artifact_type large_stringclasses 2
values | artifact_name large_stringlengths 5 123 | org large_stringlengths 2 42 | created_at large_stringdate 2022-03-02 00:00:00 2026-05-31 00:00:00 | last_modified large_stringdate 2020-07-16 00:00:00 2026-05-31 00:00:00 | languages listlengths 0 7.91k | license large_stringclasses 81
values | task_categories listlengths 0 47 | tags listlengths 2 7.92k | size_category large_stringclasses 11
values | downloads int64 0 262M | multilinguality listlengths 0 52 ⌀ | num_dataset_rows float64 0 194B ⌀ | disk_size float64 6 306,846B ⌀ | arxiv_ids listlengths 0 440 | readme large_stringlengths 0 13.4M |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dataset | ryanmarten/OpenThoughts-1k-sample | ryanmarten | 2025-08-30 | 2025-08-31 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2506.04178",
"region:us"
] | 1K<n<10K | 672,899 | null | 2,000 | 28,059,770 | [
"2506.04178"
] |
<p align="center">
<img src="open_thoughts.png" width="50%">
</p>
> [!NOTE]
> We have released a paper for OpenThoughts! See our paper [here](https://arxiv.org/abs/2506.04178).
<a href="https://github.com/bespokelabsai/curator/">
<img src="https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k/resolve/... |
dataset | Salesforce/wikitext | Salesforce | 2022-03-02 | 2024-01-04 | [
"en"
] | cc-by-sa-3.0 | [
"text-generation",
"fill-mask"
] | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:cc-by-sa-3.0... | 1M<n<10M | 1,348,717 | [
"monolingual"
] | 3,708,608 | 643,690,517 | [
"1609.07843"
] |
# Dataset Card for "wikitext"
## 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)... |
dataset | openai/openai_humaneval | openai | 2022-03-02 | 2024-01-04 | [
"en"
] | mit | [
"text2text-generation"
] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:mit",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"lib... | n<1K | 304,706 | [
"monolingual"
] | 164 | 91,617 | [
"2107.03374"
] |
# Dataset Card for OpenAI HumanEval
## Table of Contents
- [OpenAI HumanEval](#openai-humaneval)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Lang... |
dataset | HennyPr/ps2_hf2 | HennyPr | 2026-03-10 | 2026-04-05 | [] | null | [] | [
"size_categories:n<1K",
"format:text",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us"
] | n<1K | 804,649 | null | 1 | 3,502,252,975,093 | [] | |
dataset | nick007x/arxiv-papers | nick007x | 2025-09-29 | 2026-04-01 | [] | null | [] | [
"size_categories:1M<n<10M",
"format:parquet",
"modality:document",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1M<n<10M | 880,444 | null | 2,549,619 | 4,683,495,097,843 | [] | |
dataset | bluuebunny/arxiv_metadata_by_year | bluuebunny | 2024-04-07 | 2024-09-07 | [
"en"
] | apache-2.0 | [] | [
"language:en",
"license:apache-2.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"doi:10.57967/hf/2056",
"region:us"
] | 1M<n<10M | 1,648,059 | null | 2,551,074 | 2,055,017,918 | [] |
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## ... |
dataset | AlgorithmicResearchGroup/arxiv_s2orc_parsed | AlgorithmicResearchGroup | 2023-07-15 | 2024-09-04 | [
"en"
] | null | [
"text-generation",
"zero-shot-classification"
] | [
"task_categories:text-generation",
"task_categories:zero-shot-classification",
"language:en",
"size_categories:1M<n<10M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1M<n<10M | 462,682 | null | 1,671,614 | 43,545,306,389 | [] | # Dataset Card for "ArtifactAI/arxiv_s2orc_parsed"
## Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_s2orc_parsed
### Dataset Summary
AlgorithmicResearchGroup/arxiv_s2orc_parsed is a subset of the [AllenAI S2ORC dataset](https://github.com/allenai/s2orc), a general-purpose corp... |
dataset | librarian-bots/arxiv-metadata-snapshot | librarian-bots | 2023-10-08 | 2026-05-25 | [
"en"
] | cc0-1.0 | [
"text-generation",
"text-classification"
] | [
"task_categories:text-generation",
"task_categories:text-classification",
"language:en",
"license:cc0-1.0",
"size_categories:1M<n<10M",
"format:parquet",
"format:optimized-parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
"... | 1M<n<10M | 343,566 | null | 3,050,852 | 2,854,630,058 | [] | # Dataset Card for "arxiv-metadata-oai-snapshot"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
This is a mirror of the metadata portion of the arXiv [dataset](https://www.kaggle.com/datasets/Cornell-University/arxiv/versions/147).
... |
dataset | princeton-nlp/SWE-bench_Verified | princeton-nlp | 2024-08-13 | 2025-02-18 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 866,821 | null | 500 | 2,102,434 | [] |
**Dataset Summary**
SWE-bench Verified is a subset of 500 samples from the SWE-bench test set, which have been human-validated for quality. SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. See this post for more details on the human-validation process.
The dataset collects 500... |
dataset | Rowan/hellaswag | Rowan | 2022-03-02 | 2025-07-10 | [
"en"
] | null | [] | [
"language:en",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:1905.07830",
"region:us"
] | 10K<n<100K | 292,361 | null | 59,950 | 36,802,065 | [
"1905.07830"
] |
# Dataset Card for "hellaswag"
## 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... |
dataset | nyu-mll/glue | nyu-mll | 2022-03-02 | 2024-01-30 | [
"en"
] | other | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:acceptability-classification",
"task_ids:natural-language-inference",
"task_ids:semantic-similarity-scoring",
"task_ids:sentiment-classification",
"task_ids:text-scoring",
"annotations_creators:other",
"language_creators:other",
"multilinguality:monol... | 1M<n<10M | 485,230 | [
"monolingual"
] | 1,485,043 | 162,286,103 | [
"1804.07461"
] |
# Dataset Card for GLUE
## Table of Contents
- [Dataset Card for GLUE](#dataset-card-for-glue)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [ax](... |
dataset | SWE-bench/SWE-bench_Multilingual | SWE-bench | 2025-04-29 | 2025-08-26 | [
"en"
] | mit | [] | [
"language:en",
"license:mit",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 543,237 | null | 300 | 1,169,158 | [] | |
dataset | openai/gsm8k | openai | 2022-04-12 | 2026-03-23 | [
"en"
] | mit | [
"text-generation"
] | [
"benchmark:official",
"benchmark:eval-yaml",
"task_categories:text-generation",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:mit",
"size_categories:10K<n<100K",
"format:parquet",
"modal... | 10K<n<100K | 971,177 | [
"monolingual"
] | 17,584 | 5,900,352 | [
"2110.14168"
] |
# Dataset Card for GSM8K
## 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](#da... |
dataset | lavita/medical-qa-shared-task-v1-toy | lavita | 2023-07-20 | 2023-07-20 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 285,717 | null | 64 | 92,760 | [] | # Dataset Card for "medical-qa-shared-task-v1-toy"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
dataset | HuggingFaceM4/the_cauldron | HuggingFaceM4 | 2024-04-11 | 2024-05-06 | [] | null | [] | [
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:1603.07396",
"arxiv:2206.01718",
"arxiv:2208.05358",
"arxiv:1612.06890",
"arxiv:2310.00367",
"arxiv:1710.07300",
"arxiv:231... | 1M<n<10M | 732,073 | null | 1,880,992 | 168,904,013,601 | [
"1603.07396",
"2206.01718",
"2208.05358",
"1612.06890",
"2310.00367",
"1710.07300",
"2312.12241",
"1912.03098",
"2211.08545",
"2306.05425",
"1709.00103",
"2003.12462",
"1612.00837",
"2205.00363",
"2403.09029",
"2405.02246"
] | # Dataset Card for The Cauldron
## Dataset description
The Cauldron is part of the Idefics2 release.
It is a massive collection of 50 vision-language datasets (training sets only) that were used fo... |
dataset | cais/mmlu | cais | 2022-03-02 | 2024-03-08 | [
"en"
] | mit | [
"question-answering"
] | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:mit",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text"... | 100K<n<1M | 560,750 | [
"monolingual"
] | 231,400 | 270,035,224 | [
"2009.03300",
"2005.00700",
"2005.14165",
"2008.02275"
] |
# Dataset Card for MMLU
## 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)
... |
dataset | allenai/ai2_arc | allenai | 2022-03-02 | 2023-12-21 | [
"en"
] | cc-by-sa-4.0 | [
"question-answering"
] | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"task_ids:multiple-choice-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"size_categories:1K<n<10K",
"format:parquet",... | 1K<n<10K | 493,934 | [
"monolingual"
] | 7,787 | 1,222,570 | [
"1803.05457"
] |
# Dataset Card for "ai2_arc"
## 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)
... |
dataset | airtrain-ai/fineweb-edu-fortified | airtrain-ai | 2024-07-22 | 2024-08-08 | [
"en"
] | odc-by | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:odc-by",
"size_categories:100M<n<1B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2406.17557",
"arxiv:2109.07445",
"region:us"
] | 100M<n<1B | 403,765 | null | 322,250,000 | 1,744,881,253,858 | [
"2406.17557",
"2109.07445"
] |
# Fineweb-Edu-Fortified
<figure>
<img src="https://cdn-uploads.huggingface.co/production/uploads/646516d2200b583e1e50faf8/79yPdK79m9mA0cCz-3h4v.png" width="500" style="margin-left:auto; margin-right: auto"/>
<figcaption style="text-align: center; margin-left: auto; margin-right: auto; font-style: italic;">
The compo... |
dataset | bigcode/commitpackft | bigcode | 2023-06-27 | 2023-08-20 | [
"code"
] | mit | [] | [
"language:code",
"license:mit",
"size_categories:100K<n<1M",
"modality:text",
"library:datasets",
"library:mlcroissant",
"arxiv:2308.07124",
"region:us"
] | 100K<n<1M | 361,436 | null | 702,062 | 1,580,515,642 | [
"2308.07124"
] |
# Dataset Card for CommitPackFT
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Language... |
dataset | Narsil/image_dummy | Narsil | 2022-03-02 | 2021-08-26 | [] | null | [] | [
"size_categories:n<1K",
"modality:audio",
"modality:image",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us"
] | n<1K | 219,135 | null | 3 | 596,238 | [] | |
dataset | PeakStars/Math-Instruct | PeakStars | 2026-04-20 | 2026-04-20 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"format:optimized-parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | n<1K | 221,248 | null | 30 | 12,569 | [] | |
dataset | AlgorithmicResearchGroup/s2orc_arxiv | AlgorithmicResearchGroup | 2024-12-31 | 2026-04-11 | [
"en"
] | null | [
"text-generation",
"summarization",
"feature-extraction"
] | [
"task_categories:text-generation",
"task_categories:summarization",
"task_categories:feature-extraction",
"language:en",
"size_categories:1M<n<10M",
"modality:text",
"region:us",
"s2orc",
"arxiv",
"scientific-papers",
"nlp",
"research"
] | 1M<n<10M | 312,152 | null | 2,579,762 | 266,094,176,380 | [] |
# S2ORC ArXiv
A subset of the [Semantic Scholar Open Research Corpus (S2ORC)](https://github.com/allenai/s2orc) filtered to ArXiv papers. Contains 2.58 million parsed scientific papers with full text, abstracts, structured sections, figures, and citation metadata.
## Dataset Summary
| Statistic | Value |
|---------... |
dataset | stanfordnlp/imdb | stanfordnlp | 2022-03-02 | 2024-01-04 | [
"en"
] | other | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:other",
"size_categories:100K<n<1M",
"format:parquet",
"mo... | 100K<n<1M | 253,118 | [
"monolingual"
] | 100,000 | 83,455,823 | [] |
# Dataset Card for "imdb"
## 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)
-... |
dataset | ErikCikalleshi/new_york_times_news_2000_2007 | ErikCikalleshi | 2024-03-27 | 2024-03-27 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100K<n<1M | 280,861 | null | 552,499 | 1,592,420,125 | [] | |
dataset | fixie-ai/covost2 | fixie-ai | 2024-07-16 | 2024-08-27 | [] | null | [] | [
"size_categories:1M<n<10M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1M<n<10M | 254,816 | null | 5,651,526 | 240,252,229,048 | [] |
This is a partial copy of [CoVoST2](https://huggingface.co/datasets/facebook/covost2) dataset.
The main difference is that the audio data is included in the dataset, which makes usage easier and allows browsing the samples using HF Dataset Viewer.
The limitation of this method is that all audio samples of the `EN_XX`... |
dataset | HuggingFaceFW/fineweb-edu | HuggingFaceFW | 2024-05-28 | 2025-07-11 | [
"en"
] | odc-by | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:odc-by",
"size_categories:1B<n<10B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2406.17557",
"arxiv:2404.14219",
"arxiv:2401.10020",
... | 1B<n<10B | 635,221 | null | 3,496,736,741 | 5,835,742,481,176 | [
"2406.17557",
"2404.14219",
"2401.10020",
"2109.07445"
] |
# 📚 FineWeb-Edu
<center>
<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/wwRnEQydH9qdRtFofIE-A.png" alt="FineWeb-Edu: The finest collection of educational content the web has to offer">
</center>
> 1.3 trillion tokens of the finest educational data the 🌐 web has to offe... |
dataset | jat-project/jat-dataset | jat-project | 2023-08-29 | 2024-02-16 | [] | apache-2.0 | [
"reinforcement-learning",
"text-generation",
"question-answering"
] | [
"task_categories:reinforcement-learning",
"task_categories:text-generation",
"task_categories:question-answering",
"annotations_creators:found",
"annotations_creators:machine-generated",
"source_datasets:conceptual-captions",
"source_datasets:ok-vqa",
"source_datasets:oscar",
"license:apache-2.0",
... | 100M<n<1B | 747,062 | null | 258,457,671 | 1,086,293,204,067 | [
"2402.09844",
"2303.03915"
] |
# JAT Dataset
## Dataset Description
The Jack of All Trades (JAT) dataset combines a wide range of individual datasets. It includes expert demonstrations by expert RL agents, image and caption pairs, textual data and more. The JAT dataset is part of the JAT project, which aims to build a multimodal generalist agent.... |
dataset | japanese-asr/whisper_transcriptions.reazon_speech_all | japanese-asr | 2024-09-07 | 2024-09-14 | [] | null | [] | [
"size_categories:10M<n<100M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10M<n<100M | 455,496 | null | 17,347,033 | 2,519,801,172,928 | [] | |
dataset | wikimedia/wikipedia | wikimedia | 2022-03-02 | 2024-01-09 | [
"ab",
"ace",
"ady",
"af",
"alt",
"am",
"ami",
"an",
"ang",
"anp",
"ar",
"arc",
"ary",
"arz",
"as",
"ast",
"atj",
"av",
"avk",
"awa",
"ay",
"az",
"azb",
"ba",
"ban",
"bar",
"bbc",
"bcl",
"be",
"bg",
"bh",
"bi",
"bjn",
"blk",
"bm",
"bn",
"bo",
... | cc-by-sa-3.0 | [
"text-generation",
"fill-mask"
] | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"language:ab",
"language:ace",
"language:ady",
"language:af",
"language:alt",
"language:am",
"language:ami",
"language:an",
"language:ang",
"language:anp",
"... | 10M<n<100M | 247,316 | null | 61,614,907 | 71,792,022,791 | [] |
# Dataset Card for Wikimedia Wikipedia
## 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](#datas... |
dataset | utter-project/EuroWeb-2512 | utter-project | 2026-02-03 | 2026-02-09 | [] | null | [] | [
"size_categories:1B<n<10B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2602.05879",
"region:us"
] | 1B<n<10B | 293,058 | null | 4,048,543,357 | 10,555,018,328,009 | [
"2602.05879"
] |
# EuroWeb-2512
EuroWeb is a dataset of collecting multilingual web data from various sources. It was processed with standard practices and then classified with [utter-project/EuroFilter-v1](https://huggingface.co/utter-project/EuroFilter-v1).
For more information read the [EuroLLM-22B: Technical Report](https://arxi... |
dataset | allenai/winogrande | allenai | 2022-03-02 | 2025-07-11 | [
"en"
] | null | [] | [
"language:en",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 241,145 | null | 81,442 | 4,618,916 | [] |
# Dataset Card for "winogrande"
## 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-instance... |
dataset | aps/super_glue | aps | 2022-03-02 | 2025-05-16 | [
"en"
] | other | [
"text-classification",
"token-classification",
"question-answering"
] | [
"task_categories:text-classification",
"task_categories:token-classification",
"task_categories:question-answering",
"task_ids:natural-language-inference",
"task_ids:word-sense-disambiguation",
"task_ids:coreference-resolution",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"lan... | 100K<n<1M | 198,654 | [
"monolingual"
] | 196,313 | 102,539,920 | [
"1905.00537"
] |
# Dataset Card for "super_glue"
## 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-instance... |
dataset | fineinstructions/fineinstructions_nemotron | fineinstructions | 2025-07-29 | 2026-01-30 | [
"en"
] | null | [] | [
"language:en",
"size_categories:1B<n<10B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2601.22146",
"region:us"
] | 1B<n<10B | 493,865 | null | 1,228,476,202 | 1,937,693,552,198 | [
"2601.22146"
] |
[](https://huggingface.co/fineinstructions)
**✨ Note:** For all FineInstructions resources please visit: https://huggingface.co/fineinstructions
----
This dataset is ~1B+ synthetic ... |
dataset | abisee/cnn_dailymail | abisee | 2022-03-02 | 2024-01-18 | [
"en"
] | apache-2.0 | [
"summarization"
] | [
"task_categories:summarization",
"task_ids:news-articles-summarization",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text"... | 100K<n<1M | 195,424 | [
"monolingual"
] | 935,913 | 2,511,133,332 | [] | # Dataset Card for CNN Dailymail 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](#data-... |
dataset | Kazimir-ai/text-to-image-prompts | Kazimir-ai | 2024-02-15 | 2024-02-15 | [
"en"
] | apache-2.0 | [] | [
"language:en",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"prompts",
"text-to-image",
"stable diffusion"
] | 10K<n<100K | 204,496 | null | 50,000 | 1,135,585 | [] | # The dataset of the most popular text-to-image prompts.
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** kazimir.ai
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** https://kazimir.ai
- **License:** apache-2.... |
dataset | google-research-datasets/mbpp | google-research-datasets | 2022-03-02 | 2024-01-04 | [
"en"
] | cc-by-4.0 | [
"text2text-generation"
] | [
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"size_categories:1K<n<10K",
"format:parquet",
"moda... | 1K<n<10K | 215,060 | [
"monolingual"
] | 1,401 | 361,723 | [
"2108.07732"
] |
# Dataset Card for Mostly Basic Python Problems (mbpp)
## Table of Contents
- [Dataset Card for Mostly Basic Python Problems (mbpp)](#dataset-card-for-mostly-basic-python-problems-(mbpp))
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summa... |
dataset | TIGER-Lab/arxiv-latex-5T | TIGER-Lab | 2025-04-05 | 2025-04-17 | [
"en"
] | apache-2.0 | [] | [
"language:en",
"license:apache-2.0",
"size_categories:10M<n<100M",
"format:webdataset",
"modality:image",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"region:us"
] | 10M<n<100M | 281,720 | null | 11,900 | 5,077,493,908,748 | [] |
The dataset used for https://github.com/TIGER-AI-Lab/ScholarCopilot. |
dataset | HuggingFaceH4/MATH-500 | HuggingFaceH4 | 2024-11-15 | 2025-12-15 | [
"en"
] | null | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 171,410 | null | 500 | 450,344 | [] |
# Dataset Card for MATH-500
<!-- Provide a quick summary of the dataset. -->
This dataset contains a subset of 500 problems from the MATH benchmark that OpenAI created in their _Let's Verify Step by Step_ paper. See their GitHub repo for the source file: https://github.com/openai/prm800k/tree/main?tab=readme-ov-file... |
dataset | TIGER-Lab/MMLU-Pro | TIGER-Lab | 2024-05-08 | 2026-05-02 | [
"en"
] | mit | [
"question-answering"
] | [
"benchmark:official",
"benchmark:eval-yaml",
"task_categories:question-answering",
"language:en",
"license:mit",
"size_categories:10K<n<100K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"arxiv:2406.0... | 10K<n<100K | 163,906 | null | 12,102 | 4,207,360 | [
"2406.01574"
] |
# MMLU-Pro Dataset
MMLU-Pro dataset is a more **robust** and **challenging** massive multi-task understanding dataset tailored to more rigorously benchmark large language models' capabilities. This dataset contains 12K complex questions across various disciplines.
|[**Github**](https://github.com/TIGER-AI-Lab/MMLU-... |
dataset | EleutherAI/hendrycks_math | EleutherAI | 2023-09-14 | 2025-01-12 | [] | mit | [] | [
"license:mit",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 161,404 | null | 12,500 | 4,890,090 | [] |
## Dataset Summary
MATH dataset from https://github.com/hendrycks/math
### Citation Information
```
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn... |
dataset | HuggingFaceFW/finephrase | HuggingFaceFW | 2026-02-15 | 2026-03-31 | [
"en"
] | odc-by | [
"text-generation"
] | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:machine-generated",
"language_creators:found",
"source_datasets:HuggingFaceFW/fineweb-edu/sample-350BT",
"language:en",
"license:odc-by",
"size_categories:1B<n<10B",
"modality:tabular",
"modality:text",
"regio... | 1B<n<10B | 400,661 | null | 1,015,005,264 | 5,161,648,526,469 | [] |
# Dataset Card for HuggingFaceFW/finephrase
## Dataset Summary
Synthetic data generated by [DataTrove](https://github.com/huggingface/datatrove):
- Model: [`HuggingFaceTB/SmolLM2-1.7B-Instruct`](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct) (`main`)
- Source dataset: [`HuggingFaceFW/fineweb-edu`](http... |
dataset | idegen/csts | idegen | 2025-04-29 | 2025-05-21 | [] | cc-by-4.0 | [] | [
"license:cc-by-4.0",
"size_categories:100M<n<1B",
"format:parquet",
"modality:tabular",
"modality:text",
"modality:timeseries",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2505.14596",
"doi:10.57967/hf/6689",
"region:us",
"timeseries",
"timeseries ... | 100M<n<1B | 199,910 | null | 825,857,015 | 9,761,652,794 | [
"2505.14596"
] | # CSTS - Correlation Structures in Time Series
- **Repository:** https://github.com/isabelladegen/corrclust-validation
- **Paper:** https://arxiv.org/abs/2505.14596
- **Demo:** https://colab.research.google.com/github/isabelladegen/corrclust-validation/blob/main/src/utils/hf_tooling/CSTS_HuggingFace_UsageExample.ipynb
... |
dataset | mlfoundations/MINT-1T-HTML | mlfoundations | 2024-07-21 | 2024-09-21 | [
"en"
] | cc-by-4.0 | [
"image-to-text",
"text-generation"
] | [
"task_categories:image-to-text",
"task_categories:text-generation",
"language:en",
"license:cc-by-4.0",
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2406.11271",
"region:us",
"multimodal"... | 100M<n<1B | 230,148 | null | 897,871 | 5,912,008,757,937 | [
"2406.11271"
] |
<h1 align="center">
🍃 MINT-1T:<br>Scaling Open-Source Multimodal Data by 10x:<br> A Multimodal Dataset with One Trillion Tokens
</h1>
🍃 MINT-1T is an open-source **M**ultimodal **INT**erleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additional... |
dataset | mlfoundations/dclm-baseline-1.0-parquet | mlfoundations | 2024-06-30 | 2024-07-19 | [
"en"
] | cc-by-4.0 | [] | [
"language:en",
"license:cc-by-4.0",
"size_categories:1B<n<10B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2406.11794",
"region:us"
] | 1B<n<10B | 687,700 | null | 965,502 | 7,419,668,280,688 | [
"2406.11794"
] | ## DCLM-baseline
***Note: this is an identical copy of https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0, where all the files have been mapped to a parquet format.***
DCLM-baseline is a 4T token / 3B document pretraining dataset that achieves strong performance on language model benchmarks.
Below are... |
dataset | VLM2Vec/MSR-VTT | VLM2Vec | 2025-04-07 | 2025-08-03 | [
"en"
] | null | [
"text-to-video",
"text-retrieval",
"video-classification"
] | [
"task_categories:text-to-video",
"task_categories:text-retrieval",
"task_categories:video-classification",
"language:en",
"size_categories:10K<n<100K",
"format:json",
"modality:tabular",
"modality:text",
"modality:video",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:... | 10K<n<100K | 224,537 | null | 17,010 | 2,269,138,279 | [] |
Clone from "friedrichor/MSR-VTT".
[MSRVTT](https://openaccess.thecvf.com/content_cvpr_2016/html/Xu_MSR-VTT_A_Large_CVPR_2016_paper.html) contains 10K video clips and 200K captions.
We adopt the standard `1K-A split` protocol, which was introduced in [JSFusion](https://openaccess.thecvf.com/content_ECCV_2018/html/You... |
dataset | rajpurkar/squad | rajpurkar | 2022-03-02 | 2024-03-04 | [
"en"
] | cc-by-sa-4.0 | [
"question-answering"
] | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:extended|wikipedia",
"language:en",
"license:cc-by-sa-4.0",
"size_categories:10K<n<100K"... | 10K<n<100K | 158,840 | [
"monolingual"
] | 98,169 | 16,286,997 | [
"1606.05250"
] |
# Dataset Card for SQuAD
## Table of Contents
- [Dataset Card for "squad"](#dataset-card-for-squad)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [L... |
dataset | applied-ai-018/pretraining_v1-omega_books | applied-ai-018 | 2024-07-31 | 2024-08-05 | [] | null | [] | [
"size_categories:100M<n<1B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100M<n<1B | 175,799 | null | 103,802,366 | 12,333,578,946,015 | [] | |
dataset | ieasybooks-org/prophet-mosque-library | ieasybooks-org | 2025-05-04 | 2025-05-14 | [
"ar"
] | mit | [
"image-to-text"
] | [
"task_categories:image-to-text",
"language:ar",
"license:mit",
"size_categories:10K<n<100K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 150,496 | null | 48,718 | null | [] |
# Prophet's Mosque Library
## 📖 Overview
[Prophet’s Mosque Library](https://alharamain.gov.sa/public/?page=page_299500) is one of the primary resources for Islamic books. It hosts more than 48,000 PDF books across over 70 categories.
In this dataset, we processed the original PDF files using Google Document AI APIs... |
dataset | PsiBotAI/SynData | PsiBotAI | 2026-04-21 | 2026-05-22 | [
"en"
] | cc-by-4.0 | [] | [
"language:en",
"license:cc-by-4.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:3d",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | 100K<n<1M | 176,647 | null | 449,363 | 29,260,329,421,214 | [] |
# SynData
[中文说明](https://huggingface.co/datasets/PsiBotAI/SynData/blob/main/README_zh.md)
## Demo
<video controls muted loop playsinline width="100%">
<source src="https://huggingface.co/datasets/PsiBotAI/SynData/resolve/main/assets/syndata-demo.mp4" type="video/mp4">
</video>
If the video cannot be displayed in... |
dataset | HuggingFaceFW/fineweb | HuggingFaceFW | 2024-04-18 | 2025-07-11 | [
"en"
] | odc-by | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:odc-by",
"size_categories:10B<n<100B",
"modality:tabular",
"modality:text",
"arxiv:2306.01116",
"arxiv:2109.07445",
"arxiv:2406.17557",
"doi:10.57967/hf/2493",
"region:us"
] | 10B<n<100B | 1,051,137 | null | 52,453,695,892 | 54,812,538,723,397 | [
"2306.01116",
"2109.07445",
"2406.17557"
] | # 🍷 FineWeb
<center>
<img src="https://huggingface.co/datasets/HuggingFaceFW/admin/resolve/main/fineweb-logo.png" alt="FineWeb: The finest collection of data the web has to offer">
</center>
> 15 trillion tokens of the finest data the 🌐 web has to offer
# Table of Contents
- [🍷 FineWeb](#-fineweb)
* [What i... |
dataset | adams-story/datacomp200m | adams-story | 2023-07-12 | 2023-07-19 | [] | null | [] | [
"size_categories:100M<n<1B",
"format:parquet",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100M<n<1B | 185,730 | null | 213,009,083 | 1,441,811,492,996 | [] | # Datacomp200m
This is a smaller version of the [datacomp_1b](https://huggingface.co/datasets/mlfoundations/datacomp_1b) dataset.
Filtering was done by taking all rows that had self similarity (inner product) above 0.32. This resulted in 213009083 (213 million) rows.
The results of the datacomp paper suggest that... |
dataset | baber/piqa | baber | 2025-03-14 | 2025-03-14 | [] | null | [] | [
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 148,118 | null | 21,035 | 3,436,787 | [] | |
dataset | gksriharsha/chitralekha | gksriharsha | 2023-11-29 | 2024-08-23 | [
"te"
] | mit | [
"image-to-text"
] | [
"task_categories:image-to-text",
"language:te",
"license:mit",
"size_categories:10M<n<100M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"doi:10.57967/hf/3403",
"region:us"
] | 10M<n<100M | 175,778 | null | 61,898,021 | 270,797,925,598 | [] |
# Chitralekha
## Dataset Details
### Dataset Version
Some of the fonts do not have proper letters/rendering of different telugu letter combinations. Those have been removed as much as I can find them. If there are any other mistakes that you notice, please raise an issue and I will try my best to look into it
##... |
dataset | mlfoundations/MINT-1T-ArXiv | mlfoundations | 2024-06-29 | 2024-09-19 | [
"en"
] | cc-by-4.0 | [
"image-to-text",
"text-generation"
] | [
"task_categories:image-to-text",
"task_categories:text-generation",
"language:en",
"license:cc-by-4.0",
"size_categories:1M<n<10M",
"format:webdataset",
"modality:image",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"arxiv:2406.11271",
"region:us",
"mul... | 1M<n<10M | 167,299 | null | 7,300 | 3,860,532,985,860 | [
"2406.11271"
] |
<h1 align="center">
🍃 MINT-1T:<br>Scaling Open-Source Multimodal Data by 10x:<br> A Multimodal Dataset with One Trillion Tokens
</h1>
🍃 MINT-1T is an open-source **M**ultimodal **INT**erleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additional... |
dataset | allenai/openbookqa | allenai | 2022-03-02 | 2024-01-04 | [
"en"
] | unknown | [
"question-answering"
] | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:unknown",
"size_categories:10K<n<1... | 10K<n<100K | 157,540 | [
"monolingual"
] | 11,914 | 1,403,637 | [] |
# Dataset Card for OpenBookQA
## 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)... |
dataset | jackkuo/arXiv-metadata-oai-snapshot | jackkuo | 2025-04-14 | 2025-04-14 | [
"en"
] | mit | [
"text-classification",
"summarization",
"text2text-generation",
"sentence-similarity",
"text-generation"
] | [
"task_categories:text-classification",
"task_categories:summarization",
"task_categories:sentence-similarity",
"task_categories:text-generation",
"language:en",
"license:mit",
"size_categories:1M<n<10M",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant... | 1M<n<10M | 148,263 | null | 2,710,806 | 4,621,344,695 | [] |
# About Dataset
- Dataset name: arXiv academic paper metadata
- Data source: https://arxiv.org/
- Submission date: 1986-04-25 ~ 2025-05-13 (data updated weekly)
- Number of papers: 2,710,806 (as of 2025.5.14)
- Fields included: title, author, abstract, journal information, DOI, etc.
- Data format: json
- Data volume... |
dataset | Idavidrein/gpqa | Idavidrein | 2023-11-27 | 2026-03-05 | [
"en"
] | cc-by-4.0 | [
"question-answering",
"text-generation"
] | [
"benchmark:official",
"benchmark:eval-yaml",
"task_categories:question-answering",
"task_categories:text-generation",
"language:en",
"license:cc-by-4.0",
"size_categories:1K<n<10K",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"... | 1K<n<10K | 141,229 | null | null | 8,713,216 | [
"2311.12022"
] |
# Dataset Card for GPQA
<!-- Provide a quick summary of the dataset. -->
GPQA is a multiple-choice, Q&A dataset of very hard questions written and validated by experts in biology, physics, and chemistry. When attempting questions out of their own domain (e.g., a physicist answers a chemistry question), these experts... |
dataset | timchen0618/bcp-traj-ext-formatted-v1 | timchen0618 | 2026-04-08 | 2026-04-08 | [] | mit | [] | [
"license:mit",
"size_categories:n<1K",
"format:parquet",
"format:optimized-parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"bcp",
"traj-ext",
"browsecomp-plus",
"seed0"
] | n<1K | 157,863 | null | 830 | 35,875,020 | [] |
# bcp-traj-ext-formatted-v1
Trajectories from seed0 (gpt-oss-120b, Qwen3-Embedding-8B, full split) formatted in the traj_ext style: trajectory_text is the serialized steps ([Reasoning]/[Tool call]/[Tool result]/[Final answer]), and formatted_prompt is the full QUERY_TEMPLATE_GIVEN_TRAJECTORY prompt ready to feed to t... |
dataset | CohereLabs/aya_collection | CohereLabs | 2024-01-31 | 2025-04-15 | [
"ace",
"afr",
"amh",
"ara",
"aze",
"ban",
"bbc",
"bel",
"bem",
"ben",
"bjn",
"bul",
"cat",
"ceb",
"ces",
"cym",
"dan",
"deu",
"ell",
"eng",
"epo",
"est",
"eus",
"fil",
"fin",
"fon",
"fra",
"gla",
"gle",
"glg",
"guj",
"hat",
"hau",
"heb",
"hin",
"... | apache-2.0 | [
"text-classification",
"summarization",
"translation"
] | [
"task_categories:text-classification",
"task_categories:summarization",
"task_categories:translation",
"language:ace",
"language:afr",
"language:amh",
"language:ara",
"language:aze",
"language:ban",
"language:bbc",
"language:bel",
"language:bem",
"language:ben",
"language:bjn",
"language... | 100M<n<1B | 167,546 | null | 513,755,590 | 155,397,150,051 | [
"2402.06619"
] |
****This dataset is uploaded in two places: here and additionally [here](https://huggingface.co/datasets/CohereLabs/aya_collection_language_split) as 'Aya Collection Language Split.' These datasets are identical in co... |
dataset | JianZhangAI/hoi4d-depth | JianZhangAI | 2025-01-31 | 2025-02-02 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:webdataset",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"region:us"
] | 1K<n<10K | 138,849 | null | 200 | 127,243,795,713 | [] | |
dataset | mvp-lab/LLaVA-OneVision-2-Data | mvp-lab | 2026-03-24 | 2026-05-11 | [
"en"
] | apache-2.0 | [
"video-text-to-text",
"visual-question-answering",
"image-text-to-text"
] | [
"task_categories:video-text-to-text",
"task_categories:visual-question-answering",
"task_categories:image-text-to-text",
"language:en",
"license:apache-2.0",
"size_categories:n<1K",
"format:parquet",
"format:optimized-parquet",
"modality:image",
"modality:text",
"modality:video",
"library:data... | n<1K | 194,784 | null | 24 | 66,575,112,910,817 | [] |
# LLaVA-OneVision-2-Data
Training data for the LLaVA-OneVision-2 multimodal model family, covering large-scale video and spatial reasoning corpora used in mid-training.
## Dataset Composition
| Subset | Format | Description |
|---|---|---|
| `mid_training_video/60s_rest/` | WebDataset (`.tar`) | 10,809 shards of ~6... |
dataset | MMInstruction/ArxivCap | MMInstruction | 2023-12-01 | 2024-10-03 | [
"en"
] | cc-by-4.0 | [
"image-to-text"
] | [
"task_categories:image-to-text",
"language:en",
"license:cc-by-4.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2403.00231",
"region:us",
"arxiv",
"multi-modal"
] | 100K<n<1M | 149,338 | null | 572,734 | 754,758,749,675 | [
"2403.00231"
] |
# Dataset Card for ArxivCap
## Table of Contents
- [Dataset Card for ArxivCap](#dataset-card-for-arxivcap)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Curation Process](#curation-process)
- [Dataset Structure](#datase... |
dataset | google/IFEval | google | 2023-12-22 | 2024-08-14 | [
"en"
] | apache-2.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2311.07911",
"region:us"
] | n<1K | 119,198 | null | 541 | 214,941 | [
"2311.07911"
] |
# Dataset Card for IFEval
<!-- Provide a quick summary of the dataset. -->
## Dataset Description
- **Repository:** https://github.com/google-research/google-research/tree/master/instruction_following_eval
- **Paper:** https://huggingface.co/papers/2311.07911
- **Leaderboard:** https://huggingface.co/spaces/open-ll... |
dataset | m-a-p/PIN-200M | m-a-p | 2024-05-25 | 2026-04-15 | [
"en",
"zh"
] | apache-2.0 | [] | [
"language:en",
"language:zh",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"arxiv:2406.13923",
"region:us",
"multimodal",
"interleaved"
] | 10K<n<100K | 192,998 | null | 68,084 | 306,845,854,390,689 | [
"2406.13923"
] |
# PIN-200M
A mini version of "PIN: A Knowledge-Intensive Dataset for Paired and Interleaved Multimodal Documents"
Paper: https://arxiv.org/abs/2406.13923
This dataset contains around **200M** samples in PIN format, with around **312** TB storage.
🚀 News
[ 2025.09.22 ] !NEW! 🔥 We have completed the final version... |
dataset | fancyzhx/ag_news | fancyzhx | 2022-03-02 | 2024-03-07 | [
"en"
] | unknown | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:topic-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:unknown",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library... | 100K<n<1M | 129,625 | [
"monolingual"
] | 127,600 | 19,829,511 | [] |
# Dataset Card for "ag_news"
## 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)
... |
dataset | ttj/metadata_arxiv | ttj | 2022-03-02 | 2021-08-05 | [] | null | [] | [
"size_categories:1M<n<10M",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1M<n<10M | 132,968 | null | 1,160,741 | 1,112,687,549 | [] | |
dataset | tatsu-lab/alpaca | tatsu-lab | 2023-03-13 | 2023-05-22 | [
"en"
] | cc-by-nc-4.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:cc-by-nc-4.0",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"instruction-finetuning"
] | 10K<n<100K | 111,357 | null | 52,002 | 24,256,428 | [] |
# Dataset Card for Alpaca
## Dataset Description
- **Homepage:** https://crfm.stanford.edu/2023/03/13/alpaca.html
- **Repository:** https://github.com/tatsu-lab/stanford_alpaca
- **Paper:**
- **Leaderboard:**
- **Point of Contact:** Rohan Taori
### Dataset Summary
Alpaca is a dataset of 52,000 instructions and d... |
dataset | princeton-nlp/SWE-bench_Lite | princeton-nlp | 2024-03-19 | 2025-03-03 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2310.06770",
"region:us"
] | n<1K | 111,014 | null | 323 | 1,245,072 | [
"2310.06770"
] |
### Dataset Summary
SWE-bench *Lite* is _subset_ of [SWE-bench](https://huggingface.co/datasets/princeton-nlp/SWE-bench), a dataset that tests systems’ ability to solve GitHub issues automatically. The dataset collects 300 test Issue-Pull Request pairs from 11 popular Python. Evaluation is performed by unit test verif... |
dataset | OpenSQZ/AutoMathText-V2 | OpenSQZ | 2025-08-20 | 2026-04-02 | [
"en",
"zh"
] | null | [
"text-generation",
"question-answering"
] | [
"task_categories:text-generation",
"task_categories:question-answering",
"language:en",
"language:zh",
"size_categories:10B<n<100B",
"modality:tabular",
"modality:text",
"arxiv:2402.07625",
"region:us",
"LLM",
"pretraining",
"finetuning",
"midtraining",
"reasoning",
"STEM",
"math"
] | 10B<n<100B | 197,191 | null | 15,243,199,677 | 7,349,253,089,284 | [
"2402.07625"
] |
# 🚀 AutoMathText-V2: A 2.46 Trillion Token AI-Curated STEM Pretraining Dataset
[](https://arxiv.org/abs/2402.07625)
[](https://iiis-ai.github.io/AutoMathText-V2)
[![Technical Report](https... |
dataset | m-a-p/FineFineWeb | m-a-p | 2024-12-14 | 2024-12-19 | [
"en"
] | apache-2.0 | [
"text-classification",
"text2text-generation",
"text-generation"
] | [
"task_categories:text-classification",
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"size_categories:1B<n<10B",
"modality:tabular",
"modality:text",
"region:us"
] | 1B<n<10B | 773,895 | null | 1,646,140 | 23,156,388,392,763 | [] | # FineFineWeb: A Comprehensive Study on Fine-Grained Domain Web Corpus
arXiv: Coming Soon
Project Page: Coming Soon
Blog: Coming Soon
## Data Statistics
| Domain (#tokens/#samples) | Iteration 1 Tokens | Iteration 2 Tokens | Iteration 3 Tokens | Total Tokens | Iteration 1 Count | Iteration 2 Count | Iteration 3 C... |
dataset | LanguageBind/Open-Sora-Plan-v1.1.0 | LanguageBind | 2024-05-16 | 2024-07-01 | [] | mit | [] | [
"license:mit",
"size_categories:100K<n<1M",
"format:webdataset",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"region:us"
] | 100K<n<1M | 111,891 | null | 100 | 8,921,250,782,626 | [] |
## Annotation
We resized the dataset to 1080p for easier uploading. Therefore, the original annotation file might not match the video names. Please refer to this https://github.com/PKU-YuanGroup/Open-Sora-Plan/issues/312#issuecomment-2197312973
## Pexels
Pexels consists of multiple folders, but each folder exceeds t... |
dataset | occiglot/tokenizer-wiki-bench | occiglot | 2024-03-13 | 2024-04-23 | [
"af",
"ar",
"bg",
"ca",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"ga",
"he",
"hi",
"hr",
"hu",
"hy",
"id",
"it",
"ja",
"ko",
"lt",
"lv",
"mr",
"nl",
"no",
"pl",
"pt",
"ro",
"ru",
"sa",
"sk",
"sl",
"sr",
"sv",
"ta"... | mit | [] | [
"language:af",
"language:ar",
"language:bg",
"language:ca",
"language:cs",
"language:da",
"language:de",
"language:el",
"language:en",
"language:es",
"language:et",
"language:eu",
"language:fa",
"language:fi",
"language:fr",
"language:ga",
"language:he",
"language:hi",
"language:... | 10M<n<100M | 118,418 | null | 84,440,680 | 228,556,371,738 | [
"2012.15613"
] |
# Multilingual Tokenizer Benchmark
This dataset includes pre-processed wikipedia data for tokenizer evaluation in [45 languages](https://huggingface.co/datasets/occiglot/tokenizer-wiki-bench/blob/main/README.md#supported-languages). We provide more information on the evaluation task in general [this blogpost](https:... |
dataset | Helsinki-NLP/fineweb-edu-translated | Helsinki-NLP | 2025-07-24 | 2026-04-22 | [
"bos",
"bul",
"cat",
"ces",
"dan",
"deu",
"ell",
"eng",
"est",
"eus",
"fin",
"fra",
"gle",
"glg",
"hrv",
"hun",
"isl",
"ita",
"kat",
"lav",
"lit",
"mkd",
"mlt",
"nld",
"nno",
"nob",
"pol",
"por",
"ron",
"slk",
"slv",
"spa",
"sqi",
"srp",
"swe",
"... | odc-by | [
"translation",
"text-generation"
] | [
"task_categories:translation",
"task_categories:text-generation",
"language:bos",
"language:bul",
"language:cat",
"language:ces",
"language:dan",
"language:deu",
"language:ell",
"language:eng",
"language:est",
"language:eus",
"language:fin",
"language:fra",
"language:gle",
"language:gl... | 1B<n<10B | 132,323 | null | 1,999,563,091 | 5,583,387,429,124 | [] |
# Helsinki-NLP/fineweb-edu-translated
**fineweb-edu-tanslated** is a collection of automatically translated documents from fineweb-edu.
Translations are based on [OPUS-MT and HPLT-MT models](https://opus.nlpl.eu/dashboard/).
The data in v1.0 covers 36,704,000 documents with over 28 billion space-searated tokens of E... |
dataset | PleIAs/common_corpus | PleIAs | 2024-11-12 | 2026-05-06 | [
"en",
"fr",
"de",
"zh",
"it",
"es",
"ja",
"pl",
"la",
"nl",
"ru",
"ar",
"ko"
] | null | [] | [
"language:en",
"language:fr",
"language:de",
"language:zh",
"language:it",
"language:es",
"language:ja",
"language:pl",
"language:la",
"language:nl",
"language:ru",
"language:ar",
"language:ko",
"size_categories:10K<n<100K",
"format:parquet",
"modality:tabular",
"modality:text",
"l... | 10K<n<100K | 154,916 | null | 69,907 | 4,489,487,190,361 | [
"2410.22587"
] |
# Common Corpus
<p align="center">
<a href="https://iclr.cc/virtual/2026/poster/10011885"><b>Full paper - ICLR 2026 oral</b></a>
</p>
Common Corpus is the largest open licensed text dataset, comprising 2.27 trillion tokens (2,267,302,720,836 tokens). It is a diverse dataset, consisting of books, newspapers, scien... |
dataset | wyu1/Leopard-Instruct | wyu1 | 2024-10-29 | 2024-11-08 | [
"en"
] | apache-2.0 | [] | [
"language:en",
"license:apache-2.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2410.01744",
"region:us",
"multimodal",
"instruction-following",
"multi-image",
"lmm... | 1M<n<10M | 131,047 | null | 978,710 | 605,912,091,996 | [
"2410.01744"
] |
# Leopard-Instruct
[Paper](https://arxiv.org/abs/2410.01744) | [Github](https://github.com/tencent-ailab/Leopard) | [Models-LLaVA](https://huggingface.co/wyu1/Leopard-LLaVA) | [Models-Idefics2](https://huggingface.co/wyu1/Leopard-Idefics2)
## Summaries
Leopard-Instruct is a large instruction-tuning dataset, compris... |
dataset | open-thoughts/OpenThoughts-114k | open-thoughts | 2025-01-27 | 2025-08-31 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2506.04178",
"region:us",
"curator",
"synthetic"
] | 100K<n<1M | 113,783 | null | 227,914 | 3,549,265,414 | [
"2506.04178"
] |
<p align="center">
<img src="open_thoughts.png" width="50%">
</p>
> [!NOTE]
> We have released a paper for OpenThoughts! See our paper [here](https://arxiv.org/abs/2506.04178).
<a href="https://github.com/bespokelabsai/curator/">
<img src="https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k/resolve/... |
dataset | isaacus/open-australian-legal-corpus | isaacus | 2023-06-25 | 2026-03-07 | [
"en"
] | other | [
"text-generation",
"fill-mask",
"text-retrieval"
] | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:text-retrieval",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"task_ids:document-retrieval",
"annotations_creators:no-annotation",
"language_creators:found",
"source_datasets:Federal Register of Le... | 100K<n<1M | 213,648 | null | 118,346 | 9,401,213,158 | [] | # **Open Australian Legal Corpus ⚖️**
<a href="https://huggingface.co/datasets/isaacus/open-australian-legal-corpus" alt="Release"><img src="https://img.shields.io/badge/release-v7.1.0-green"></a>
The **Open Australian Legal Corpus** by **[Isaacus](https://isaacus.com/)**, a foundational legal AI research company, is... |
dataset | mvp-lab/LLaVA-OneVision-1.5-Mid-Training-85M | mvp-lab | 2025-09-14 | 2025-11-24 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2509.23661",
"region:us"
] | 10M<n<100M | 150,361 | null | 91,493,097 | 46,662,982,787,572 | [
"2509.23661"
] | # 🚀 LLaVA-One-Vision-1.5-Mid-Training-85M Dataset is being uploaded 🚀
# Upload Status
- **All Completed**: ImageNet-21k、LAIONCN、DataComp-1B、Zero250M、COYO700M、SA-1B、MINT、Obelics
# 📜 Cite
If you find *LLaVA-One-Vision-1.5-Mid-Training-85M* useful in your research, please consider to cite the following related paper... |
dataset | HuggingFaceFW/fineweb-edu-score-2 | HuggingFaceFW | 2024-05-28 | 2025-07-11 | [
"en"
] | odc-by | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:odc-by",
"size_categories:10B<n<100B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2404.14219",
"arxiv:2401.10020",
"arxiv:2109.07445",
... | 10B<n<100B | 145,827 | null | 13,892,422,290 | 18,695,115,318,094 | [
"2404.14219",
"2401.10020",
"2109.07445"
] |
# 📚 FineWeb-Edu-score-2
<center>
<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/wwRnEQydH9qdRtFofIE-A.png" alt="FineWeb-Edu: The finest collection of educational content the web has to offer">
</center>
> 1.3 trillion tokens of the finest educational data the 🌐 web has ... |
dataset | fixie-ai/common_voice_17_0 | fixie-ai | 2024-07-21 | 2025-01-17 | [] | null | [] | [
"size_categories:10M<n<100M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10M<n<100M | 140,053 | null | 11,432,177 | 399,323,796,505 | [] | |
dataset | lmms-lab/Video-MME | lmms-lab | 2024-06-07 | 2024-07-04 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"modality:video",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1K<n<10K | 108,157 | null | 2,700 | 101,002,235,118 | [] | |
dataset | ailsntua/Chordonomicon | ailsntua | 2024-10-29 | 2025-05-15 | [] | cc-by-nc-4.0 | [] | [
"license:cc-by-nc-4.0",
"size_categories:100K<n<1M",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2410.22046",
"region:us"
] | 100K<n<1M | 107,636 | null | 679,807 | 264,201,651 | [
"2410.22046"
] |
# Chordonomicon
Chordonomicon: A Dataset of 666,000 Chord Progressions
Chordonomicon is a very large scale dataset featuring the symbolic representation of more than 666,000 contemporary music compositions through the use of music chords and chord progressions. We offer metadata for details such as genre, sub-genre, ... |
dataset | openslr/librispeech_asr | openslr | 2022-03-02 | 2025-07-25 | [
"en"
] | cc-by-4.0 | [
"automatic-speech-recognition",
"audio-classification"
] | [
"task_categories:automatic-speech-recognition",
"task_categories:audio-classification",
"task_ids:speaker-identification",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"source_datasets:original",
"lang... | 100K<n<1M | 109,459 | [
"monolingual"
] | 584,734 | 123,675,353,811 | [] |
# Dataset Card for librispeech_asr
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-insta... |
dataset | hf-internal-testing/librispeech_asr_dummy | hf-internal-testing | 2022-03-02 | 2024-06-19 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 107,554 | null | 73 | 9,193,753 | [] | |
dataset | truthfulqa/truthful_qa | truthfulqa | 2022-06-08 | 2024-01-04 | [
"en"
] | apache-2.0 | [
"multiple-choice",
"text-generation",
"question-answering"
] | [
"task_categories:multiple-choice",
"task_categories:text-generation",
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"task_ids:language-modeling",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monoling... | 1K<n<10K | 104,673 | [
"monolingual"
] | 1,634 | 504,836 | [
"2109.07958"
] |
# Dataset Card for truthful_qa
## Table of Contents
- [Dataset Card for truthful_qa](#dataset-card-for-truthful_qa)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leader... |
dataset | locuslab/TOFU | locuslab | 2023-11-14 | 2025-03-27 | [
"en"
] | mit | [
"question-answering"
] | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:mit",
"size_categories:10K<n<100K",
"format:json",
"modality:text... | 10K<n<100K | 109,473 | [
"monolingual"
] | 18,114 | 6,326,167 | [
"2401.06121"
] |
# TOFU: Task of Fictitious Unlearning 🍢
The TOFU dataset serves as a benchmark for evaluating unlearning performance of large language models on realistic tasks. The dataset comprises question-answer pairs based on autobiographies of 200 different authors that do not exist and are completely fictitiously generated b... |
dataset | lyk/ArxivMetaData | lyk | 2025-10-30 | 2026-01-08 | [] | null | [] | [
"size_categories:1M<n<10M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1M<n<10M | 103,663 | null | 2,935,643 | 1,204,393,704 | [] | |
dataset | jxcai-scale/hle-public-questions | jxcai-scale | 2025-06-06 | 2025-06-06 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1K<n<10K | 103,766 | null | 2,500 | 2,079,245 | [] | |
dataset | nvidia/Nemotron-CC-Math-v1 | nvidia | 2025-08-14 | 2025-12-23 | [] | other | [
"text-generation"
] | [
"task_categories:text-generation",
"license:other",
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2508.15096",
"arxiv:2410.12881",
"arxiv:2508.14444",
"region:us"
] | 100M<n<1B | 93,390 | null | null | 259,937,855,799 | [
"2508.15096",
"2410.12881",
"2508.14444"
] |
# Nemotron-Pre-Training-Dataset-v1 Release
👩💻 **Authors**: Rabeeh Karimi Mahabadi, Sanjeev Satheesh
📘 **Paper**: [Nemotron-cc-math: A 133 Billion-Token-Scale High Quality Math Pretraining Dataset](https://arxiv.org/abs/2508.15096)
📝 **Blog**: [Nemotron-cc-math blog](https://huggingface.co/blog/nvidia/nemotron-... |
dataset | math-ai/aime25 | math-ai | 2025-02-17 | 2026-01-19 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 93,874 | null | 30 | 30,508 | [] |
# AIME 25
[](https://opensource.org/license/apache-2-0)
[](https://huggingface.co/datasets/math-ai/aime25)
### American Invitational Mathematics Examination (AI... |
dataset | MMMU/MMMU | MMMU | 2023-11-27 | 2026-04-21 | [
"en"
] | apache-2.0 | [
"question-answering",
"visual-question-answering",
"multiple-choice"
] | [
"task_categories:question-answering",
"task_categories:visual-question-answering",
"task_categories:multiple-choice",
"language:en",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
... | 10K<n<100K | 102,970 | null | 11,550 | 3,655,836,507 | [
"2311.16502"
] |
# MMMU (A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI)
[**🌐 Homepage**](https://mmmu-benchmark.github.io/) | [**🏆 Leaderboard**](https://mmmu-benchmark.github.io/#leaderboard) | [**🤗 Dataset**](https://huggingface.co/datasets/MMMU/MMMU/) | [**🤗 Paper**](https://huggin... |
dataset | EleutherAI/lambada_openai | EleutherAI | 2022-12-16 | 2025-07-10 | [
"de",
"en",
"es",
"fr",
"it"
] | mit | [] | [
"task_ids:language-modeling",
"language_creators:machine-generated",
"multilinguality:translation",
"source_datasets:lambada",
"language:de",
"language:en",
"language:es",
"language:fr",
"language:it",
"license:mit",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library... | 10K<n<100K | 98,172 | [
"translation"
] | 30,918 | 18,765,997 | [] |
## Dataset Description
- **Repository:** [openai/gpt2](https://github.com/openai/gpt-2)
- **Paper:** Radford et al. [Language Models are Unsupervised Multitask Learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf)
### Dataset Summary
This dataset is comprised of the LAMBADA test ... |
dataset | HuggingFaceM4/FineVision | HuggingFaceM4 | 2025-07-28 | 2025-10-21 | [] | null | [] | [
"size_categories:10M<n<100M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2510.17269",
"region:us"
] | 10M<n<100M | 145,067 | null | 24,209,105 | 4,645,230,711,508 | [
"2510.17269"
] |
# Fine Vision
FineVision is a massive collection of datasets with **17.3M images**, **24.3M samples**, **88.9M turns**, and **9.5B answer tokens**, designed for training state-of-the-art open Vision... |
dataset | llamafactory/demo_data | llamafactory | 2024-05-17 | 2024-07-18 | [
"en",
"zh"
] | apache-2.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"language:zh",
"license:apache-2.0",
"size_categories:1K<n<10K",
"modality:text",
"region:us",
"llama-factory"
] | 1K<n<10K | 95,902 | null | 4,197 | 9,948,638 | [] |
- 1,000 examples from https://huggingface.co/datasets/llamafactory/alpaca_gpt4_en
- 1,000 examples from https://huggingface.co/datasets/llamafactory/alpaca_gpt4_zh
- 300 examples from https://huggingface.co/datasets/llamafactory/glaive_toolcall_en
- 300 examples from https://huggingface.co/datasets/llamafactory/glaive... |
dataset | Muennighoff/multi_eurlex | Muennighoff | 2023-05-21 | 2023-05-21 | [] | null | [] | [
"size_categories:10M<n<100M",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us"
] | 10M<n<100M | 97,343 | null | 33,641,552 | 142,428 | [] | |
dataset | lmsys/chatbot_arena_conversations | lmsys | 2023-07-18 | 2023-09-30 | [] | cc | [
"conversational"
] | [
"license:cc",
"size_categories:10K<n<100K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2306.05685",
"region:us"
] | 10K<n<100K | 90,300 | null | null | 41,582,304 | [
"2306.05685"
] |
## Chatbot Arena Conversations Dataset
This dataset contains 33K cleaned conversations with pairwise human preferences.
It is collected from 13K unique IP addresses on the [Chatbot Arena](https://lmsys.org/blog/2023-05-03-arena/) from April to June 2023.
Each sample includes a question ID, two model names, their full ... |
dataset | bettergovph/gov-library | bettergovph | 2026-01-23 | 2026-01-31 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 100K<n<1M | 98,370 | null | 206,824 | 2,069,267,195 | [] | # Philippine Legal Documents Dataset
A comprehensive collection of Philippine legal documents from Lawphil.net, extracted from HTML to Markdown and organized for easy querying.
## Overview
This dataset contains **114,340** legal documents spanning from 1900 to 2025, including:
- **Jurisprudence** (68,080 documents)... |
dataset | nvidia/Nemotron-Pretraining-Code-v2 | nvidia | 2025-11-25 | 2025-12-22 | [] | other | [
"text-generation"
] | [
"task_categories:text-generation",
"license:other",
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2508.14444",
"arxiv:2508.15096",
"arxiv:2412.02595",
"arxiv:2505.02881",
"region:us"
] | 100M<n<1B | 91,887 | null | null | 907,124,100,086 | [
"2508.14444",
"2508.15096",
"2412.02595",
"2505.02881"
] | # Nemotron-Pre-Training-Dataset-v2.1
## Dataset Description
The Nemotron-Pre-Training-Dataset-v2.1 extends the previously released Nemotron pretraining datasets with refreshed, higher-quality, and more diverse data across math, code, English Common Crawl, and large-scale synthetic ... |
dataset | hotpotqa/hotpot_qa | hotpotqa | 2022-03-02 | 2025-08-11 | [
"en"
] | cc-by-sa-4.0 | [
"question-answering"
] | [
"task_categories:question-answering",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:d... | 100K<n<1M | 91,250 | [
"monolingual"
] | 203,109 | 746,637,047 | [
"1809.09600"
] |
# Dataset Card for "hotpot_qa"
## 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... |
dataset | JosephusCheung/GuanacoDataset | JosephusCheung | 2023-03-16 | 2024-04-15 | [
"zh",
"en",
"ja",
"de"
] | gpl-3.0 | [
"text-generation",
"question-answering",
"conversational"
] | [
"task_categories:text-generation",
"task_categories:question-answering",
"language:zh",
"language:en",
"language:ja",
"language:de",
"license:gpl-3.0",
"size_categories:1M<n<10M",
"format:json",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"doi:10.57967/hf/14... | 1M<n<10M | 87,703 | null | null | 814,872,975 | [] | **Sorry, it's no longer available on Hugging Face. Please reach out to those who have already downloaded it. If you have a copy, please refrain from re-uploading it to Hugging Face. The people here don't deserve it. See also: https://twitter.com/RealJosephus/status/1779913520529707387**
# GuanacoDataset
**News: We're... |
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