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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a4060f6c30fac71147c6f424fd6adb3b0b753f59 | Images from CC12M encoded with VQGAN f16 1024
Script to continue prep is included in the repo if you want more than the ~1.5M images I did here.
VQGAN model:
```
!curl -L 'https://heibox.uni-heidelberg.de/d/8088892a516d4e3baf92/files/?p=%2Fckpts%2Flast.ckpt&dl=1' > vqgan_im1024.ckpt
!curl -L 'https://heibox.uni-heide... | johnowhitaker/vqgan1024_encs_sf | [
"region:us"
] | 2022-04-23T15:07:38+00:00 | {} | 2022-04-23T15:22:37+00:00 | [] | [] | TAGS
#region-us
| Images from CC12M encoded with VQGAN f16 1024
Script to continue prep is included in the repo if you want more than the ~1.5M images I did here.
VQGAN model:
Try it out: TODO | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
44fe0b34f20ba09aa287148447873c1f3992e265 |
# MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages
## Table of Contents
- [Dataset Card for [Needs More Information]](#dataset-card-for-needs-more-information)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
... | qanastek/MASSIVE | [
"task_categories:text-classification",
"task_ids:intent-classification",
"task_ids:multi-class-classification",
"task_ids:named-entity-recognition",
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:multilingual",
"size_cat... | 2022-04-23T15:23:09+00:00 | {"annotations_creators": ["machine-generated", "expert-generated"], "language_creators": ["found"], "language": ["af", "am", "ar", "az", "bn", "cy", "da", "de", "el", "en", "es", "fa", "fi", "fr", "he", "hi", "hu", "hy", "id", "is", "it", "ja", "jv", "ka", "km", "kn", "ko", "lv", "ml", "mn", "ms", "my", "nb", "nl", "pl... | 2022-12-23T21:28:08+00:00 | [
"2204.08582"
] | [
"af",
"am",
"ar",
"az",
"bn",
"cy",
"da",
"de",
"el",
"en",
"es",
"fa",
"fi",
"fr",
"he",
"hi",
"hu",
"hy",
"id",
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"ja",
"jv",
"ka",
"km",
"kn",
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"lv",
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"nb",
"nl",
"pl",
"pt",
"ro",
"ru",
"sl",
"sq"... | TAGS
#task_categories-text-classification #task_ids-intent-classification #task_ids-multi-class-classification #task_ids-named-entity-recognition #annotations_creators-machine-generated #annotations_creators-expert-generated #language_creators-found #multilinguality-multilingual #size_categories-100K<n<1M #source_datas... | MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages
=================================================================================================================
Table of Contents
-----------------
* [Dataset Card for](#dataset-card-for-needs-more-in... | [
"### Dataset Summary\n\n\nMASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations for the Natural Language Understanding tasks of intent prediction and slot annotation. Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing the SLURP dataset, composed o... | [
"TAGS\n#task_categories-text-classification #task_ids-intent-classification #task_ids-multi-class-classification #task_ids-named-entity-recognition #annotations_creators-machine-generated #annotations_creators-expert-generated #language_creators-found #multilinguality-multilingual #size_categories-100K<n<1M #source... | [
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5ccd054e794667994e2fd3b6a5ff01bed70f9acf | VQGAN is great, but leaves artifacts that are especially visible around things like faces.
It's be great to be able to train a model to fix ('devqganify') these flaws.
For this purpose, I've made this dataset, which contains >100k examples, each with
- A 512px image
- A smaller 256px version of the same image
- A re... | johnowhitaker/vqgan16k_reconstruction | [
"region:us"
] | 2022-04-23T17:00:28+00:00 | {} | 2022-04-24T05:13:26+00:00 | [] | [] | TAGS
#region-us
| VQGAN is great, but leaves artifacts that are especially visible around things like faces.
It's be great to be able to train a model to fix ('devqganify') these flaws.
For this purpose, I've made this dataset, which contains >100k examples, each with
- A 512px image
- A smaller 256px version of the same image
- A re... | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
ebe02645e5511e32c87c79746a75dc2d45bae062 | # Dataset Card for [Kaggle MNLI]
## 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-stru... | chrishuber/kaggle_mnli | [
"arxiv:1704.05426",
"region:us"
] | 2022-04-23T17:16:05+00:00 | {} | 2022-04-23T18:19:52+00:00 | [
"1704.05426"
] | [] | TAGS
#arxiv-1704.05426 #region-us
| # Dataset Card for [Kaggle MNLI]
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Per... | [
"# Dataset Card for [Kaggle MNLI]",
"## 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 Rationale\n - Source Data\n ... | [
"TAGS\n#arxiv-1704.05426 #region-us \n",
"# Dataset Card for [Kaggle MNLI]",
"## 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\... | [
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ac3f65840a512ce745231e9d6339c2bc83e61582 |
## Dataset Description
- **Homepage:** None
- **Repository:** None
- **Paper:** None
- **Leaderboard:** [More Information Needed]
- **Point of Contact:** [More Information Needed]
| d0r1h/Shlokam | [
"language_creators:found",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:sn",
"language:en",
"license:cc-by-3.0",
"region:us"
] | 2022-04-24T08:50:02+00:00 | {"annotations_creators": "found", "language_creators": ["found"], "language": ["sn", "en"], "license": "cc-by-3.0", "multilinguality": ["translation"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "pretty_name": "Shlokam"} | 2022-10-25T09:09:04+00:00 | [] | [
"sn",
"en"
] | TAGS
#language_creators-found #multilinguality-translation #size_categories-1K<n<10K #source_datasets-original #language-Shona #language-English #license-cc-by-3.0 #region-us
|
## Dataset Description
- Homepage: None
- Repository: None
- Paper: None
- Leaderboard:
- Point of Contact:
| [
"## Dataset Description\n\n- Homepage: None\n- Repository: None\n- Paper: None\n- Leaderboard: \n- Point of Contact:"
] | [
"TAGS\n#language_creators-found #multilinguality-translation #size_categories-1K<n<10K #source_datasets-original #language-Shona #language-English #license-cc-by-3.0 #region-us \n",
"## Dataset Description\n\n- Homepage: None\n- Repository: None\n- Paper: None\n- Leaderboard: \n- Point of Contact:"
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] |
7a414e80725eac766f2602676dc8b39f80b061e4 |
## Dataset Summary
FaithDial is a faithful knowledge-grounded dialogue benchmark, composed of **50,761** turns spanning **5649** conversations. It was curated through Amazon Mechanical Turk by asking annotators to amend hallucinated utterances in [Wizard of Wikipedia](https://parl.ai/projects/wizard_of_wikipedia/) (Wo... | McGill-NLP/FaithDial | [
"task_categories:conversational",
"task_categories:text-generation",
"task_ids:dialogue-modeling",
"annotations_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100k",
"language:en",
"license:mit",
"faithful-dialogue-modeling",
"trustworthy-dialogue-modeling",
"arxiv... | 2022-04-24T22:10:52+00:00 | {"annotations_creators": ["crowdsourced"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100k"], "task_categories": ["conversational", "text-generation"], "task_ids": ["dialogue-modeling"], "pretty_name": "A Faithful Benchmark for Information-Seeking Dialogue", "... | 2023-02-05T04:09:45+00:00 | [
"2204.10757"
] | [
"en"
] | TAGS
#task_categories-conversational #task_categories-text-generation #task_ids-dialogue-modeling #annotations_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100k #language-English #license-mit #faithful-dialogue-modeling #trustworthy-dialogue-modeling #arxiv-2204.10757 #region-us
|
## Dataset Summary
FaithDial is a faithful knowledge-grounded dialogue benchmark, composed of 50,761 turns spanning 5649 conversations. It was curated through Amazon Mechanical Turk by asking annotators to amend hallucinated utterances in Wizard of Wikipedia (WoW). In our dialogue setting, we simulate interactions bet... | [
"## Dataset Summary\nFaithDial is a faithful knowledge-grounded dialogue benchmark, composed of 50,761 turns spanning 5649 conversations. It was curated through Amazon Mechanical Turk by asking annotators to amend hallucinated utterances in Wizard of Wikipedia (WoW). In our dialogue setting, we simulate interaction... | [
"TAGS\n#task_categories-conversational #task_categories-text-generation #task_ids-dialogue-modeling #annotations_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100k #language-English #license-mit #faithful-dialogue-modeling #trustworthy-dialogue-modeling #arxiv-2204.10757 #region-us \n",
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5af3b4f0df36436a071954af1d499b9753c0f27b |
# TAU Spatial Room Impulse Response Database (TAU-SRIR DB)
## Important
**This is a copy from the Zenodo Original one**
## Description
[Audio Research Group / Tampere University](https://webpages.tuni.fi/arg/)
AUTHORS
**Tampere University**
- Archontis Politis ([contact](mailto:archontis.politis@tuni.fi), [prof... | Fhrozen/tau_srir_db | [
"task_categories:audio-classification",
"annotations_creators:unknown",
"language_creators:unknown",
"size_categories:n<1K",
"source_datasets:unknown",
"license:unknown",
"audio-slot-filling",
"region:us"
] | 2022-04-25T01:54:54+00:00 | {"annotations_creators": ["unknown"], "language_creators": ["unknown"], "license": "unknown", "size_categories": ["n<1K"], "source_datasets": ["unknown"], "task_categories": ["audio-classification"], "task_ids": [], "tags": ["audio-slot-filling"]} | 2022-12-03T03:27:05+00:00 | [] | [] | TAGS
#task_categories-audio-classification #annotations_creators-unknown #language_creators-unknown #size_categories-n<1K #source_datasets-unknown #license-unknown #audio-slot-filling #region-us
| TAU Spatial Room Impulse Response Database (TAU-SRIR DB)
========================================================
Important
---------
This is a copy from the Zenodo Original one
Description
-----------
Audio Research Group / Tampere University
AUTHORS
Tampere University
* Archontis Politis (contact, profi... | [] | [
"TAGS\n#task_categories-audio-classification #annotations_creators-unknown #language_creators-unknown #size_categories-n<1K #source_datasets-unknown #license-unknown #audio-slot-filling #region-us \n"
] | [
76
] | [
"passage: TAGS\n#task_categories-audio-classification #annotations_creators-unknown #language_creators-unknown #size_categories-n<1K #source_datasets-unknown #license-unknown #audio-slot-filling #region-us \n"
] |
f9c3dafb9b947ddeb04e0b4fcb5c3a904d9105e3 |
## Dataset Description
- **Homepage:** None
- **Repository:** [https://github.com/d0r1h/ILC]
- **Paper:** None
- **Leaderboard:** [More Information Needed]
- **Point of Contact:** [More Information Needed] | d0r1h/ILC | [
"task_categories:summarization",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc-by-3.0",
"legal",
"region:us"
] | 2022-04-25T06:13:24+00:00 | {"language": ["en"], "license": "cc-by-3.0", "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["summarization"], "pretty_name": "ILC", "tags": ["legal"]} | 2023-09-02T11:03:40+00:00 | [] | [
"en"
] | TAGS
#task_categories-summarization #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc-by-3.0 #legal #region-us
|
## Dataset Description
- Homepage: None
- Repository: [URL
- Paper: None
- Leaderboard:
- Point of Contact: | [
"## Dataset Description\n- Homepage: None\n- Repository: [URL\n- Paper: None\n- Leaderboard: \n- Point of Contact:"
] | [
"TAGS\n#task_categories-summarization #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc-by-3.0 #legal #region-us \n",
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51,
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] |
f23677a6713b1558fe0e6ba3ec8db76ec8e49e98 | ## Overview
Original dataset available [here](https://wellecks.github.io/dialogue_nli/).
## Dataset curation
Original `label` column is renamed `original_label`. The original classes are renamed as follows
```
{"positive": "entailment", "negative": "contradiction", "neutral": "neutral"})
```
and encoded with the fo... | pietrolesci/dialogue_nli | [
"region:us"
] | 2022-04-25T07:21:01+00:00 | {} | 2022-04-25T07:39:10+00:00 | [] | [] | TAGS
#region-us
| ## Overview
Original dataset available here.
## Dataset curation
Original 'label' column is renamed 'original_label'. The original classes are renamed as follows
and encoded with the following mapping
and stored in the newly created column 'label'.
The following splits and the corresponding columns are presen... | [
"## Overview\nOriginal dataset available here.",
"## Dataset curation\nOriginal 'label' column is renamed 'original_label'. The original classes are renamed as follows\n\n\n\nand encoded with the following mapping\n\n\n\nand stored in the newly created column 'label'.\n\n\nThe following splits and the correspondi... | [
"TAGS\n#region-us \n",
"## Overview\nOriginal dataset available here.",
"## Dataset curation\nOriginal 'label' column is renamed 'original_label'. The original classes are renamed as follows\n\n\n\nand encoded with the following mapping\n\n\n\nand stored in the newly created column 'label'.\n\n\nThe following s... | [
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"passage: TAGS\n#region-us \n## Overview\nOriginal dataset available here.## Dataset curation\nOriginal 'label' column is renamed 'original_label'. The original classes are renamed as follows\n\n\n\nand encoded with the following mapping\n\n\n\nand stored in the newly created column 'label'.\n\n\nThe following spli... |
1b34f1c8b073c6782b68dc3c5c10ef6356a284d3 | ## Overview
Original dataset [here](https://github.com/decompositional-semantics-initiative/DNC).
This dataset has been proposed in [Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation](https://www.aclweb.org/anthology/D18-1007/).
## Dataset curation
This version of the data... | pietrolesci/dnc | [
"region:us"
] | 2022-04-25T07:54:56+00:00 | {} | 2022-04-25T07:59:06+00:00 | [] | [] | TAGS
#region-us
| ## Overview
Original dataset here.
This dataset has been proposed in Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation.
## Dataset curation
This version of the dataset does not include the 'type-of-inference' "KG" as its label set is
'[1, 2, 3, 4, 5]' while here we focus ... | [
"## Overview\nOriginal dataset here.\n\nThis dataset has been proposed in Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation.",
"## Dataset curation\nThis version of the dataset does not include the 'type-of-inference' \"KG\" as its label set is \n'[1, 2, 3, 4, 5]' while... | [
"TAGS\n#region-us \n",
"## Overview\nOriginal dataset here.\n\nThis dataset has been proposed in Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation.",
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"passage: TAGS\n#region-us \n## Overview\nOriginal dataset here.\n\nThis dataset has been proposed in Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation."
] |
bbf6138e30cff48af0b9fa46ed710f68400dde85 | This dataset contains IMDB Ratings of various movies of different languages. This dataset also contains the number of votes each movies received | Meena/imdb_ratings_table | [
"region:us"
] | 2022-04-25T07:59:04+00:00 | {} | 2022-04-25T08:25:49+00:00 | [] | [] | TAGS
#region-us
| This dataset contains IMDB Ratings of various movies of different languages. This dataset also contains the number of votes each movies received | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
fbd6fcc5c3b8dc79ad26eaced52d7f04c6fea6d7 | ## Overview
Original dataset page [here](https://abhilasharavichander.github.io/NLI_StressTest/) and dataset available [here](https://drive.google.com/open?id=1faGA5pHdu5Co8rFhnXn-6jbBYC2R1dhw).
## Dataset curation
Added new column `label` with encoded labels with the following mapping
```
{"entailment": 0, "neutra... | pietrolesci/stress_tests_nli | [
"region:us"
] | 2022-04-25T08:21:50+00:00 | {} | 2022-04-25T08:32:28+00:00 | [] | [] | TAGS
#region-us
| ## Overview
Original dataset page here and dataset available here.
## Dataset curation
Added new column 'label' with encoded labels with the following mapping
and the columns with parse information are dropped as they are not well formatted.
Also, the name of the file from which each instance comes is added in t... | [
"## Overview\n\nOriginal dataset page here and dataset available here.",
"## Dataset curation\nAdded new column 'label' with encoded labels with the following mapping\n\n\n\nand the columns with parse information are dropped as they are not well formatted.\n\nAlso, the name of the file from which each instance co... | [
"TAGS\n#region-us \n",
"## Overview\n\nOriginal dataset page here and dataset available here.",
"## Dataset curation\nAdded new column 'label' with encoded labels with the following mapping\n\n\n\nand the columns with parse information are dropped as they are not well formatted.\n\nAlso, the name of the file fr... | [
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"passage: TAGS\n#region-us \n## Overview\n\nOriginal dataset page here and dataset available here.## Dataset curation\nAdded new column 'label' with encoded labels with the following mapping\n\n\n\nand the columns with parse information are dropped as they are not well formatted.\n\nAlso, the name of the file from ... |
8526f3a347c2d5760dc79a3dbe88134cc89c36b9 | ## Overview
Original dataset available [here](https://github.com/jimmycode/gen-debiased-nli#training-with-our-datasets).
```latex
@inproceedings{gen-debiased-nli-2022,
title = "Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets",
author = "Wu, Yuxiang and
Gardner, M... | pietrolesci/gen_debiased_nli | [
"region:us"
] | 2022-04-25T08:35:37+00:00 | {} | 2022-04-25T08:49:52+00:00 | [] | [] | TAGS
#region-us
| ## Overview
Original dataset available here.
## Dataset curation
No curation.
## Code to create the dataset
| [
"## Overview\nOriginal dataset available here.",
"## Dataset curation\nNo curation.",
"## Code to create the dataset"
] | [
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"## Dataset curation\nNo curation.",
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"passage: TAGS\n#region-us \n## Overview\nOriginal dataset available here.## Dataset curation\nNo curation.## Code to create the dataset"
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48d27a285f1919f3f7e6cd53b6a07fb13a238efb | ## Overview
Original dataset available [here](https://github.com/krandiash/gpt3-nli). Debiased dataset generated with GPT-3.
## Dataset curation
All string columns are stripped. Labels are encoded with the following mapping
```
{"entailment": 0, "neutral": 1, "contradiction": 2}
```
## Code to create the dataset
`... | pietrolesci/gpt3_nli | [
"region:us"
] | 2022-04-25T08:49:23+00:00 | {} | 2022-04-25T09:17:45+00:00 | [] | [] | TAGS
#region-us
| ## Overview
Original dataset available here. Debiased dataset generated with GPT-3.
## Dataset curation
All string columns are stripped. Labels are encoded with the following mapping
## Code to create the dataset
| [
"## Overview\nOriginal dataset available here. Debiased dataset generated with GPT-3.",
"## Dataset curation\nAll string columns are stripped. Labels are encoded with the following mapping",
"## Code to create the dataset"
] | [
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cd38beddf8badad23b8224f515a35c5d53ae0a53 |
# Dataset Card for UK Selective Web Archive Classification Dataset
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instan... | TheBritishLibrary/web_archive_classification | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:multi-label-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
... | 2022-04-25T09:14:45+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["multi-class-classification... | 2023-05-04T11:59:29+00:00 | [] | [
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# Dataset Card for UK Selective Web Archive Classification Dataset
## 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
- Pers... | [
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429dde22805398bdd6cfece27284f53a44ed6e67 | ## Overview
Original dataset is available in the original [Github repo](https://github.com/tyliupku/nli-debiasing-datasets).
This dataset is a collection of NLI benchmarks constructed as described in the paper
[An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference](https://acl... | pietrolesci/robust_nli | [
"region:us"
] | 2022-04-25T10:43:30+00:00 | {} | 2022-04-25T10:45:07+00:00 | [] | [] | TAGS
#region-us
| Overview
--------
Original dataset is available in the original Github repo.
This dataset is a collection of NLI benchmarks constructed as described in the paper
An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference
published at CoNLL 2020.
Dataset curation
--------------... | [] | [
"TAGS\n#region-us \n"
] | [
6
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"passage: TAGS\n#region-us \n"
] |
8ede2d7bf4531a7b210c793fe7b9e483b871c8f5 | This is part of `robust_NLI`but since there seems to be a bug when loading and downloading
`DatasetDict` containing datasets with different configurations, I loaded the datasets with
the differing configs as standalone datasets.
Issue here: [https://github.com/huggingface/datasets/issues/4211](https://github.com/huggi... | pietrolesci/robust_nli_li_ts | [
"region:us"
] | 2022-04-25T10:48:57+00:00 | {} | 2022-04-25T10:49:51+00:00 | [] | [] | TAGS
#region-us
| This is part of 'robust_NLI'but since there seems to be a bug when loading and downloading
'DatasetDict' containing datasets with different configurations, I loaded the datasets with
the differing configs as standalone datasets.
Issue here: URL | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
338d9797bb910381f7493343991c1055d425b9c4 | This is part of `robust_NLI`but since there seems to be a bug when loading and downloading
`DatasetDict` containing datasets with different configurations, I loaded the datasets with
the differing configs as standalone datasets.
Issue here: [https://github.com/huggingface/datasets/issues/4211](https://github.com/huggi... | pietrolesci/robust_nli_is_sd | [
"region:us"
] | 2022-04-25T10:49:03+00:00 | {} | 2022-04-25T12:07:25+00:00 | [] | [] | TAGS
#region-us
| This is part of 'robust_NLI'but since there seems to be a bug when loading and downloading
'DatasetDict' containing datasets with different configurations, I loaded the datasets with
the differing configs as standalone datasets.
Issue here: URL | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
c47716065f1f2076c39c806dd7007027342da502 | # Python Subreddit
Dataset containing data scraped from the [Python subreddit](https://www.reddit.com/r/python). | jamescalam/reddit-python | [
"region:us"
] | 2022-04-25T11:29:25+00:00 | {} | 2022-04-25T11:41:35+00:00 | [] | [] | TAGS
#region-us
| # Python Subreddit
Dataset containing data scraped from the Python subreddit. | [
"# Python Subreddit\n\nDataset containing data scraped from the Python subreddit."
] | [
"TAGS\n#region-us \n",
"# Python Subreddit\n\nDataset containing data scraped from the Python subreddit."
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"passage: TAGS\n#region-us \n# Python Subreddit\n\nDataset containing data scraped from the Python subreddit."
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2e7504f0d4a70d6bf0373a39767ecd2f85ae0d9f | # Pretokenized GitHub Code Dataset
## Dataset Description
This is a pretokenized version of the Python files of the [GitHub Code dataset](https://huggingface.co/datasets/lvwerra/github-code), that consists of 115M code files from GitHub in 32 programming languages. We tokenized the dataset using BPE Tokenizer trained ... | loubnabnl/tokenized-github-code-python | [
"region:us"
] | 2022-04-25T11:34:38+00:00 | {} | 2022-04-27T23:13:55+00:00 | [] | [] | TAGS
#region-us
| # Pretokenized GitHub Code Dataset
## Dataset Description
This is a pretokenized version of the Python files of the GitHub Code dataset, that consists of 115M code files from GitHub in 32 programming languages. We tokenized the dataset using BPE Tokenizer trained on code, available in this repo. Having a pretokenized ... | [
"# Pretokenized GitHub Code Dataset",
"## Dataset Description\nThis is a pretokenized version of the Python files of the GitHub Code dataset, that consists of 115M code files from GitHub in 32 programming languages. We tokenized the dataset using BPE Tokenizer trained on code, available in this repo. Having a pre... | [
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"passage: TAGS\n#region-us \n# Pretokenized GitHub Code Dataset## Dataset Description\nThis is a pretokenized version of the Python files of the GitHub Code dataset, that consists of 115M code files from GitHub in 32 programming languages. We tokenized the dataset using BPE Tokenizer trained on code, available in t... |
8371e5cf43c3564daa1314ecf6086b58fcbf2178 | ## Overview
Original dataset available [here](https://github.com/sheng-z/JOCI/tree/master/data).
This dataset is the "full" JOCI dataset, which is the file named `joci.csv.zip`.
# Dataset curation
The following processing is applied,
- `label` column renamed to `original_label`
- creation of the `label` column usi... | pietrolesci/joci | [
"region:us"
] | 2022-04-25T12:32:52+00:00 | {} | 2022-04-25T12:33:08+00:00 | [] | [] | TAGS
#region-us
| ## Overview
Original dataset available here.
This dataset is the "full" JOCI dataset, which is the file named 'URL'.
# Dataset curation
The following processing is applied,
- 'label' column renamed to 'original_label'
- creation of the 'label' column using the following mapping, using common practices (1, 2)
- ... | [
"## Overview\n\nOriginal dataset available here. \nThis dataset is the \"full\" JOCI dataset, which is the file named 'URL'.",
"# Dataset curation\nThe following processing is applied,\n\n- 'label' column renamed to 'original_label'\n- creation of the 'label' column using the following mapping, using common pract... | [
"TAGS\n#region-us \n",
"## Overview\n\nOriginal dataset available here. \nThis dataset is the \"full\" JOCI dataset, which is the file named 'URL'.",
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82b6583887562130331c99bba2c994b44eae310f | ## Overview
Proposed by
```latex
@InProceedings{glockner_acl18,
author = {Glockner, Max and Shwartz, Vered and Goldberg, Yoav},
title = {Breaking NLI Systems with Sentences that Require Simple Lexical Inferences},
booktitle = {The 56th Annual Meeting of the Association for Computational Linguistics (ACL)}... | pietrolesci/breaking_nli | [
"region:us"
] | 2022-04-25T12:36:48+00:00 | {} | 2022-04-25T12:37:23+00:00 | [] | [] | TAGS
#region-us
| ## Overview
Proposed by
Original dataset available here.
## Dataset curation
Labels encoded with the following mapping '{"entailment": 0, "neutral": 1, "contradiction": 2}'
and made available in the 'label' column.
## Code to create the dataset
| [
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] |
e39c4231c5c09a3ee1d3fd9e9bdfab466a6254f6 | ## Overview
Original dataset available [here](https://people.ict.usc.edu/~gordon/copa.html).
Current dataset extracted from [this repo](https://github.com/felipessalvatore/NLI_datasets).
This is the "full" dataset.
# Curation
Same curation as the one applied in [this repo](https://github.com/felipessalvatore/NLI_dat... | pietrolesci/copa_nli | [
"region:us"
] | 2022-04-25T12:46:42+00:00 | {} | 2022-04-25T12:47:10+00:00 | [] | [] | TAGS
#region-us
| Overview
--------
Original dataset available here.
Current dataset extracted from this repo.
This is the "full" dataset.
Curation
========
Same curation as the one applied in this repo, that is
from the original COPA format:
to the NLI format:
premise: My body cast a shadow over the grass, hypothesis: Th... | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
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bbafadc05d7fdc9c668653a5e81bb034a99af3d9 |
<p align="center"><img src="https://huggingface.co/datasets/cfilt/HiNER-collapsed/raw/main/cfilt-dark-vec.png" alt="Computation for Indian Language Technology Logo" width="150" height="150"/></p>
# Dataset Card for HiNER-original
[![Twitter Follow](https://img.shields.io/twitter/follow/cfiltnlp?color=1DA1F2&logo=twi... | cfilt/HiNER-original | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
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"multilinguality:monolingual",
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"language:hi",
"license:cc-by-sa-4.0",
"arxiv:2204.137... | 2022-04-25T12:55:19+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["hi"], "license": "cc-by-sa-4.0", "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognit... | 2023-03-07T16:42:05+00:00 | [
"2204.13743"
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"hi"
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| 
Dataset Card for HiNER-original
===============================
![Twitter Follow](URL
![Twitter Follow](URL
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Cre... | [
"### Dataset Summary\n\n\nThis dataset was created for the fundamental NLP task of Named Entity Recognition for the Hindi language at CFILT Lab, IIT Bombay. We gathered the dataset from various government information webpages and manually annotated these sentences as a part of our data collection strategy.\n\n\nNot... | [
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f88b0c931a28aac0824a988e60b76e5a83fd0da3 | annotations_creators:
- annotation
languages:
- pt-br
multilinguality:
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source_datasets:
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task_categories:
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# Dataset Card for c_corpus
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-lead... | rosimeirecosta/c_corpus | [
"region:us"
] | 2022-04-25T18:49:57+00:00 | {} | 2022-04-25T19:03:08+00:00 | [] | [] | TAGS
#region-us
| annotations_creators:
- annotation
languages:
- pt-br
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- ner
# Dataset Card for c_corpus
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks
- Languages
- Dataset Structure
- Data Instances
- Data Fields
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709fd56c19915e82eafc9bc39780e078daee5e00 |
# Dataset Card for [Dataset Name]
## 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-st... | AmirulOm/lottie-urls | [
"task_categories:image-segmentation",
"task_ids:instance-segmentation",
"annotations_creators:crowdsourced",
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] | 2022-04-25T21:45:19+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": [], "license": ["unknown"], "multilinguality": [], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["image-segmentation"], "task_ids": ["instance-segmentation"], "pretty_name": "lottie-uri"} | 2022-10-25T09:12:14+00:00 | [] | [] | TAGS
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# Dataset Card for [Dataset Name]
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- P... | [
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5d2ef1db3b12764224290882c360f966bdbb8aeb | # AutoTrain Dataset for project: isear_bert
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project isear_bert.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
... | crcb/autotrain-data-isear_bert | [
"task_categories:text-classification",
"region:us"
] | 2022-04-26T02:06:30+00:00 | {"task_categories": ["text-classification"]} | 2022-04-26T02:10:34+00:00 | [] | [] | TAGS
#task_categories-text-classification #region-us
| AutoTrain Dataset for project: isear\_bert
==========================================
Dataset Descritpion
-------------------
This dataset has been automatically processed by AutoTrain for project isear\_bert.
### Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
-----------------... | [
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ac97fe2b8719890567bea1fbcf9a5b22594bf88b | Dataset for API: https://github.com/eleldar/Translation | eleldar/different_sub_normal_datasets | [
"region:us"
] | 2022-04-26T05:32:15+00:00 | {} | 2022-06-16T10:19:15+00:00 | [] | [] | TAGS
#region-us
| Dataset for API: URL | [] | [
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06fbc6482522edcba63c38da575269369694c6f2 |
Original from https://gitlab.inria.fr/french-crows-pairs/acl-2022-paper-data-and-code/-/tree/main/.
# Data Statement for CrowS-Pairs-fr
> **How to use this document:**
> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people ... | BigScienceBiasEval/crows_pairs_multilingual | [
"language:en",
"language:fr",
"license:cc-by-sa-4.0",
"arxiv:2010.00133",
"region:us"
] | 2022-04-26T06:49:31+00:00 | {"language": ["en", "fr"], "license": "cc-by-sa-4.0"} | 2024-01-14T11:46:09+00:00 | [
"2010.00133"
] | [
"en",
"fr"
] | TAGS
#language-English #language-French #license-cc-by-sa-4.0 #arxiv-2010.00133 #region-us
|
Original from URL
# Data Statement for CrowS-Pairs-fr
> How to use this document:
> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach it. This could be someone looking at it in ten... | [
"# Data Statement for CrowS-Pairs-fr\n\n> How to use this document:\n> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach it. This could be someone looking at it in ten years, or i... | [
"TAGS\n#language-English #language-French #license-cc-by-sa-4.0 #arxiv-2010.00133 #region-us \n",
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5e93d44a6d6fb1fe35c41df7af170a8618b23e70 |
# Dataset Card for CrosswordQA
## 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 Field... | albertxu/CrosswordQA | [
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"license:unknown",
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] | 2022-04-26T07:05:14+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "task_categories": ["question-answering"], "task_ids": ["open-domain-qa"]} | 2022-10-29T22:45:36+00:00 | [] | [
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|
# Dataset Card for CrosswordQA
## 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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01020533529fc1cda0af7d99231eb96e7837f883 |
# Dataset Card for HuffPost
## 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... | khalidalt/HuffPost | [
"license:cc0-1.0",
"region:us"
] | 2022-04-26T08:32:57+00:00 | {"license": "cc0-1.0"} | 2023-05-19T17:35:08+00:00 | [] | [] | TAGS
#license-cc0-1.0 #region-us
|
# Dataset Card for HuffPost
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Persona... | [
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726a7cb5d4eab90c9035bd55b7bde3018c3bd06b |
### Dataset Summary
Kinopoisk movie reviews dataset (TOP250 & BOTTOM100 rank lists).
In total it contains 36,591 reviews from July 2004 to November 2012.
With following distribution along the 3-point sentiment scale:
- Good: 27,264;
- Bad: 4,751;
- Neutral: 4,576.
### Data Fields
Each sample contains the followin... | blinoff/kinopoisk | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:ru",
"region:us"
] | 2022-04-26T08:47:00+00:00 | {"language": ["ru"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pretty_name": "Kinopoisk"} | 2022-10-23T15:51:58+00:00 | [] | [
"ru"
] | TAGS
#task_categories-text-classification #task_ids-sentiment-classification #multilinguality-monolingual #size_categories-10K<n<100K #language-Russian #region-us
|
### Dataset Summary
Kinopoisk movie reviews dataset (TOP250 & BOTTOM100 rank lists).
In total it contains 36,591 reviews from July 2004 to November 2012.
With following distribution along the 3-point sentiment scale:
- Good: 27,264;
- Bad: 4,751;
- Neutral: 4,576.
### Data Fields
Each sample contains the followin... | [
"### Dataset Summary\n\nKinopoisk movie reviews dataset (TOP250 & BOTTOM100 rank lists).\n\nIn total it contains 36,591 reviews from July 2004 to November 2012.\n\nWith following distribution along the 3-point sentiment scale:\n- Good: 27,264;\n- Bad: 4,751;\n- Neutral: 4,576.",
"### Data Fields\n\nEach sample co... | [
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"passage: TAGS\n#task_categories-text-classification #task_ids-sentiment-classification #multilinguality-monolingual #size_categories-10K<n<100K #language-Russian #region-us \n### Dataset Summary\n\nKinopoisk movie reviews dataset (TOP250 & BOTTOM100 rank lists).\n\nIn total it contains 36,591 reviews from July 200... |
dec13d12c9fbda58367264342cba2376364aa2fe |
# Dataset Card for CANLI
### Dataset Summary
[CANLI: The Chinese Causative-Passive Homonymy Disambiguation: an Adversarial Dataset for NLI and a Probing Task](http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.460.pdf)
The disambiguation of causative-passive homonymy (CPH) is potentially tricky for machi... | sxu/CANLI | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"language:cn",
"license:afl-3.0",
"region:us"
] | 2022-04-26T12:31:34+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["cn"], "license": "afl-3.0", "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"]} | 2023-01-06T13:23:58+00:00 | [] | [
"cn"
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#annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-1K<n<10K #language-cn #license-afl-3.0 #region-us
|
# Dataset Card for CANLI
### Dataset Summary
CANLI: The Chinese Causative-Passive Homonymy Disambiguation: an Adversarial Dataset for NLI and a Probing Task
The disambiguation of causative-passive homonymy (CPH) is potentially tricky for machines, as the causative and the passive
are not distinguished by the senten... | [
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"### Dataset Summary\nCANLI: The Chinese Causative-Passive Homonymy Disambiguation: an Adversarial Dataset for NLI and a Probing Task\n\nThe disambiguation of causative-passive homonymy (CPH) is potentially tricky for machines, as the causative and the passive\nare not distinguished by... | [
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"### Dataset Summary\nCANLI: The Chinese Causative-Passive Homonymy Disambiguation: an Adversarial Da... | [
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7455d89e3da5e569b49d6ae1005fd52e89eb5087 |
# Dataset Card for "scientific_papers"
## 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-in... | ENM/dataset-prueba | [
"language:en",
"region:us"
] | 2022-04-26T17:11:02+00:00 | {"language": ["en"], "pretty_name": "ScientificPapers"} | 2022-10-25T09:12:20+00:00 | [] | [
"en"
] | TAGS
#language-English #region-us
| Dataset Card for "scientific\_papers"
=====================================
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... | [
"### Dataset Summary\n\n\nScientific papers datasets contains two sets of long and structured documents.\nThe datasets are obtained from ArXiv and PubMed OpenAccess repositories.\nBoth \"arxiv\" and \"pubmed\" have two features:\n\n\n* article: the body of the document, pagragraphs seperated by \"/n\".\n* abstract:... | [
"TAGS\n#language-English #region-us \n",
"### Dataset Summary\n\n\nScientific papers datasets contains two sets of long and structured documents.\nThe datasets are obtained from ArXiv and PubMed OpenAccess repositories.\nBoth \"arxiv\" and \"pubmed\" have two features:\n\n\n* article: the body of the document, pa... | [
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5fc63ea7788cd5b4edb6aeba801cdc7083cf07e9 |
# Dataset Card for the-reddit-nft-dataset
## 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](#dat... | SocialGrep/the-reddit-nft-dataset | [
"annotations_creators:lexyr",
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"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-04-26T18:52:29+00:00 | {"annotations_creators": ["lexyr"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": ["original"]} | 2022-07-01T16:52:49+00:00 | [] | [
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|
# Dataset Card for the-reddit-nft-dataset
## 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
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739825f9dbb674e44f71019730d403f626aac4be | POS tagging on the Universal Dependencies dataset
| aakanksha/udpos | [
"region:us"
] | 2022-04-27T00:16:51+00:00 | {} | 2022-04-27T18:21:57+00:00 | [] | [] | TAGS
#region-us
| POS tagging on the Universal Dependencies dataset
| [] | [
"TAGS\n#region-us \n"
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6
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578d877dd50601749b406d53805a4bd332b63091 | annotations_creators:
- found
language_creators:
- found
languages:
- zh
licenses:
- other-my-license
multilinguality:
- monolingual
pretty_name: symptom
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- word-sense-disambiguation | junliang/symptom | [
"region:us"
] | 2022-04-27T06:47:35+00:00 | {} | 2022-05-11T11:57:22+00:00 | [] | [] | TAGS
#region-us
| annotations_creators:
- found
language_creators:
- found
languages:
- zh
licenses:
- other-my-license
multilinguality:
- monolingual
pretty_name: symptom
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- word-sense-disambiguation | [] | [
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6
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a3fc132b1a1b550f82e0801e9ded2ae475b659ea |
# Dataset Card for LAMA: LAnguage Model Analysis - a dataset for probing and analyzing the factual and commonsense knowledge contained in pretrained language models.
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#suppo... | janck/bigscience-lama | [
"task_categories:text-retrieval",
"task_categories:text-classification",
"task_ids:fact-checking-retrieval",
"task_ids:text-scoring",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"language:en",
"license:cc-by-4.0",
"probing",
"re... | 2022-04-27T08:20:12+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["machine-generated"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": {"trex": ["1M<n<10M"]}, "task_categories": ["text-retrieval", "text-classification"], "task_ids": ["fact-checking-retrieval", "... | 2022-10-21T07:16:23+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-retrieval #task_categories-text-classification #task_ids-fact-checking-retrieval #task_ids-text-scoring #annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #language-English #license-cc-by-4.0 #probing #region-us
|
# Dataset Card for LAMA: LAnguage Model Analysis - a dataset for probing and analyzing the factual and commonsense knowledge contained in pretrained language models.
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances... | [
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96a234bd25c04939c4a79213eb764ae90e4d0d81 |
# Dataset Card for BANKING77
## 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)
... | PolyAI/banking77 | [
"task_categories:text-classification",
"task_ids:intent-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"li... | 2022-04-27T11:54:13+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["intent-classification"... | 2022-10-25T09:12:22+00:00 | [
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==========================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Data
+ Annotatio... | [
"### Dataset Summary\n\n\nDataset composed of online banking queries annotated with their corresponding intents.\n\n\nBANKING77 dataset provides a very fine-grained set of intents in a banking domain.\nIt comprises 13,083 customer service queries labeled with 77 intents.\nIt focuses on fine-grained single-domain in... | [
"TAGS\n#task_categories-text-classification #task_ids-intent-classification #task_ids-multi-class-classification #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-4.0 #arxiv-2... | [
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e504e76976d00dbe5d2ee3945bf6d42c65e2bd1d | # AutoTrain Dataset for project: Rule
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project Rule.
### Languages
The BCP-47 code for the dataset's language is zh.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"text":... | EAST/autotrain-data-Rule | [
"task_categories:text-classification",
"language:zh",
"region:us"
] | 2022-04-27T13:55:32+00:00 | {"language": ["zh"], "task_categories": ["text-classification"]} | 2022-10-25T09:12:41+00:00 | [] | [
"zh"
] | TAGS
#task_categories-text-classification #language-Chinese #region-us
| AutoTrain Dataset for project: Rule
===================================
Dataset Descritpion
-------------------
This dataset has been automatically processed by AutoTrain for project Rule.
### Languages
The BCP-47 code for the dataset's language is zh.
Dataset Structure
-----------------
### Data Instances
... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is zh.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis da... | [
"TAGS\n#task_categories-text-classification #language-Chinese #region-us \n",
"### Languages\n\n\nThe BCP-47 code for the dataset's language is zh.\n\n\nDataset Structure\n-----------------",
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904009d6f19d0d4eabb8f1471a92d49c839920d5 |
This dataset contains sentence-level formality annotations used in the 2016
TACL paper "An Empirical Analysis of Formality in Online Communication"
(Pavlick and Tetreault, 2016). It includes sentences from four genres (news,
blogs, email, and QA forums), all annotated by humans on Amazon Mechanical
Turk. The news and... | osyvokon/pavlick-formality-scores | [
"task_categories:text-classification",
"task_ids:text-scoring",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-3.0",
"region:us"
] | 2022-04-27T14:28:07+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-3.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["text-scoring"], "pretty_name": "Sente... | 2023-11-24T16:41:26+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #task_ids-text-scoring #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-3.0 #region-us
|
This dataset contains sentence-level formality annotations used in the 2016
TACL paper "An Empirical Analysis of Formality in Online Communication"
(Pavlick and Tetreault, 2016). It includes sentences from four genres (news,
blogs, email, and QA forums), all annotated by humans on Amazon Mechanical
Turk. The news and... | [
"## Contents\n\nThe annotated data files and number of lines in each are as follows:\n\n* 4977 answers -- Annotated sentences from a random sample of posts from the Yahoo! Answers forums: URL\n* 1821 blog -- Annotated sentences from the top 100 blogs listed on URL on October 31, 2009.\n* 1701 email -- Annotated sen... | [
"TAGS\n#task_categories-text-classification #task_ids-text-scoring #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-3.0 #region-us \n",
"## Contents\n\nThe annotated data files and number... | [
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"passage: TAGS\n#task_categories-text-classification #task_ids-text-scoring #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-3.0 #region-us \n## Contents\n\nThe annotated data files and num... |
2d04a4fde26d92fbed2ae7604677736e6b901a4d | This file contains news texts (sentences) belonging to different writing styles. The original dataset created by {*Upeksha, D., Wijayarathna, C., Siriwardena, M.,
Lasandun, L., Wimalasuriya, C., de Silva, N., and Dias, G. (2015). Implementing a corpus for Sinhala language. 01*}is processed and cleaned.
If you use this... | NLPC-UOM/Writing-style-classification | [
"task_categories:text-classification",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"language:si",
"license:mit",
"region:us"
] | 2022-04-27T17:08:07+00:00 | {"annotations_creators": [], "language_creators": ["crowdsourced"], "language": ["si"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": [], "source_datasets": [], "task_categories": ["text-classification"], "task_ids": [], "pretty_name": "sinhala-writing-style-classification"} | 2022-10-25T09:12:46+00:00 | [] | [
"si"
] | TAGS
#task_categories-text-classification #language_creators-crowdsourced #multilinguality-monolingual #language-Sinhala #license-mit #region-us
| This file contains news texts (sentences) belonging to different writing styles. The original dataset created by {*Upeksha, D., Wijayarathna, C., Siriwardena, M.,
Lasandun, L., Wimalasuriya, C., de Silva, N., and Dias, G. (2015). Implementing a corpus for Sinhala language. 01*}is processed and cleaned.
If you use this... | [] | [
"TAGS\n#task_categories-text-classification #language_creators-crowdsourced #multilinguality-monolingual #language-Sinhala #license-mit #region-us \n"
] | [
47
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"passage: TAGS\n#task_categories-text-classification #language_creators-crowdsourced #multilinguality-monolingual #language-Sinhala #license-mit #region-us \n"
] |
e220d18727665580a083db6162dd78f9e0f61438 |
Original from TODO.
# Data Statement for SHADES
> **How to use this document:**
> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach it. This could be someone looking at it in ten y... | bigscience-catalogue-data/bias-shades | [
"license:cc-by-sa-4.0",
"arxiv:2010.00133",
"region:us"
] | 2022-04-27T17:49:56+00:00 | {"license": "cc-by-sa-4.0"} | 2022-05-01T14:18:02+00:00 | [
"2010.00133"
] | [] | TAGS
#license-cc-by-sa-4.0 #arxiv-2010.00133 #region-us
|
Original from TODO.
# Data Statement for SHADES
> How to use this document:
> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach it. This could be someone looking at it in ten years... | [
"# Data Statement for SHADES\n\n> How to use this document:\n> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach it. This could be someone looking at it in ten years, or it could ... | [
"TAGS\n#license-cc-by-sa-4.0 #arxiv-2010.00133 #region-us \n",
"# Data Statement for SHADES\n\n> How to use this document:\n> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach i... | [
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"passage: TAGS\n#license-cc-by-sa-4.0 #arxiv-2010.00133 #region-us \n# Data Statement for SHADES\n\n> How to use this document:\n> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approac... |
f004a913f9170e5ff39e63f6172ee3ae918197c9 | mapping:
```
n01440764 tench, Tinca tinca
n01443537 goldfish, Carassius auratus
n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias
n01491361 tiger shark, Galeocerdo cuvieri
n01494475 hammerhead, hammerhead shark
n01496331 electric ray, crampfish, numbfish, torpedo
n01498041 st... | mrm8488/ImageNet1K-val | [
"region:us"
] | 2022-04-27T18:05:28+00:00 | {} | 2022-04-27T18:16:51+00:00 | [] | [] | TAGS
#region-us
| mapping:
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
006c4bc87abe217e728bbd7bfcd76f9f828c11e2 | mapping:
```
n01440764 tench, Tinca tinca
n01443537 goldfish, Carassius auratus
n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias
n01491361 tiger shark, Galeocerdo cuvieri
n01494475 hammerhead, hammerhead shark
n01496331 electric ray, crampfish, numbfish, torpedo
n01498041 st... | mrm8488/ImageNet1K-train | [
"region:us"
] | 2022-04-27T19:03:48+00:00 | {} | 2022-04-28T10:06:11+00:00 | [] | [] | TAGS
#region-us
| mapping:
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
ff6bd8e4b27c3543e4f8fe2108f32bb95a6f8740 |
# MASSIVE 1.1: A 1M-Example Multilingual Natural Language Understanding Dataset with 52 Typologically-Diverse Languages
## Table of Contents
- [Dataset Card for [Needs More Information]](#dataset-card-for-needs-more-information)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-descriptio... | AmazonScience/massive | [
"task_categories:text-classification",
"task_ids:intent-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:af-ZA",
"multilinguality:am-ET",
"multilinguality:ar-SA",
"multilinguality:az-AZ",
"multilinguality:b... | 2022-04-27T19:48:46+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "license": ["cc-by-4.0"], "multilinguality": ["af-ZA", "am-ET", "ar-SA", "az-AZ", "bn-BD", "ca-ES", "cy-GB", "da-DK", "de-DE", "el-GR", "en-US", "es-ES", "fa-IR", "fi-FI", "fr-FR", "he-IL", "hi-IN", "hu-HU", "hy-AM", "id-ID", "is-IS", "it-IT... | 2022-11-16T15:44:51+00:00 | [
"2204.08582"
] | [] | TAGS
#task_categories-text-classification #task_ids-intent-classification #task_ids-multi-class-classification #annotations_creators-expert-generated #language_creators-found #multilinguality-af-ZA #multilinguality-am-ET #multilinguality-ar-SA #multilinguality-az-AZ #multilinguality-bn-BD #multilinguality-ca-ES #multil... | MASSIVE 1.1: A 1M-Example Multilingual Natural Language Understanding Dataset with 52 Typologically-Diverse Languages
=====================================================================================================================
Table of Contents
-----------------
* [Dataset Card for](#dataset-card-for-needs... | [
"### Dataset Summary\n\n\nMASSIVE 1.1 is a parallel dataset of > 1M utterances across 52 languages with annotations for the Natural Language Understanding tasks of intent prediction and slot annotation. Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing the SLURP dataset, compos... | [
"TAGS\n#task_categories-text-classification #task_ids-intent-classification #task_ids-multi-class-classification #annotations_creators-expert-generated #language_creators-found #multilinguality-af-ZA #multilinguality-am-ET #multilinguality-ar-SA #multilinguality-az-AZ #multilinguality-bn-BD #multilinguality-ca-ES #... | [
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3a14d4d277b7ad97c668740aa9d0affadbf3fe8d | # CodeParrot 🦜 Dataset Cleaned and filtered (validation)
## Dataset Description
A dataset of Python files from Github. It is a more filtered version of the validation split [codeparrot-clean-valid](https://huggingface.co/datasets/codeparrot/codeparrot-clean-valid) of [codeparrot-clean](https://huggingface.co/dataset... | codeparrot/codeparrot-valid-more-filtering | [
"region:us"
] | 2022-04-27T19:57:16+00:00 | {} | 2022-06-21T16:56:02+00:00 | [] | [] | TAGS
#region-us
| # CodeParrot Dataset Cleaned and filtered (validation)
## Dataset Description
A dataset of Python files from Github. It is a more filtered version of the validation split codeparrot-clean-valid of codeparrot-clean. The additional filters aim at detecting configuration and test files, as well as outlier files that ar... | [
"# CodeParrot Dataset Cleaned and filtered (validation)",
"## Dataset Description\n\nA dataset of Python files from Github. It is a more filtered version of the validation split codeparrot-clean-valid of codeparrot-clean. The additional filters aim at detecting configuration and test files, as well as outlier fi... | [
"TAGS\n#region-us \n",
"# CodeParrot Dataset Cleaned and filtered (validation)",
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6,
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"passage: TAGS\n#region-us \n# CodeParrot Dataset Cleaned and filtered (validation)## Dataset Description\n\nA dataset of Python files from Github. It is a more filtered version of the validation split codeparrot-clean-valid of codeparrot-clean. The additional filters aim at detecting configuration and test files,... |
f6e726786732dbdb82a970091bb6d7ffe2251c80 | # CodeParrot 🦜 Dataset Cleaned and filtered (train)
## Dataset Description
A dataset of Python files from Github. It is a more filtered version of the train split [codeparrot-clean-train](https://huggingface.co/datasets/codeparrot/codeparrot-clean-train) of [codeparrot-clean](https://huggingface.co/datasets/codeparr... | codeparrot/codeparrot-train-more-filtering | [
"region:us"
] | 2022-04-27T21:28:47+00:00 | {} | 2022-06-21T16:54:51+00:00 | [] | [] | TAGS
#region-us
| # CodeParrot Dataset Cleaned and filtered (train)
## Dataset Description
A dataset of Python files from Github. It is a more filtered version of the train split codeparrot-clean-train of codeparrot-clean. The additional filters aim at detecting configuration and test files, as well as outlier files that are unlikely... | [
"# CodeParrot Dataset Cleaned and filtered (train)",
"## Dataset Description\n\nA dataset of Python files from Github. It is a more filtered version of the train split codeparrot-clean-train of codeparrot-clean. The additional filters aim at detecting configuration and test files, as well as outlier files that a... | [
"TAGS\n#region-us \n",
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"passage: TAGS\n#region-us \n# CodeParrot Dataset Cleaned and filtered (train)## Dataset Description\n\nA dataset of Python files from Github. It is a more filtered version of the train split codeparrot-clean-train of codeparrot-clean. The additional filters aim at detecting configuration and test files, as well a... |
c8e9269cd96a600bb340ee83ae45f46a02787a12 | # Dataset Card for Spanish IMDb Synopsis
## 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 Fields](#data-fiel... | mathigatti/spanish_imdb_synopsis | [
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:text2text-generation",
"annotations_creators:no-annotation",
"multilinguality:monolingual",
"language:es",
"license:apache-2.0",
"region:us"
] | 2022-04-27T23:54:42+00:00 | {"annotations_creators": ["no-annotation"], "language": ["es"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "task_categories": ["summarization", "text-generation", "text2text-generation"]} | 2022-10-25T09:12:53+00:00 | [] | [
"es"
] | TAGS
#task_categories-summarization #task_categories-text-generation #task_categories-text2text-generation #annotations_creators-no-annotation #multilinguality-monolingual #language-Spanish #license-apache-2.0 #region-us
| # Dataset Card for Spanish IMDb Synopsis
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Fields
- Dataset Creation
## Dataset Description
4969 movie synopsis from IMDb in spanish.
### Dataset Summary
[N/A]
### Languages
... | [
"# Dataset Card for Spanish IMDb Synopsis",
"## Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks and Leaderboards\n - Languages\n- Dataset Structure\n - Data Fields\n- Dataset Creation",
"## Dataset Description\n\n4969 movie synopsis from IMDb in spanish.",
"### Dataset Sum... | [
"TAGS\n#task_categories-summarization #task_categories-text-generation #task_categories-text2text-generation #annotations_creators-no-annotation #multilinguality-monolingual #language-Spanish #license-apache-2.0 #region-us \n",
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8ef331f75ebced42eceb7c5f53c47a3dafd8ef20 | hello
| TalTechNLP/VoxLingua107 | [
"license:cc-by-nc-4.0",
"region:us"
] | 2022-04-28T06:34:03+00:00 | {"license": "cc-by-nc-4.0"} | 2022-05-05T09:52:37+00:00 | [] | [] | TAGS
#license-cc-by-nc-4.0 #region-us
| hello
| [] | [
"TAGS\n#license-cc-by-nc-4.0 #region-us \n"
] | [
17
] | [
"passage: TAGS\n#license-cc-by-nc-4.0 #region-us \n"
] |
5d01e3f6a661d48e127ab5d7e3aaa0dc8331438a |
# Dataset Card for DanFEVER
## 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]... | strombergnlp/danfever | [
"task_categories:text-classification",
"task_ids:fact-checking",
"task_ids:natural-language-inference",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:da",
"license:cc-by-4.0",
"... | 2022-04-28T08:17:29+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["da"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["fact-checking", "natural-language-i... | 2022-10-25T20:42:40+00:00 | [] | [
"da"
] | TAGS
#task_categories-text-classification #task_ids-fact-checking #task_ids-natural-language-inference #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Danish #license-cc-by-4.0 #knowledge-verification #region-us
|
# Dataset Card for DanFEVER
## 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
- Consid... | [
"# Dataset Card for DanFEVER",
"## Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks\n - Languages\n- Dataset Structure\n - Data Instances\n - Data Fields\n - Data Splits\n- Dataset Creation\n - Curation Rationale\n - Source Data\n - Annotations\n - Personal and Sensitive ... | [
"TAGS\n#task_categories-text-classification #task_ids-fact-checking #task_ids-natural-language-inference #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Danish #license-cc-by-4.0 #knowledge-verification #regio... | [
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d766cb8a7497d0d507d81f5f681a8d58deedf495 |
# Dataset Card for broad_twitter_corpus
## 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... | strombergnlp/broad_twitter_corpus | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-04-28T08:58:09+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "paperswi... | 2022-07-01T14:46:36+00:00 | [] | [
"en"
] | TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-cc-by-4.0 #region-us
| Dataset Card for broad\_twitter\_corpus
=======================================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Data
+ ... | [
"### Dataset Summary\n\n\nThis is the Broad Twitter corpus, a dataset of tweets collected over stratified times, places and social uses. The goal is to represent a broad range of activities, giving a dataset more representative of the language used in this hardest of social media formats to process. Further, the BT... | [
"TAGS\n#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-cc-by-4.0 #region-us \n",
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"passage: TAGS\n#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-cc-by-4.0 #region-us \n### Dataset Summary\n\n\nThis is th... |
cc150b1a28983f4796ab486f6e1ef1d1047e523a |
# Dataset Card for "ipm-nel"
## 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)
... | strombergnlp/ipm_nel | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"language:en",
"license:cc-by-4.0",
"named-entity-linking",
"region:us"
] | 2022-04-28T09:06:10+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": [], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "paperswithcode_id":... | 2022-10-25T20:41:26+00:00 | [] | [
"en"
] | TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #named-entity-linking #region-us
| Dataset Card for "ipm-nel"
==========================
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\nThis data is for the task of named entity recognition and linking/disambiguation over tweets. It comprises\nthe addition of an entity URI layer on top of an NER-annotated tweet dataset. The task is to detect entities\nand then provide a correct link to them in DBpedia, thus disambiguating ... | [
"TAGS\n#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #named-entity-linking #region-us \n",
"### Dataset Summary\n\n\nThis data is for t... | [
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5e511fb803405e3b2454c77ba8928fe47557017e |
# Dataset Card for "shaj"
## 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)
-... | strombergnlp/shaj | [
"task_ids:hate-speech-detection",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"arxiv:2107.13592",
"doi:10.57967/hf/0514",
"region:us"
] | 2022-04-28T09:07:18+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text_classification"], "task_ids": ["hate-speech-detection", "text-classification-other-hate-speech-detection"], "pa... | 2022-06-14T13:03:37+00:00 | [
"2107.13592"
] | [] | TAGS
#task_ids-hate-speech-detection #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #arxiv-2107.13592 #doi-10.57967/hf/0514 #region-us
| Dataset Card for "shaj"
=======================
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 is an abusive/offensive language detection dataset for Albanian. The data is formatted\nfollowing the OffensEval convention, with three tasks:\n\n\n* Subtask A: Offensive (OFF) or not (NOT)\n* Subtask B: Untargeted (UNT) or targeted insult (TIN)\n* Subtask C: Type of target: individua... | [
"TAGS\n#task_ids-hate-speech-detection #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #arxiv-2107.13592 #doi-10.57967/hf/0514 #region-us \n",
"### Dataset Summary\n\n\nThis is an abusive/offensive language detectio... | [
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"passage: TAGS\n#task_ids-hate-speech-detection #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #arxiv-2107.13592 #doi-10.57967/hf/0514 #region-us \n### Dataset Summary\n\n\nThis is an abusive/offensive language detec... |
1075212523ac84e51b0fe6bc41fef4cd2bf695cc |
# Dataset Card for "dkstance / DAST"
## 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-ins... | strombergnlp/dkstance | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:da",
"license:cc-by-4.0",
"stance-detection",
"region:us"
] | 2022-04-28T09:07:39+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["da"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["fact-checking"], "paperswithcode_id... | 2022-10-25T20:45:42+00:00 | [] | [
"da"
] | TAGS
#task_categories-text-classification #task_ids-fact-checking #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Danish #license-cc-by-4.0 #stance-detection #region-us
| Dataset Card for "dkstance / DAST"
==================================
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 D... | [
"### Dataset Summary\n\n\nThis is an SDQC stance-annotated Reddit dataset for the Danish language generated within a thesis project. The dataset consists of over 5000 comments structured as comment trees and linked to 33 source posts.\n\n\nThe dataset is applicable for supervised stance classification and rumour ve... | [
"TAGS\n#task_categories-text-classification #task_ids-fact-checking #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Danish #license-cc-by-4.0 #stance-detection #region-us \n",
"### Dataset Summary\n\n\nThis ... | [
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d617a5df1b7ec95b1b290926e2d1f20c55d2c0b9 |
# Dataset Card for "polstance"
## 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... | strombergnlp/polstance | [
"task_categories:text-classification",
"task_ids:sentiment-analysis",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:da",
"license:cc-by-4.0",
"stance-detection",
"region:us"
] | 2022-04-28T09:08:13+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["da"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-analysis"], "paperswithcode_i... | 2022-10-25T20:42:18+00:00 | [] | [
"da"
] | TAGS
#task_categories-text-classification #task_ids-sentiment-analysis #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-n<1K #source_datasets-original #language-Danish #license-cc-by-4.0 #stance-detection #region-us
| Dataset Card for "polstance"
============================
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
+ Annot... | [
"### Dataset Summary\n\n\nPolitical stance in Danish. Examples represent statements by\npoliticians and are annotated for, against, or neutral to a given topic/article.",
"### Supported Tasks and Leaderboards\n\n\n*",
"### Languages\n\n\nDanish, bcp47: 'da-DK'\n\n\nDataset Structure\n-----------------",
"### ... | [
"TAGS\n#task_categories-text-classification #task_ids-sentiment-analysis #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-n<1K #source_datasets-original #language-Danish #license-cc-by-4.0 #stance-detection #region-us \n",
"### Dataset Summary\n\n\nPoli... | [
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8ad62edaaf487414e527d3f59edd6f6b52778b41 |
## 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](#data-instances)
- [Data S... | strombergnlp/bornholmsk | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:da",
"license:cc-by-4.0",
"region:us"
] | 2022-04-28T09:08:37+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["da"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["text-generation"], "task_ids": ["language-modeling"], "language_bcp47": ["... | 2022-10-25T20:40:56+00:00 | [] | [
"da"
] | TAGS
#task_categories-text-generation #task_ids-language-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-Danish #license-cc-by-4.0 #region-us
|
## 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
- Considerations for Using the Data
... | [
"## Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks\n - Languages\n- Dataset Structure\n - Data Instances\n - Data Fields\n - Data Splits\n- Dataset Creation\n - Curation Rationale\n - Source Data\n - Annotations\n - Personal and Sensitive Information\n- Considerations for... | [
"TAGS\n#task_categories-text-generation #task_ids-language-modeling #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-Danish #license-cc-by-4.0 #region-us \n",
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12ff587afc996106440872be6b3656218fad0e82 |
# Dataset Card for "twitter-pos-vcb"
## 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-ins... | strombergnlp/twitter_pos_vcb | [
"task_categories:token-classification",
"task_ids:part-of-speech",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-04-28T09:10:59+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["part-of-speech"], "paperswithcode... | 2022-10-25T20:42:56+00:00 | [] | [
"en"
] | TAGS
#task_categories-token-classification #task_ids-part-of-speech #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-original #language-English #license-cc-by-4.0 #region-us
| Dataset Card for "twitter-pos-vcb"
==================================
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 D... | [
"### Dataset Summary\n\n\nPart-of-speech information is basic NLP task. However, Twitter text\nis difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style.\nThis data is the vote-constrained bootstrapped data generate to support state-of-the-art results.\n\n\nThe data is about 1.... | [
"TAGS\n#task_categories-token-classification #task_ids-part-of-speech #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-original #language-English #license-cc-by-4.0 #region-us \n",
"### Dataset Summary\n\n\nPart-of-speech info... | [
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9cd7629e8632e2bf2185a7ae2309b8333248d57e |
# Dataset Card for "zulu-stance"
## 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-instanc... | strombergnlp/zulu_stance | [
"task_categories:text-classification",
"task_ids:fact-checking",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:zu",
"license:cc-by-4.0",
"st... | 2022-04-28T09:24:38+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["zu"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["fact-checking", "sentiment-classifi... | 2022-10-25T20:46:14+00:00 | [
"2205.03153"
] | [
"zu"
] | TAGS
#task_categories-text-classification #task_ids-fact-checking #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Zulu #license-cc-by-4.0 #stance-detection #arxiv-2205.03153 #reg... | Dataset Card for "zulu-stance"
==============================
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
+ A... | [
"### Dataset Summary\n\n\nThis is a stance detection dataset in the Zulu language. The data is translated to Zulu by Zulu native speakers, from English source texts.\n\n\nOur paper aims at utilizing this progress made for English to transfers that knowledge into other languages, which is a non-trivial task due to t... | [
"TAGS\n#task_categories-text-classification #task_ids-fact-checking #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-Zulu #license-cc-by-4.0 #stance-detection #arxiv-2205.0315... | [
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00e360ccbfa82f47287311387af1011f28f7e667 | You should know how to use it:)
Just in case, you can email me [mingzhe at nus.edu.sg] if you need any help. | Elfsong/clef_data | [
"region:us"
] | 2022-04-28T10:31:27+00:00 | {} | 2022-08-29T04:41:54+00:00 | [] | [] | TAGS
#region-us
| You should know how to use it:)
Just in case, you can email me [mingzhe at URL] if you need any help. | [] | [
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3fc0666c45d46d03a9bcd43f5e887dda2727328e |
Adapted from https://github.com/nicholas-leonard/word2vec | tomasmcz/word2vec_analogy | [
"license:apache-2.0",
"region:us"
] | 2022-04-28T10:58:50+00:00 | {"license": "apache-2.0"} | 2022-04-28T13:07:56+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
|
Adapted from URL | [] | [
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a1f29ad15db2594f69420a2abc845cc0bd09a311 |
Possibly a placeholder dataset for the original here: https://huggingface.co/datasets/bigscience-catalogue-data/bias-shades
# Data Statement for SHADES
> **How to use this document:**
> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is... | BigScienceBiasEval/bias-shades | [
"language:ar",
"language:en",
"language:fr",
"language:de",
"language:hi",
"language:ru",
"language:es",
"language:ta",
"license:cc-by-sa-4.0",
"region:us"
] | 2022-04-28T15:46:11+00:00 | {"language": ["ar", "en", "fr", "de", "hi", "ru", "es", "ta"], "license": "cc-by-sa-4.0"} | 2024-01-14T11:45:29+00:00 | [] | [
"ar",
"en",
"fr",
"de",
"hi",
"ru",
"es",
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] | TAGS
#language-Arabic #language-English #language-French #language-German #language-Hindi #language-Russian #language-Spanish #language-Tamil #license-cc-by-sa-4.0 #region-us
|
Possibly a placeholder dataset for the original here: URL
# Data Statement for SHADES
> How to use this document:
> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach it. This could... | [
"# Data Statement for SHADES\n\n> How to use this document:\n> Fill in each section according to the instructions. Give as much detail as you can, but there's no need to extrapolate. The goal is to help people understand your data when they approach it. This could be someone looking at it in ten years, or it could ... | [
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"passage: TAGS\n#language-Arabic #language-English #language-French #language-German #language-Hindi #language-Russian #language-Spanish #language-Tamil #license-cc-by-sa-4.0 #region-us \n# Data Statement for SHADES\n\n> How to use this document:\n> Fill in each section according to the instructions. Give as much d... |
f6eb365a04aacbd3b1055cf1cfea9edf1d6355f7 |
# Dataset Card for sci-definition
## 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 F... | talaugust/sci-definition | [
"region:us"
] | 2022-04-28T17:46:51+00:00 | {} | 2022-05-17T21:10:49+00:00 | [] | [] | TAGS
#region-us
|
# Dataset Card for sci-definition
## 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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96349b9bd7536aac67f892f5cf36197cd49ea722 | # Dataset Card for FactRuEval-2016
## Dataset Description
- **Point of Contact:** [Guskov Sergey](https://gusevski.com)
### Dataset Summary
Evaluation of [Named Entity Recognition](https://www.dialog-21.ru/media/3430/starostinaetal.pdf) and Fact Extraction Systems for Russian.
### Supported Tasks and Leaderboards
... | gusevski/factrueval2016 | [
"arxiv:2005.00614",
"region:us"
] | 2022-04-29T05:41:12+00:00 | {} | 2022-04-29T19:34:48+00:00 | [
"2005.00614"
] | [] | TAGS
#arxiv-2005.00614 #region-us
| Dataset Card for FactRuEval-2016
================================
Dataset Description
-------------------
* Point of Contact: Guskov Sergey
### Dataset Summary
Evaluation of Named Entity Recognition and Fact Extraction Systems for Russian.
### Supported Tasks and Leaderboards
For each of the tasks tagged fo... | [
"### Dataset Summary\n\n\nEvaluation of Named Entity Recognition and Fact Extraction Systems for Russian.",
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30d1fddbdb897932513e5974736b46c6fe6b6ceb | # AutoTrain Dataset for project: procell-expert
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project procell-expert.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```j... | Mim/autotrain-data-procell-expert | [
"task_categories:text-classification",
"region:us"
] | 2022-04-29T07:23:02+00:00 | {"task_categories": ["text-classification"]} | 2022-04-29T07:27:03+00:00 | [] | [] | TAGS
#task_categories-text-classification #region-us
| AutoTrain Dataset for project: procell-expert
=============================================
Dataset Descritpion
-------------------
This dataset has been automatically processed by AutoTrain for project procell-expert.
### Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
--------... | [
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474fa5e109d3675a21add2fc4cc0f201159545ec |
# WikiHow Entries
Contains wikiHow question, answer and summary in `.json` format. | soyasis/wikihow_small | [
"language:en",
"license:mit",
"region:us"
] | 2022-04-29T09:17:35+00:00 | {"language": "en", "license": "mit"} | 2022-04-29T09:24:34+00:00 | [] | [
"en"
] | TAGS
#language-English #license-mit #region-us
|
# WikiHow Entries
Contains wikiHow question, answer and summary in '.json' format. | [
"# WikiHow Entries\n\nContains wikiHow question, answer and summary in '.json' format."
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"passage: TAGS\n#language-English #license-mit #region-us \n# WikiHow Entries\n\nContains wikiHow question, answer and summary in '.json' format."
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0653eeaccbe5f0a9738220e0b1615f791da248b1 |
# Dataset Card for WMT21 Metrics Task
## 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](#datase... | muibk/wmt21_metrics_task | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:found",
"language_creators:machine-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:100K<n<1M",
"license:unknown",
"region:us"
] | 2022-04-29T09:52:47+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found", "machine-generated", "expert-generated"], "language": ["bn-hi", "cs-en", "de-en", "de-fr", "en-cs", "en-de", "en-ha", "en-is", "en-ja", "en-ru", "en-zh", "fr-de", "ha-en", "hi-bn", "is-en", "ja-en", "ru-en", "xh-zh", "zh-en", "zu-xh"], "licen... | 2022-07-12T12:13:25+00:00 | [] | [
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"ha-en",
"hi-bn",
"is-en",
"ja-en",
"ru-en",
"xh-zh",
"zh-en",
"zu-xh"
] | TAGS
#task_categories-translation #annotations_creators-expert-generated #language_creators-found #language_creators-machine-generated #language_creators-expert-generated #multilinguality-translation #size_categories-100K<n<1M #license-unknown #region-us
|
# Dataset Card for WMT21 Metrics Task
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
... | [
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3d793d9bfee3ee10313e3fa736c80d310c3a7209 |
# Dataset Card for Common Voice Corpus 9.0
## 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](#da... | mozilla-foundation/common_voice_9_0 | [
"task_categories:automatic-speech-recognition",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"source_datasets:extended|common_voice",
"license:cc0-1.0",
"arxiv:1912.06670",
"region:us"
] | 2022-04-29T15:49:21+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "license": ["cc0-1.0"], "multilinguality": ["multilingual"], "size_categories": {"ab": ["10K<n<100K"], "ar": ["100K<n<1M"], "as": ["n<1K"], "az": ["n<1K"], "ba": ["100K<n<1M"], "bas": ["1K<n<10K"], "be": ["100K<n<1M"], "bg": ["1K<n<10K"],... | 2023-07-29T15:00:12+00:00 | [
"1912.06670"
] | [] | TAGS
#task_categories-automatic-speech-recognition #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-multilingual #source_datasets-extended|common_voice #license-cc0-1.0 #arxiv-1912.06670 #region-us
|
# Dataset Card for Common Voice Corpus 9.0
## 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
- Personal and... | [
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8a8252c8c8e8c9a8f7ecaeb27bae1ac8b2313ab0 | Dataset containing city, country, region, and continents alongside their longitude and latitude co-ordinates. Cartesian coordinates are provided in x, y, z features. | jamescalam/world-cities-geo | [
"region:us"
] | 2022-04-29T15:54:48+00:00 | {} | 2022-04-29T17:34:46+00:00 | [] | [] | TAGS
#region-us
| Dataset containing city, country, region, and continents alongside their longitude and latitude co-ordinates. Cartesian coordinates are provided in x, y, z features. | [] | [
"TAGS\n#region-us \n"
] | [
6
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03f4a9bf2ec961792476aee76a9fa8722ff8dc1e |
# VQGAN Pairs
This dataset contains ~2.4 million image pairs intended for improvement of image quality in VQGAN predictions. Each pair consists of:
- A 512x512 crop of an image taken from Open Images.
- A 256x256 image encoded and decoded using VQGAN, corresponding to the same image crop as the original.
This is the... | dalle-mini/vqgan-pairs | [
"task_categories:other",
"source_datasets:Open Images",
"license:cc-by-4.0",
"license:cc-by-2.0",
"license:unknown",
"super-resolution",
"image-enhancement",
"region:us"
] | 2022-04-29T18:08:33+00:00 | {"license": ["cc-by-4.0", "cc-by-2.0", "unknown"], "source_datasets": ["Open Images"], "task_categories": ["other"], "task_ids": [], "pretty_name": "VQGAN Pairs", "tags": ["super-resolution", "image-enhancement"]} | 2022-10-25T12:56:57+00:00 | [] | [] | TAGS
#task_categories-other #source_datasets-Open Images #license-cc-by-4.0 #license-cc-by-2.0 #license-unknown #super-resolution #image-enhancement #region-us
|
# VQGAN Pairs
This dataset contains ~2.4 million image pairs intended for improvement of image quality in VQGAN predictions. Each pair consists of:
- A 512x512 crop of an image taken from Open Images.
- A 256x256 image encoded and decoded using VQGAN, corresponding to the same image crop as the original.
This is the... | [
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3b03eda1bd275edf2d9caaccf07d32d2c237c0d2 |
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Enzyme Commission labels.
The dataset is ported from Protinfer: https://github.com/google-research/proteinfer.
The EC-labels are extracted an... | DanielHesslow/SwissProt-EC | [
"Protein",
"Enzyme Commission",
"EC",
"region:us"
] | 2022-04-29T18:46:46+00:00 | {"language": ["protein sequences"], "datasets": ["Swissprot"], "tags": ["Protein", "Enzyme Commission", "EC"]} | 2022-04-30T14:12:33+00:00 | [] | [
"protein sequences"
] | TAGS
#Protein #Enzyme Commission #EC #region-us
|
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Enzyme Commission labels.
The dataset is ported from Protinfer: URL
The EC-labels are extracted and indexed, the mapping is provided in 'idx_... | [] | [
"TAGS\n#Protein #Enzyme Commission #EC #region-us \n"
] | [
17
] | [
"passage: TAGS\n#Protein #Enzyme Commission #EC #region-us \n"
] |
0db4e0ea3153c4caa5c49e7387f65b78a8996148 |
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with PFam labels.
The dataset is ported from Protinfer: https://github.com/google-research/proteinfer.
The Pfam-labels are extracted and indexed, ... | DanielHesslow/SwissProt-Pfam | [
"Protein",
"PFam",
"region:us"
] | 2022-04-29T18:52:56+00:00 | {"language": ["protein sequences"], "datasets": ["Swissprot"], "tags": ["Protein", "PFam"]} | 2022-04-30T14:15:55+00:00 | [] | [
"protein sequences"
] | TAGS
#Protein #PFam #region-us
|
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with PFam labels.
The dataset is ported from Protinfer: URL
The Pfam-labels are extracted and indexed, the mapping is provided in 'idx_mapping.jso... | [] | [
"TAGS\n#Protein #PFam #region-us \n"
] | [
13
] | [
"passage: TAGS\n#Protein #PFam #region-us \n"
] |
f64128a2e9e7a2756daacee8cc00e9b86142e19e |
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Gene Ontology labels.
The dataset is ported from Protinfer: https://github.com/google-research/proteinfer.
The GO-labels are extracted and in... | DanielHesslow/SwissProt-GO | [
"Protein",
"Gene Ontology",
"GO",
"region:us"
] | 2022-04-29T18:53:34+00:00 | {"language": ["protein sequences"], "datasets": ["Swissprot"], "tags": ["Protein", "Gene Ontology", "GO"]} | 2022-04-30T14:16:48+00:00 | [] | [
"protein sequences"
] | TAGS
#Protein #Gene Ontology #GO #region-us
|
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Gene Ontology labels.
The dataset is ported from Protinfer: URL
The GO-labels are extracted and indexed, the mapping is provided in 'idx_mapp... | [] | [
"TAGS\n#Protein #Gene Ontology #GO #region-us \n"
] | [
17
] | [
"passage: TAGS\n#Protein #Gene Ontology #GO #region-us \n"
] |
74c9c46cc27003593171ef289c364f42d0f4286b |
# Dataset
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Enzyme Commission labels.
The dataset is ported from Protinfer: https://github.com/google-research/proteinfer.
The leaf level EC-l... | lightonai/SwissProt-EC-leaf | [
"Protein",
"Enzyme Commission",
"region:us"
] | 2022-04-30T14:14:51+00:00 | {"language": ["protein sequences"], "datasets": ["Swissprot"], "tags": ["Protein", "Enzyme Commission"]} | 2022-05-05T08:54:42+00:00 | [] | [
"protein sequences"
] | TAGS
#Protein #Enzyme Commission #region-us
|
# Dataset
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Enzyme Commission labels.
The dataset is ported from Protinfer: URL
The leaf level EC-labels are extracted and indexed, the mappin... | [
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dc89ed1cc59ea92c19958c81c58070a2e95b02ab |
# Ukrainian Wikipedia Edits
### Dataset summary
A collection of over 5M sentence edits extracted from Ukrainian Wikipedia history revisions.
Edits were filtered by edit distance and sentence length. This makes them usable for grammatical error correction (GEC) or spellchecker models pre-training.
### Supported Ta... | osyvokon/wiki-edits-uk | [
"task_categories:other",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"multilinguality:translation",
"size_categories:1M<n<10M",
"source_datasets:original",
"license:cc-by-3.0",
"region:us"
] | 2022-04-30T17:21:55+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["uk-UA"], "license": ["cc-by-3.0"], "multilinguality": ["monolingual", "translation"], "size_categories": ["1M<n<10M"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "pretty_name": "Ukrainian ... | 2022-07-02T18:06:25+00:00 | [] | [
"uk-UA"
] | TAGS
#task_categories-other #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #multilinguality-translation #size_categories-1M<n<10M #source_datasets-original #license-cc-by-3.0 #region-us
|
# Ukrainian Wikipedia Edits
### Dataset summary
A collection of over 5M sentence edits extracted from Ukrainian Wikipedia history revisions.
Edits were filtered by edit distance and sentence length. This makes them usable for grammatical error correction (GEC) or spellchecker models pre-training.
### Supported Ta... | [
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"#... | [
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"passage: TAGS\n#task_categories-other #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #multilinguality-translation #size_categories-1M<n<10M #source_datasets-original #license-cc-by-3.0 #region-us \n# Ukrainian Wikipedia Edits### Dataset summary\n\nA collection of ov... |
c517b46f5b0574f716b9e3b173deb85d4db74236 | # AutoTrain Dataset for project: company
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project company.
### Languages
The BCP-47 code for the dataset's language is en.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"... | defector/autotrain-data-company | [
"language:en",
"region:us"
] | 2022-04-30T18:34:55+00:00 | {"language": ["en"]} | 2022-10-25T09:12:59+00:00 | [] | [
"en"
] | TAGS
#language-English #region-us
| AutoTrain Dataset for project: company
======================================
Dataset Descritpion
-------------------
This dataset has been automatically processed by AutoTrain for project company.
### Languages
The BCP-47 code for the dataset's language is en.
Dataset Structure
-----------------
### Data I... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------",
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"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis da... | [
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"### Data Instances\n\n\nA sample from this dataset looks as follows:",
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e8ae5ab634fd26487d0686488fd8abfb833ff283 | # Dataset Card for OSDG-CD
## 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)
-... | Filippo/osdg_cd | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-04-30T20:54:04+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "task_categories": ["text-classification"], "task_ids": ["natural-language-inference"], "pretty_name": "OSDG Community Da... | 2023-10-08T08:57:13+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #task_ids-natural-language-inference #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100K #language-English #license-cc-by-4.0 #region-us
| Dataset Card for OSDG-CD
========================
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\nThe OSDG Community Dataset (OSDG-CD) is a public dataset of thousands of text excerpts, which were validated by approximately 1,000 OSDG Community Platform (OSDG-CP) citizen scientists from over 110 countries, with respect to the Sustainable Development Goals (SDGs).\n\n\n\n> \n> NOTES\n> ... | [
"TAGS\n#task_categories-text-classification #task_ids-natural-language-inference #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100K #language-English #license-cc-by-4.0 #region-us \n",
"### Dataset Summary\n\n\nThe OSDG Community Dataset (OS... | [
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4ed58453467ac729dd815696584b8fad8dac4646 |
# RAFT submissions for my-raft-submission
## Submitting to the leaderboard
To make a submission to the [leaderboard](https://huggingface.co/spaces/ought/raft-leaderboard), there are three main steps:
1. Generate predictions on the unlabeled test set of each task
2. Validate the predictions are compatible with the e... | Anon126/my-raft-submission | [
"benchmark:raft",
"region:us"
] | 2022-05-01T09:48:53+00:00 | {"benchmark": "raft", "type": "prediction", "submission_name": "none"} | 2022-05-01T09:50:18+00:00 | [] | [] | TAGS
#benchmark-raft #region-us
|
# RAFT submissions for my-raft-submission
## Submitting to the leaderboard
To make a submission to the leaderboard, there are three main steps:
1. Generate predictions on the unlabeled test set of each task
2. Validate the predictions are compatible with the evaluation framework
3. Push the predictions to the Hub!
... | [
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c3d2d2159db2fb34ca8ef05cbf96f21addeeea8b | annotations_creators:
- automatic
language_creators:
- found
languages:
- es-AR
licenses:
- cc0-1.0
multilinguality:
- monolingual
paperswithcode_id:
pretty_name: wikiner
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
---
license: c... | NazaGara/wikiner-es | [
"region:us"
] | 2022-05-01T12:57:29+00:00 | {} | 2022-08-14T14:01:57+00:00 | [] | [] | TAGS
#region-us
| annotations_creators:
- automatic
language_creators:
- found
languages:
- es-AR
licenses:
- cc0-1.0
multilinguality:
- monolingual
paperswithcode_id:
pretty_name: wikiner
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
---
license: c... | [
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fed332421fbf9afc326f2490ec5bb49ffec180f3 |
# Dataset Card for ToxiGen
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-instances)
- [Additional Information](#additional-information)
- [Citation Information](... | skg/toxigen-data | [
"task_categories:text-classification",
"task_ids:hate-speech-detection",
"annotations_creators:expert-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"arxiv:2203.09509",
"region:us"
] | 2022-05-01T14:49:02+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["machine-generated"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["hate-speech-detection"], "pretty_name": "ToxiGen", "languages": ["en... | 2022-06-20T10:12:11+00:00 | [
"2203.09509"
] | [] | TAGS
#task_categories-text-classification #task_ids-hate-speech-detection #annotations_creators-expert-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #arxiv-2203.09509 #region-us
|
# Dataset Card for ToxiGen
## Table of Contents
- Dataset Description
- Dataset Summary
- Languages
- Dataset Structure
- Data Fields
- Additional Information
- Citation Information
## Sign up for Data Access
To access ToxiGen, first fill out this form.
## Dataset Description
- Repository: URL
- Paper: URL... | [
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"## Dataset Description\n\n- Re... | [
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b52b6486b38d74ddaf95626b15e0f0c50fa5e959 |
# Dataset Card for WIT
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Preprocessing](#dataset-preprocessing)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#lan... | google/wit | [
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"task_categories:image-to-text",
"task_ids:image-captioning",
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"language_creators:found",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"source_datasets:extended|wikipedia",
"lang... | 2022-05-02T10:22:32+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": ["af", "ar", "ast", "azb", "be", "bg", "bn", "br", "ca", "cs", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fr", "fy", "ga", "gl", "hr", "hu", "hy", "id", "it", "iw", "ja", "ka", "ko", "la", "lt", "lv", "mk... | 2022-07-04T09:47:07+00:00 | [
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#task_categories-text-retrieval #task_categories-image-to-text #task_ids-image-captioning #annotations_creators-machine-generated #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #source_datasets-extended|wikipedia #language-Afrikaans #language-Arabic #la... | Dataset Card for WIT
====================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Dataset Preprocessing
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rati... | [
"### Dataset Summary\n\n\nWikipedia-based Image Text (WIT) Dataset is a large multimodal multilingual dataset. WIT is composed of a curated set of 37.6 million entity rich image-text examples with 11.5 million unique images across 108 Wikipedia languages. Its size enables WIT to be used as a pretraining dataset for... | [
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82895de1f6c69a73fd9c4fdb2d6adff0a8fbc4b4 |
## Dataset Description
- **Homepage:** [SIL AI](https://ai.sil.org/)
- **Point of Contact:** [SIL AI email](mailto:idx_aqua@sil.org)
- **Source Data:** [Bloom Library](https://bloomlibrary.org/)
 ![sil-ai logo](https://s3.amazonaws.com/moo... | sil-ai/bloom-captioning | [
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"source_datasets:original",
"language:afr",
"language:af",
"language:aaa",
"language:abc",
"language:ada",
"language:adq",
... | 2022-05-02T13:24:03+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["afr", "af", "aaa", "abc", "ada", "adq", "aeu", "agq", "ags", "ahk", "aia", "ajz", "aka", "ak", "ame", "amh", "am", "amp", "amu", "ann", "aph", "awa", "awb", "azn", "azo", "bag", "bam", "bm", "baw", "bax", "bbk", "bcc... | 2022-12-10T02:16:13+00:00 | [] | [
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-------------------
* Homepage: SIL AI
* Point of Contact: SIL AI email
* Source Data: Bloom Library
!logo for Bloom Library !sil-ai logo
Dataset Summary
---------------
Bloom is free, open-source software and an associated website Bloom Library, app, and services developed by SIL Internatio... | [
"### Data Instances\n\n\nThe examples look like this for Hausa:\n\n\nThis would produce an output:\n\n\nTo download all of the images locally directory 'images', you can do something similar to the following:",
"### Data Fields\n\n\nThe metadata fields below are available:\n\n\n* image\\_id: a unique ID for the i... | [
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d9a3cfd6830ce040b34c1169d564227de87d5bf8 |
# Dataset Card for "crd3"
## 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)
-... | shanya/crd3 | [
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:... | 2022-05-02T14:01:40+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["summarization", "text-generation", "fill-mask"], "task_ids": ["... | 2022-10-25T09:13:08+00:00 | [] | [
"en"
] | TAGS
#task_categories-summarization #task_categories-text-generation #task_categories-fill-mask #task_ids-dialogue-modeling #annotations_creators-no-annotation #language_creators-crowdsourced #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-sa-4.0 #regi... | Dataset Card for "crd3"
=======================
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\nStorytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset.\nCritical Role is an unscripted, live-streamed show where a fixed group of people play Dungeons and Dragons, an open-ended role-playing game.\nThe dataset is collected from 159 Critical Role episodes transcribed to t... | [
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ff6d4fb32fd566d3a1fa20e946cba3234179465e |
# Dataset Card for WIT
## 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)
... | wikimedia/wit_base | [
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"size_categories:1M<n<10M",
"source_datasets:original",
"source_datasets:extended|wikipedia",
"langua... | 2022-05-02T15:08:58+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": ["af", "an", "ar", "arz", "ast", "az", "azb", "ba", "bar", "be", "bg", "bn", "br", "bs", "ca", "ce", "ceb", "ckb", "cs", "cv", "cy", "da", "de", "el", "en", "eo", "es", "et", "eu", "fa", "fi", "fil", "fr", "fy", "ga", "gl", "hi"... | 2022-11-04T15:09:33+00:00 | [
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# Dataset Card for WIT
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
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014711311cec8b5959350c373878a3311caeb764 |
# Dataset Card for ImageNet
## 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](... | imagenet-1k | [
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=========================
Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Supported Tasks
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Data
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+ Personal and ... | [
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e387ddf167f3eba99936cff89909ed6264f17e1f |
# Dataset Card for Czech Subjectivity Dataset
### Dataset Summary
Czech subjectivity dataset (Subj-CS) of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. See the paper description https://arxiv.org/abs/2204.13915
### Github
https://github.com/pauli31/czech-subjectivi... | pauli31/czech-subjectivity-dataset | [
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|
# Dataset Card for Czech Subjectivity Dataset
### Dataset Summary
Czech subjectivity dataset (Subj-CS) of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. See the paper description URL
### Github
URL
### Supported Tasks and Leaderboards
Subjectivity Analysis
### La... | [
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ffd50dace84cd36afc994d9193d988b30c200a5b |
# Dataset Card for Text-based NP Enrichment
## 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)
... | tne | [
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|
# Dataset Card for Text-based NP Enrichment
## 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 Infor... | [
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8b6e3f5b1dbd7244ae8251f5b1dc02da9146a04b |
# esCorpius Multilingual Raw
In the recent years, Transformer-based models have lead to significant advances in language modelling for natural language processing. However, they require a vast amount of data to be (pre-)trained and there is a lack of corpora in languages other than English. Recently, several initiati... | LHF/escorpius-mr | [
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"language:cs",... | 2022-05-03T17:49:47+00:00 | {"language": ["af", "ar", "bn", "ca", "cs", "da", "de", "el", "eu", "fa", "fi", "fr", "gl", "hi", "hr", "it", "ja", "ko", "mt", "nl", false, "oc", "pa", "pl", "pt", "ro", "sl", "sr", "sv", "tr", "uk", "ur"], "license": "cc-by-nc-nd-4.0", "multilinguality": ["multilingual"], "size_categories": ["100B<n<1T"], "source_dat... | 2023-05-11T21:29:21+00:00 | [
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# esCorpius Multilingual Raw
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# Dataset Card for Elsevier OA CC-By
## Table of Contents
- [Dataset Card for Elsevier OA CC-By](#dataset-card-for-elsevier-oa-cc-by)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supporte... | orieg/elsevier-oa-cc-by | [
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"language_creators:expert-generated",... | 2022-05-03T21:13:33+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["fill-mask", "summarization", "text-classification"], "task_... | 2022-07-01T14:59:58+00:00 | [
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==================================
Table of Contents
-----------------
* Dataset Card for Elsevier OA CC-By
+ Table of Contents
+ Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
+ Dataset Structure
- Data Instances
- Data Fields
... | [
"### Dataset Summary\n\n\nElsevier OA CC-By: This is a corpus of 40k (40,091) open access (OA) CC-BY articles from across Elsevier’s journals\nrepresenting a large scale, cross-discipline set of research data to support NLP and ML research. The corpus include full-text\narticles published in 2014 to 2020 and are ca... | [
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aee7fea371b991a01db75877fd23e37d381379c0 |
# Dataset Card for Ukhushn/home-depot
| Ukhushn/home-depot | [
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] | 2022-05-04T03:13:06+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["en"], "license": ["afl-3.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": [], "task_categories": ["sentence-similarity"], "task_ids": [], "pretty_name": "Ukhushn/home-depot", "language... | 2022-10-25T09:20:53+00:00 | [] | [
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|
# Dataset Card for Ukhushn/home-depot
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30a47cfa557c996f64903f01250799d453be6215 |
# Dataset Card for TextVQA
## 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](#... | textvqa | [
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"arxiv:1904.08920",... | 2022-05-05T05:44:56+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["visual-question-answering"], "task_ids": ["visual-question-answerin... | 2024-01-18T11:19:08+00:00 | [
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|
# Dataset Card for TextVQA
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
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# Dataset Card for [Electricity Transformer Temperature](https://github.com/zhouhaoyi/ETDataset)
## 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... | ett | [
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"license:... | 2022-05-05T11:12:41+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": [], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["time-series-forecasting"], "task_ids": ["univariate-time-series-forecasting", "... | 2024-01-18T11:19:09+00:00 | [
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# Dataset Card for Electricity Transformer Temperature
## 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
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... | [
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"passage: TAGS\n#task_categories-time-series-forecasting #task_ids-univariate-time-series-forecasting #task_ids-multivariate-time-series-forecasting #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #license-cc-by-4.0 #arxiv... |
7d5a48f50f02568d74fb4d0ca4c333684addc26d | # hotpotExtendedAno-LM
Version of hotpotExtended-Annotated formatted for Language Modelling. | ghomasHudson/hotpotExtendedAnoLM | [
"region:us"
] | 2022-05-05T13:07:24+00:00 | {} | 2022-05-05T13:09:26+00:00 | [] | [] | TAGS
#region-us
| # hotpotExtendedAno-LM
Version of hotpotExtended-Annotated formatted for Language Modelling. | [
"# hotpotExtendedAno-LM\n\nVersion of hotpotExtended-Annotated formatted for Language Modelling."
] | [
"TAGS\n#region-us \n",
"# hotpotExtendedAno-LM\n\nVersion of hotpotExtended-Annotated formatted for Language Modelling."
] | [
6,
28
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"passage: TAGS\n#region-us \n# hotpotExtendedAno-LM\n\nVersion of hotpotExtended-Annotated formatted for Language Modelling."
] |
7d23ca7e27a34288f7083619602a7a902938ead9 |
# Doctor Who Dialogues
This dataset contains all the script lines of Eleventh Doctor from Doctor Who which is a popular TV series. It can be processed and used for chatbots or relevant stuff. | truthisneverlinear/eleventh-doctor-scripts | [
"language:en",
"NLP",
"conservation",
"dialogue",
"region:us"
] | 2022-05-05T13:34:18+00:00 | {"language": "en", "tags": ["NLP", "conservation", "dialogue"]} | 2022-05-05T13:39:18+00:00 | [] | [
"en"
] | TAGS
#language-English #NLP #conservation #dialogue #region-us
|
# Doctor Who Dialogues
This dataset contains all the script lines of Eleventh Doctor from Doctor Who which is a popular TV series. It can be processed and used for chatbots or relevant stuff. | [
"# Doctor Who Dialogues\n\nThis dataset contains all the script lines of Eleventh Doctor from Doctor Who which is a popular TV series. It can be processed and used for chatbots or relevant stuff."
] | [
"TAGS\n#language-English #NLP #conservation #dialogue #region-us \n",
"# Doctor Who Dialogues\n\nThis dataset contains all the script lines of Eleventh Doctor from Doctor Who which is a popular TV series. It can be processed and used for chatbots or relevant stuff."
] | [
21,
44
] | [
"passage: TAGS\n#language-English #NLP #conservation #dialogue #region-us \n# Doctor Who Dialogues\n\nThis dataset contains all the script lines of Eleventh Doctor from Doctor Who which is a popular TV series. It can be processed and used for chatbots or relevant stuff."
] |
3997b23648a3961e1e566d976ac9310aa2ac5e20 |
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
<!-- - [Dataset Creation](#dataset-crea... | sil-ai/bloom-vist | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:afr",
"language:af",
"language:aaa",
"language:abc",
"language:ada",
"language:adq",
"language:aeu",
"language:ag... | 2022-05-05T15:25:54+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["afr", "af", "aaa", "abc", "ada", "adq", "aeu", "agq", "ags", "ahk", "aia", "ajz", "aka", "ak", "ame", "amh", "am", "amp", "amu", "ann", "aph", "awa", "awb", "azn", "azo", "bag", "bam", "bm", "baw", "bax", "bbk", "bcc... | 2022-12-06T19:37:53+00:00 | [] | [
"afr",
"af",
"aaa",
"abc",
"ada",
"adq",
"aeu",
"agq",
"ags",
"ahk",
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"ak",
"ame",
"amh",
"am",
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"amu",
"ann",
"aph",
"awa",
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"azn",
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"bag",
"bam",
"bm",
"baw",
"bax",
"bbk",
"bcc",
"bce",
"bec",
"bef",
"ben"... | TAGS
#annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-original #language-Afrikaans #language-Afrikaans #language-Ghotuo #language-Ambala Ayta #language-Adangme #language-Adangbe #language-Akeu #language-Aghem #language-... | Table of Contents
-----------------
* Dataset Description
+ Dataset Summary
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
Dataset Description
-------------------
* Homepage: SIL AI
* Point of Contact: SIL AI email
* Source Data: Bloom Library
!logo for Bloom Library !sil-... | [
"### Data Instances\n\n\nThe examples look like this for Hindi:\n\n\nThis would produce an output:",
"### Data Fields\n\n\nThe metadata fields below are available. In terms of licenses, all stories included in the current release are released under a Creative Commons license (even if the individual story metadata... | [
"TAGS\n#annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-original #language-Afrikaans #language-Afrikaans #language-Ghotuo #language-Ambala Ayta #language-Adangme #language-Adangbe #language-Akeu #language-Aghem #lan... | [
2757,
21,
153,
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] | [
"passage: "
] |
aa413c82b227dd25308df571e8b9d26e034cf2f7 | # Gcode (Geometric code)
## Details
**Usage:** 3D printing <br>
**Source:** Printables.com <br>
**Slicer:** Prusa <br>
**Category:** Art & Design <br>
**Subcategory:** Sculptures <br>
**Models:** 400 <br>
**Sliced files:** 740 (some models have many) <br>
**Data format:** txt <br>
**Train-test split:** 90/10 <br>
**S... | ablam/gcode | [
"region:us"
] | 2022-05-05T16:27:08+00:00 | {} | 2022-05-05T18:14:30+00:00 | [] | [] | TAGS
#region-us
| # Gcode (Geometric code)
## Details
Usage: 3D printing <br>
Source: URL <br>
Slicer: Prusa <br>
Category: Art & Design <br>
Subcategory: Sculptures <br>
Models: 400 <br>
Sliced files: 740 (some models have many) <br>
Data format: txt <br>
Train-test split: 90/10 <br>
Size: 11GB
| [
"# Gcode (Geometric code)",
"## Details\n\nUsage: 3D printing <br>\nSource: URL <br>\nSlicer: Prusa <br>\nCategory: Art & Design <br>\nSubcategory: Sculptures <br>\nModels: 400 <br>\nSliced files: 740 (some models have many) <br>\nData format: txt <br>\nTrain-test split: 90/10 <br>\nSize: 11GB"
] | [
"TAGS\n#region-us \n",
"# Gcode (Geometric code)",
"## Details\n\nUsage: 3D printing <br>\nSource: URL <br>\nSlicer: Prusa <br>\nCategory: Art & Design <br>\nSubcategory: Sculptures <br>\nModels: 400 <br>\nSliced files: 740 (some models have many) <br>\nData format: txt <br>\nTrain-test split: 90/10 <br>\nSize:... | [
6,
9,
89
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"passage: TAGS\n#region-us \n# Gcode (Geometric code)## Details\n\nUsage: 3D printing <br>\nSource: URL <br>\nSlicer: Prusa <br>\nCategory: Art & Design <br>\nSubcategory: Sculptures <br>\nModels: 400 <br>\nSliced files: 740 (some models have many) <br>\nData format: txt <br>\nTrain-test split: 90/10 <br>\nSize: 11... |
cdb6315d2d523ee509cb915eb37a2ac1f807da2f | # Dataset for the first <a href="https://ui.adsabs.harvard.edu/WIESP/" style="color:blue">Workshop on Information Extraction from Scientific Publications (WIESP/2022)</a>.
## Dataset Description
Datasets with text fragments from astrophysics papers, provided by the [NASA Astrophysical Data System](https://ui.adsabs.h... | adsabs/WIESP2022-NER | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-05-05T17:31:34+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": [], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "pretty_name": "... | 2023-05-17T18:42:32+00:00 | [] | [
"en"
] | TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #region-us
| # Dataset for the first <a href="URL style="color:blue">Workshop on Information Extraction from Scientific Publications (WIESP/2022)</a>.
## Dataset Description
Datasets with text fragments from astrophysics papers, provided by the NASA Astrophysical Data System with manually tagged astronomical facilities and other ... | [
"# Dataset for the first <a href=\"URL style=\"color:blue\">Workshop on Information Extraction from Scientific Publications (WIESP/2022)</a>.",
"## Dataset Description\nDatasets with text fragments from astrophysics papers, provided by the NASA Astrophysical Data System with manually tagged astronomical facilitie... | [
"TAGS\n#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #region-us \n",
"# Dataset for the first <a href=\"URL style=\"color:blue\">Wo... | [
87,
37,
309,
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3,
42
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"passage: TAGS\n#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #region-us \n# Dataset for the first <a href=\"URL style=\"color:blue\"... |
b7b7a73dbc74b681b384048716232b243ad25a99 |
# Dataset Card for ImageCoDe
To get started quickly, load descriptions via:
```
from datasets import load_dataset
examples = load_dataset('BennoKrojer/ImageCoDe')
```
And download `image_sets.zip` for all images sets (each directory consisting of 10 images).
## Dataset Description
- **Homepage & Leaderboard:** http... | BennoKrojer/ImageCoDe | [
"license:afl-3.0",
"arxiv:2203.15867",
"region:us"
] | 2022-05-05T20:50:13+00:00 | {"license": "afl-3.0"} | 2022-05-13T20:26:08+00:00 | [
"2203.15867"
] | [] | TAGS
#license-afl-3.0 #arxiv-2203.15867 #region-us
| Dataset Card for ImageCoDe
==========================
To get started quickly, load descriptions via:
And download 'image\_sets.zip' for all images sets (each directory consisting of 10 images).
Dataset Description
-------------------
* Homepage & Leaderboard: URL
* Repository: URL
* Paper: URL
* Point of Contac... | [
"### Dataset Summary\n\n\nWe introduce ImageCoDe, a vision-and-language benchmark that requires contextual language understanding in the form of pragmatics, temporality, long descriptions and visual nuances. The task: Given a detailed description, retrieve the target image among 10 minimally contrastive images. Ima... | [
"TAGS\n#license-afl-3.0 #arxiv-2203.15867 #region-us \n",
"### Dataset Summary\n\n\nWe introduce ImageCoDe, a vision-and-language benchmark that requires contextual language understanding in the form of pragmatics, temporality, long descriptions and visual nuances. The task: Given a detailed description, retrieve... | [
22,
102,
25,
11,
69
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"passage: TAGS\n#license-afl-3.0 #arxiv-2203.15867 #region-us \n### Dataset Summary\n\n\nWe introduce ImageCoDe, a vision-and-language benchmark that requires contextual language understanding in the form of pragmatics, temporality, long descriptions and visual nuances. The task: Given a detailed description, retri... |
3adb85380e4645c1fcf914a21ba4013410c0fa2b | # test-imagefolder-metadata | nateraw/test-imagefolder-metadata | [
"region:us"
] | 2022-05-05T23:18:59+00:00 | {} | 2022-05-06T00:51:57+00:00 | [] | [] | TAGS
#region-us
| # test-imagefolder-metadata | [
"# test-imagefolder-metadata"
] | [
"TAGS\n#region-us \n",
"# test-imagefolder-metadata"
] | [
6,
9
] | [
"passage: TAGS\n#region-us \n# test-imagefolder-metadata"
] |
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