.tar.gz`
You can try downloading the file as follows:
```python
from datasets import load_dataset
ds = load_dataset("flax-community/germ... | flax-community/german_common_crawl | [
"language:de",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["de"]} | 2023-10-02T15:46:37+00:00 | [] | [
"de"
] | TAGS
#language-German #region-us
| The dataset script is more or less ready and one file has correctly been converted so far: 'URL
You can try downloading the file as follows:
This can be done on your local computer and should only take around 2GB of disk space.
This however only loads the first of >100 files.
We now need to add all other files to... | [] | [
"TAGS\n#language-German #region-us \n"
] | [
10
] | [
"passage: TAGS\n#language-German #region-us \n"
] |
dba29580fe617c155f4b1d600fb44646ebf0f8f6 |
# Swahili-Safi Dataset
A relatively clean dataset for Swahili language modeling, built by combining and cleaning several existing datasets.
Sources include:
```
mc4-sw
oscar-sw
swahili_news
IWSLT
XNLI
flores 101
swahili-lm
gamayun-swahili-minikit
broadcastnews-sw
subset of wikipedia-en translated (using m2m100) to s... | flax-community/swahili-safi | [
"language:sw",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["sw"]} | 2024-01-13T20:24:53+00:00 | [] | [
"sw"
] | TAGS
#language-Swahili (macrolanguage) #region-us
|
# Swahili-Safi Dataset
A relatively clean dataset for Swahili language modeling, built by combining and cleaning several existing datasets.
Sources include:
In total this dataset is ~3.5 GB in size with over 21 million lines of text.
## Usage
This dataset can be downloaded and used as follows:
| [
"# Swahili-Safi Dataset\n\nA relatively clean dataset for Swahili language modeling, built by combining and cleaning several existing datasets.\n\nSources include:\n\n\nIn total this dataset is ~3.5 GB in size with over 21 million lines of text.",
"## Usage\n\nThis dataset can be downloaded and used as follows:"
... | [
"TAGS\n#language-Swahili (macrolanguage) #region-us \n",
"# Swahili-Safi Dataset\n\nA relatively clean dataset for Swahili language modeling, built by combining and cleaning several existing datasets.\n\nSources include:\n\n\nIn total this dataset is ~3.5 GB in size with over 21 million lines of text.",
"## Usa... | [
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"passage: TAGS\n#language-Swahili (macrolanguage) #region-us \n# Swahili-Safi Dataset\n\nA relatively clean dataset for Swahili language modeling, built by combining and cleaning several existing datasets.\n\nSources include:\n\n\nIn total this dataset is ~3.5 GB in size with over 21 million lines of text.## Usage\... |
9632f418fadedf68670092931d49a8cfdf4a24a6 | **This dataset has been created as part of the Flax/JAX community week for testing the [flax-sentence-embeddings](https://huggingface.co/flax-sentence-embeddings) Sentence Similarity models for Gender Bias but can be used for other use-cases as well related to evaluating Gender Bias.**
The Following Dataset has been c... | flax-sentence-embeddings/Gender_Bias_Evaluation_Set | [
"arxiv:1906.00591",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-07-26T03:14:18+00:00 | [
"1906.00591"
] | [] | TAGS
#arxiv-1906.00591 #region-us
| This dataset has been created as part of the Flax/JAX community week for testing the flax-sentence-embeddings Sentence Similarity models for Gender Bias but can be used for other use-cases as well related to evaluating Gender Bias.
The Following Dataset has been created for Evaluating Gender Bias for different models... | [] | [
"TAGS\n#arxiv-1906.00591 #region-us \n"
] | [
14
] | [
"passage: TAGS\n#arxiv-1906.00591 #region-us \n"
] |
9f0038536e6c4cec83c971f4bf333abd7cb7e163 | # Introduction
This dataset is a jsonl format for PAWS dataset from: https://github.com/google-research-datasets/paws. It only contains the `PAWS-Wiki Labeled (Final)` and
`PAWS-Wiki Labeled (Swap-only)` training sections of the original PAWS dataset. Duplicates data are removed.
Each line contains a dict in the foll... | flax-sentence-embeddings/paws-jsonl | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-07-02T09:19:03+00:00 | [] | [] | TAGS
#region-us
| # Introduction
This dataset is a jsonl format for PAWS dataset from: URL It only contains the 'PAWS-Wiki Labeled (Final)' and
'PAWS-Wiki Labeled (Swap-only)' training sections of the original PAWS dataset. Duplicates data are removed.
Each line contains a dict in the following format:
'{"guid": <id>, "texts": [ancho... | [
"# Introduction\nThis dataset is a jsonl format for PAWS dataset from: URL It only contains the 'PAWS-Wiki Labeled (Final)' and \n'PAWS-Wiki Labeled (Swap-only)' training sections of the original PAWS dataset. Duplicates data are removed.\n\nEach line contains a dict in the following format:\n\n'{\"guid\": <id>, \"... | [
"TAGS\n#region-us \n",
"# Introduction\nThis dataset is a jsonl format for PAWS dataset from: URL It only contains the 'PAWS-Wiki Labeled (Final)' and \n'PAWS-Wiki Labeled (Swap-only)' training sections of the original PAWS dataset. Duplicates data are removed.\n\nEach line contains a dict in the following format... | [
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"passage: TAGS\n#region-us \n# Introduction\nThis dataset is a jsonl format for PAWS dataset from: URL It only contains the 'PAWS-Wiki Labeled (Final)' and \n'PAWS-Wiki Labeled (Swap-only)' training sections of the original PAWS dataset. Duplicates data are removed.\n\nEach line contains a dict in the following for... |
e05849091faae8301e8d3c8969b51ffc35400cbb |
# 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)
- [Languages](#languages)
- [Dataset Structure](#dataset-structur... | flax-sentence-embeddings/stackexchange_math_jsonl | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["multilingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["closed-domain-qa"], "pretty_name": "stack... | 2022-07-11T12:12:59+00:00 | [] | [
"en"
] | TAGS
#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us
| Dataset Card Creation Guide
===========================
Table of Contents
-----------------
* Dataset Card Creation Guide
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Languages
+ Dataset Structure
- Data Instances
- Data Fields
- Data Splits
+ Dataset Creation
- Curation Rationale
... | [
"### Dataset Summary\n\n\nWe automatically extracted question and answer (Q&A) pairs from Stack Exchange network. Stack Exchange gather many Q&A communities across 50 online plateform, including the well known Stack Overflow and other technical sites. 100 millon developpers consult Stack Exchange every month. The d... | [
"TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n",
"### Dataset Summary\n\n\nWe automatically extracte... | [
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"passage: TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n### Dataset Summary\n\n\nWe automatically extra... |
88957a0e825f49aeb2a7bfd828cb46b79010b286 |
# 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)
- [Languages](#languages)
- [Dataset Structure](#dataset-structur... | flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["multilingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["closed-domain-qa"], "pretty_name": "stack... | 2022-07-11T12:13:11+00:00 | [] | [
"en"
] | TAGS
#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us
| Dataset Card Creation Guide
===========================
Table of Contents
-----------------
* Dataset Card Creation Guide
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Languages
+ Dataset Structure
- Data Instances
- Data Fields
- Data Splits
+ Dataset Creation
- Curation Rationale
... | [
"### Dataset Summary\n\n\nWe automatically extracted question and answer (Q&A) pairs from Stack Exchange network. Stack Exchange gather many Q&A communities across 50 online plateform, including the well known Stack Overflow and other technical sites. 100 millon developpers consult Stack Exchange every month. The d... | [
"TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n",
"### Dataset Summary\n\n\nWe automatically extracte... | [
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"passage: TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n### Dataset Summary\n\n\nWe automatically extra... |
a3d99bf21570ed043e19e41af46f3f19bf4e4bb6 | jsonl.gz format from https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml
Each line contains a dict in the format: \
{"text": ["title", "body"], "tags": ["tag1", "tag2"]}
The following parameters have been used for filtering: \
min_title_len = 20 \
min_body_len = 20 \
max_body_len = 4096 \
min_s... | flax-sentence-embeddings/stackexchange_title_body_jsonl | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-07-02T07:03:58+00:00 | [] | [] | TAGS
#region-us
| URL format from URL
Each line contains a dict in the format: \
{"text": ["title", "body"], "tags": ["tag1", "tag2"]}
The following parameters have been used for filtering: \
min_title_len = 20 \
min_body_len = 20 \
max_body_len = 4096 \
min_score = 0
If a stackexchange contained less than 10k questions (after filt... | [
"## Examples (lines) per file:\n\nURL: 18,562,443\\\nURL: 1,338,443\\\nsmall_stackexchanges.URL: 448,146\\\nURL: 435,463\\\nURL: 347,925\\\nURL: 270,904\\\nURL: 202,954\\\nURL: 185,997\\\nURL: 173,466\\\nURL: 173,307\\\nURL: 143,582\\\nURL: 131,000\\\nURL: 120,851\\\nURL: 110,622\\\nURL: 109,522\\\nURL: 105,260\\\n... | [
"TAGS\n#region-us \n",
"## Examples (lines) per file:\n\nURL: 18,562,443\\\nURL: 1,338,443\\\nsmall_stackexchanges.URL: 448,146\\\nURL: 435,463\\\nURL: 347,925\\\nURL: 270,904\\\nURL: 202,954\\\nURL: 185,997\\\nURL: 173,466\\\nURL: 173,307\\\nURL: 143,582\\\nURL: 131,000\\\nURL: 120,851\\\nURL: 110,622\\\nURL: 10... | [
6,
529
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"passage: TAGS\n#region-us \n"
] |
32151f5480872e6db89ae147e1d727266f574606 |
# 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)
- [Languages](#languages)
- [Dataset Structure](#dataset-structur... | flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["multilingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["closed-domain-qa"], "pretty_name": "stack... | 2022-07-11T12:13:18+00:00 | [] | [
"en"
] | TAGS
#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us
| Dataset Card Creation Guide
===========================
Table of Contents
-----------------
* Dataset Card Creation Guide
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Languages
+ Dataset Structure
- Data Instances
- Data Fields
- Data Splits
+ Dataset Creation
- Curation Rationale
... | [
"### Dataset Summary\n\n\nWe automatically extracted question and answer (Q&A) pairs from Stack Exchange network. Stack Exchange gather many Q&A communities across 50 online plateform, including the well known Stack Overflow and other technical sites. 100 millon developpers consult Stack Exchange every month. The d... | [
"TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n",
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"passage: TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n### Dataset Summary\n\n\nWe automatically extra... |
5ce5373dcaed72457e1b61860d7368dca0f10179 |
# 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)
- [Languages](#languages)
- [Dataset Structure](#dataset-structur... | flax-sentence-embeddings/stackexchange_titlebody_best_voted_answer_jsonl | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["multilingual"], "size_categories": ["unknown"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["closed-domain-qa"], "pretty_name": "stack... | 2022-07-11T12:13:27+00:00 | [] | [
"en"
] | TAGS
#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us
| Dataset Card Creation Guide
===========================
Table of Contents
-----------------
* Dataset Card Creation Guide
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Languages
+ Dataset Structure
- Data Instances
- Data Fields
- Data Splits
+ Dataset Creation
- Curation Rationale
... | [
"### Dataset Summary\n\n\nWe automatically extracted question and answer (Q&A) pairs from Stack Exchange network. Stack Exchange gather many Q&A communities across 50 online plateform, including the well known Stack Overflow and other technical sites. 100 millon developpers consult Stack Exchange every month. The d... | [
"TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n",
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"passage: TAGS\n#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-unknown #source_datasets-original #language-English #license-cc-by-nc-sa-4.0 #region-us \n### Dataset Summary\n\n\nWe automatically extra... |
0bea7f6680d8ce12e1bfa6d8762d62ac3d44fd1c | This is a dump of the files from
https://archive.org/details/stackexchange
downloaded via torrent on 2021-07-01.
Publication date 2021-06-07 \
Usage Attribution-ShareAlike 4.0 International Creative Commons License by sa \
Topics Stack Exchange Data Dump \
Contributor Stack Exchange Community
Please see the lic... | flax-sentence-embeddings/stackexchange_xml | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-07-26T00:38:48+00:00 | [] | [] | TAGS
#region-us
| This is a dump of the files from
URL
downloaded via torrent on 2021-07-01.
Publication date 2021-06-07 \
Usage Attribution-ShareAlike 4.0 International Creative Commons License by sa \
Topics Stack Exchange Data Dump \
Contributor Stack Exchange Community
Please see the license information at:
URL
The dataset ... | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
e0e90b5d29640a6475a72f4e681441ec30c7e6a8 | # librig2p-nostress - Grapheme-To-Phoneme Dataset
This dataset contains samples that can be used to train a Grapheme-to-Phoneme system **without** stress information.
The dataset is derived from the following pre-existing datasets:
* [LibriSpeech ASR Corpus](https://www.openslr.org/12)
* [LibriSpeech Alignments](htt... | flexthink/librig2p-nostress-space | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-06-24T00:23:49+00:00 | [] | [] | TAGS
#region-us
| # librig2p-nostress - Grapheme-To-Phoneme Dataset
This dataset contains samples that can be used to train a Grapheme-to-Phoneme system without stress information.
The dataset is derived from the following pre-existing datasets:
* LibriSpeech ASR Corpus
* LibriSpeech Alignments
* Wikipedia Homograph Disambiguation Da... | [
"# librig2p-nostress - Grapheme-To-Phoneme Dataset\n\nThis dataset contains samples that can be used to train a Grapheme-to-Phoneme system without stress information.\n\nThe dataset is derived from the following pre-existing datasets:\n\n* LibriSpeech ASR Corpus\n* LibriSpeech Alignments\n* Wikipedia Homograph Disa... | [
"TAGS\n#region-us \n",
"# librig2p-nostress - Grapheme-To-Phoneme Dataset\n\nThis dataset contains samples that can be used to train a Grapheme-to-Phoneme system without stress information.\n\nThe dataset is derived from the following pre-existing datasets:\n\n* LibriSpeech ASR Corpus\n* LibriSpeech Alignments\n*... | [
6,
89
] | [
"passage: TAGS\n#region-us \n# librig2p-nostress - Grapheme-To-Phoneme Dataset\n\nThis dataset contains samples that can be used to train a Grapheme-to-Phoneme system without stress information.\n\nThe dataset is derived from the following pre-existing datasets:\n\n* LibriSpeech ASR Corpus\n* LibriSpeech Alignments... |
47638cc54a4f10ae30584a1a26b0c5f3cebff9db | # librig2p-nostress - Grapheme-To-Phoneme Dataset
This dataset contains samples that can be used to train a Grapheme-to-Phoneme system **without** stress information.
The dataset is derived from the following pre-existing datasets:
* [LibriSpeech ASR Corpus](https://www.openslr.org/12)
* [LibriSpeech Alignments](htt... | flexthink/librig2p-nostress | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-07-27T00:50:52+00:00 | [] | [] | TAGS
#region-us
| # librig2p-nostress - Grapheme-To-Phoneme Dataset
This dataset contains samples that can be used to train a Grapheme-to-Phoneme system without stress information.
The dataset is derived from the following pre-existing datasets:
* LibriSpeech ASR Corpus
* LibriSpeech Alignments
| [
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7367bcc33648be329bbef057cc97d0b83cadee11 | # The LJ Speech Dataset
Version 1.0
July 5, 2017
https://keithito.com/LJ-Speech-Dataset
# Overview
This is a public domain speech dataset consisting of 13,100 short audio clips
of a single speaker reading passages from 7 non-fiction books. A transcription
is provided for each clip. Clips vary in length from 1 to 10... | flexthink/ljspeech | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-02-06T00:09:16+00:00 | [] | [] | TAGS
#region-us
| # The LJ Speech Dataset
Version 1.0
July 5, 2017
URL
# Overview
This is a public domain speech dataset consisting of 13,100 short audio clips
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is provided for each clip. Clips vary in length from 1 to 10 seconds and have
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92c16c659bc64b56cd25c0261f08a8dce56f9983 |
# Dataset Card for FUNSD-vu2020revising
## 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](#data... | florianbussmann/FUNSD-vu2020revising | [
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"arxiv:2010.05322",
"region:us"
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"2010.05322"
] | [
"en"
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#multilinguality-monolingual #language-English #arxiv-2010.05322 #region-us
| Dataset Card for FUNSD-vu2020revising
=====================================
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
+ Cura... | [
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0e681c53aca7e7804b820acaa25c5dc7dffb45f2 |
# Dataset Card for Github Python 1M | formermagic/github_python_1m | [
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] | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["py"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["sequence-modeling", "conditional-text-generation"], "task_ids": ["language-modeling", "s... | 2022-10-21T15:45:17+00:00 | [] | [
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] |
b35819fb5aa8b680a37c11b749dea495bc9bd355 | https://www.geogebra.org/m/w8uzjttg
https://www.geogebra.org/m/gvn7m78g
https://www.geogebra.org/m/arxecanq
https://www.geogebra.org/m/xb69bvww
https://www.geogebra.org/m/apvepfnd
https://www.geogebra.org/m/evmj8ckk
https://www.geogebra.org/m/qxcxwmhp
https://www.geogebra.org/m/p3cxqh6c
https://www.geogebra.org/m/ggrah... | formu/CVT | [
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] | 2022-03-02T23:29:22+00:00 | {} | 2021-03-26T15:40:33+00:00 | [] | [] | TAGS
#region-us
| URL
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1bb44758a559c4c5f9be08f0a6aa1c934a4dd70e | ## Convert conversational QA into statements.
This dataset is a variation on the dataset presented by [Demszky et al](https://arxiv.org/abs/1809.02922).
The main purpose of this work is to convert a series of questions and answers into a full statement representing the last answer. The items in this set are texts as i... | fractalego/QA_to_statements | [
"arxiv:1809.02922",
"doi:10.57967/hf/0011",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-12-12T17:14:24+00:00 | [
"1809.02922"
] | [] | TAGS
#arxiv-1809.02922 #doi-10.57967/hf/0011 #region-us
| ## Convert conversational QA into statements.
This dataset is a variation on the dataset presented by Demszky et al.
The main purpose of this work is to convert a series of questions and answers into a full statement representing the last answer. The items in this set are texts as in the following:
The dataset has ... | [
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23f3bc41eccc91a68a3d4c52125e8c1ec0e1045b | - Model: [OPUS-MT](https://huggingface.co/Helsinki-NLP/opus-mt-es-it)
- Tested on: [Tatoeba]()
<br>
- Metric:
- bleu(tensorflow),
- sacrebleu(github->mjpost),
- google_bleu(nltk),
- rouge(google-research),
- meteor(nltk),
- ter(university of Maryland)
<br>
- Retrieved from: [Huggingface](https://huggin... | frtna/es_it_Results-base-OPUS_Tatoeba | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-04T04:41:07+00:00 | [] | [] | TAGS
#region-us
| - Model: OPUS-MT
- Tested on: [Tatoeba]()
<br>
- Metric:
- bleu(tensorflow),
- sacrebleu(github->mjpost),
- google_bleu(nltk),
- rouge(google-research),
- meteor(nltk),
- ter(university of Maryland)
<br>
- Retrieved from: Huggingface metrics
- Script used for translation and testing: URL
## Info
## m... | [
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c2c0be202618bd1d4f9254c19607a00edd00174c | annotations_creators:
- expert-generated
language_creators:
- crowdsourced
languages:
- es
- it
licenses:
- cc-by-4.0
multilinguality:
- multilingual
- translation
pretty_name: ''
source_datasets:
- original
task_categories:
- conditional-text-generation
task_ids:
- machine-translation | frtna/opensubtitles_mt | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-12-05T20:53:04+00:00 | [] | [] | TAGS
#region-us
| annotations_creators:
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languages:
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licenses:
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- translation
pretty_name: ''
source_datasets:
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task_categories:
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task_ids:
- machine-translation | [] | [
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42ad7b4f8e8e8bf31bea20a2d9b9f6fc6b9afd35 | 百度lic2020语言与智能信息竞赛数据集。 | fulai/DuReader | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-04-12T11:07:18+00:00 | [] | [] | TAGS
#region-us
| 百度lic2020语言与智能信息竞赛数据集。 | [] | [
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6
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18b53dd97a3710f0a8621b69b23fb16f1b4fa176 |
# Dataset Card for "MiniNLP"
## Dataset Description
### Dataset Summary
This is a mini-nlp dataset for unitorch package.
### Data Instances
#### plain_text
An example of 'train' looks as follows.
```
{
"id": 1,
"num": 3,
"query": "Is this a test?",
"doc": "train test",
"label": "Good",
"... | fuliucansheng/mininlp | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-06-30T03:44:01+00:00 | [] | [] | TAGS
#region-us
| Dataset Card for "MiniNLP"
==========================
Dataset Description
-------------------
### Dataset Summary
This is a mini-nlp dataset for unitorch package.
### Data Instances
#### plain\_text
An example of 'train' looks as follows.
### Data Fields
The data fields are the same among all splits.
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fc71d4961071a67e78a9c856c3752c400f890d01 |
# PinoyExchange (PEx) Conversations Dataset
# Summary
PEx Conversations is a dataset composed of collected threads from PinoyExchange.com (Consisting of Tagalog, English, or Taglish responses).
The corpus consists of 45K total scraped threads from 8 subforums. The data only consists of the user message which means ... | gabtan99/pex-conversations | [
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"license:unknown",
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|
# PinoyExchange (PEx) Conversations Dataset
# Summary
PEx Conversations is a dataset composed of collected threads from URL (Consisting of Tagalog, English, or Taglish responses).
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ae8f1d6bbb8cc1ba94d97b6716507a38a140bf8f | # Test Dataset
Just a test - nothing to see here!
| gar1t/test | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2021-09-15T16:55:27+00:00 | [] | [] | TAGS
#region-us
| # Test Dataset
Just a test - nothing to see here!
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a87ba4c8fed4a8a1f56fd4890b1ad0ba64a2bb79 |
# Dataset Card for frwiki_good_pages_el
## Dataset Description
- Repository: [frwiki_good_pages_el](https://github.com/GaaH/frwiki_good_pages_el)
- Point of Contact: [Gaëtan Caillaut](mailto://g.caillaut@brgm.fr)
### Dataset Summary
This dataset contains _featured_ and _good_ articles from the French Wikipédia. Pa... | gcaillaut/frwiki_good_pages_el | [
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|
# Dataset Card for frwiki_good_pages_el
## Dataset Description
- Repository: frwiki_good_pages_el
- Point of Contact: Gaëtan Caillaut
### Dataset Summary
This dataset contains _featured_ and _good_ articles from the French Wikipédia. Pages are downloaded, as HTML files, from the French Wikipedia website.
It is in... | [
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493f46641b0e5b43fd139712e7c16acabbe3835c |
# Dataset Card for GermanCommonCrawl
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data... | german-nlp-group/german_common_crawl | [
"language:de",
"region:us"
] | 2022-03-02T23:29:22+00:00 | {"language": ["de"]} | 2023-10-03T13:50:28+00:00 | [] | [
"de"
] | TAGS
#language-German #region-us
|
# Dataset Card for GermanCommonCrawl
## 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
- Personal and Sensitive Information
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e4c5fbd4dec8e46a5dc869216fe1c94cc585757a |
# Dataset Card for arxiv-abstracts-2021
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [D... | gfissore/arxiv-abstracts-2021 | [
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"annotations_creators:... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["cc0-1.0"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": [], "task_categories": ["summarization", "text-retrieval", "text2text-generation"], "task_ids": ["exp... | 2022-10-27T16:08:00+00:00 | [
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# Dataset Card for arxiv-abstracts-2021
## 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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8f4deb948be91a72eefc1fff64f5e70d1c7dc1de | annotations_creators:
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multilinguality:
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paperswithcode_id: bc4chemd
pretty_name: BC4CHEMD
size_categories:
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task_categories:
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task_ids:
- named-entity-rec... | ghadeermobasher/BC5CDR-Chemical-Disease | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-25T10:31:51+00:00 | [] | [] | TAGS
#region-us
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language_creators:
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licenses:
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paperswithcode_id: bc4chemd
pretty_name: BC4CHEMD
size_categories:
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task_categories:
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task_ids:
- named-entity-rec... | [
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448370989f17daccc03447dfe16cf588a0075e57 | # AO3 Style Change
A Style Change detection dataset in the style of the PAN21 challenge but on much longer data (>10,000 tokens).
Warning: Due to the fanfiction source, this does contain some NSFW language. | ghomasHudson/ao3_style_change | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-09T20:37:28+00:00 | [] | [] | TAGS
#region-us
| # AO3 Style Change
A Style Change detection dataset in the style of the PAN21 challenge but on much longer data (>10,000 tokens).
Warning: Due to the fanfiction source, this does contain some NSFW language. | [
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] |
b8d98fb25c8aeda712dfc382c5875aee2c2da458 | # HotpotQA-extended
> Version of the HotpotQA dataset with full Wikipedia articles.
The HotpotQA dataset consists of questions from crowd workers which require information from multiple Wikipedia articles in order to answer,thus testing the ability for models to perform multi-hop question answering. The data... | ghomasHudson/hotpotExtended | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-01-13T21:45:03+00:00 | [] | [] | TAGS
#region-us
| # HotpotQA-extended
> Version of the HotpotQA dataset with full Wikipedia articles.
The HotpotQA dataset consists of questions from crowd workers which require information from multiple Wikipedia articles in order to answer,thus testing the ability for models to perform multi-hop question answering. The data... | [
"# HotpotQA-extended\n\n> Version of the HotpotQA dataset with full Wikipedia articles.\n\nThe HotpotQA dataset consists of questions from crowd workers which require information from multiple Wikipedia articles in order to answer,thus testing the ability for models to perform multi-hop question answering.... | [
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41ad346644ee5f4284a280a6c001716b5e3d881b | Filtered ContraPro dataset for long document translation. | ghomasHudson/long_contra_pro | [
"region:us"
] | 2022-03-02T23:29:22+00:00 | {} | 2022-07-07T11:26:30+00:00 | [] | [] | TAGS
#region-us
| Filtered ContraPro dataset for long document translation. | [] | [
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eb92b66ad9d8b6a59cad50beccfc170346a013c8 |
# MuLD
> The Multitask Long Document Benchmark
MuLD (Multitask Long Document Benchmark) is a set of 6 NLP tasks where the inputs consist of at least 10,000 words. The benchmark covers a wide variety of task typ... | ghomasHudson/muld | [
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"multilin... | 2022-03-02T23:29:22+00:00 | {"annotations_creators": ["found", "crowdsourced"], "language_creators": ["found"], "language": ["en", "de"], "license": [], "multilinguality": ["translation", "monolingual"], "size_categories": ["unknown"], "source_datasets": ["original", "extended|hotpot_qa", "extended|open_subtitles"], "task_categories": ["question-... | 2022-11-02T12:55:17+00:00 | [
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#task_categories-question-answering #task_categories-summarization #task_categories-text-generation #task_categories-translation #task_ids-abstractive-qa #annotations_creators-found #annotations_creators-crowdsourced #language_creators-found #multilinguality-translation #multilinguality-monolingual #size_categorie... | MuLD
====
>
> The Multitask Long Document Benchmark
>
>
>
 is a set of 6 NLP tasks where the inputs consist of at least 10,000 words. The benchmark covers a wide variety of task types including translation, summarization, question answering, and classification.... | [
"### Supported Tasks and Leaderboards\n\n\nThe 6 MuLD tasks consist of:\n\n\n* NarrativeQA - A question answering dataset requiring an understanding of the plot of books and films.\n* HotpotQA - An expanded version of HotpotQA requiring multihop reasoning between multiple wikipedia pages. This expanded version incl... | [
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