Datasets:

cfahlgren1
/

hub-stats

_id large_stringlengths 24 24	id large_stringlengths 5 123	author large_stringlengths 2 42	cardData large_stringlengths 2 1.09M ⌀	disabled bool 1 class	gated large_stringclasses 3 values	lastModified timestamp[us]date 2021-02-05 16:03:35 2026-09-04 13:27:59	likes int64 0 9.81k	trendingScore float64 0 163	private bool 1 class	sha large_stringlengths 40 40	description large_stringlengths 0 6.67k ⌀	downloads int64 0 2.77M	downloadsAllTime int64 0 143M	mainSize float64 0 306,846B ⌀	paperswithcode_id large_stringclasses 718 values	tags listlengths 1 7.92k	createdAt timestamp[us]date 2022-03-02 23:29:22 2026-09-04 13:27:49	citation large_stringlengths 0 10.7k ⌀
621ffdd236468d709f181f95	rajpurkar/squad	rajpurkar	{"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced", "found"], "language": ["en"], "license": "cc-by-sa-4.0", "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["extended\|wikipedia"], "task_categories": ["question-answering"], "task_ids": ["extractive-...	false	False	2024-03-04T13:54:37	628	163	false	7b6d24c440a36b6815f21b70d25016731768db1f	Dataset Card for SQuAD Dataset Summary Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding read...	264,632	7,901,771	16,286,997	squad	[ "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"...	2022-03-02T23:29:22	null
6a88290bf198e93508a91ba2	markov-ai/cad-1000-hours	markov-ai	{"pretty_name": "CAD 1000 Hours", "viewer": false, "tags": ["cad", "computer-use", "screen-recording", "video"]}	false	False	2026-08-21T12:26:29	356	152	false	b1bd4711343017fc40dfa6fe40a6cd338b7edaf6	CAD 1000 Hours CAD 1000 Hours is a computer-use dataset containing 1,021.64 hours of recorded work across 597 workflows and 10 CAD, BIM, structural-analysis, and visualization applications. The tables below summarize its software coverage. Category distribution Category Included sof...	101,777	101,777	275,540,558,620	null	[ "modality:video", "region:us", "cad", "computer-use", "screen-recording", "video" ]	2026-08-21T10:31:39	null
621ffdd236468d709f181e77	stanfordnlp/imdb	stanfordnlp	{"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": ["sentiment-classification"]...	false	False	2024-01-04T12:09:45	621	148	false	e6281661ce1c48d982bc483cf8a173c1bbeb5d31	Dataset Card for "imdb" Dataset Summary Large Movie Review Dataset. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additi...	181,487	9,568,705	83,455,823	imdb-movie-reviews	[ "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...	2022-03-02T23:29:22	null
621ffdd236468d709f181e3f	nyu-mll/glue	nyu-mll	{"annotations_creators": ["other"], "language_creators": ["other"], "language": ["en"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["acceptability-classification", "natural-language...	false	False	2024-01-30T07:41:18	656	129	false	bcdcba79d07bc864c1c254ccfcedcce55bcc9a8c	Dataset Card for GLUE Dataset Summary GLUE, the General Language Understanding Evaluation benchmark (https://gluebenchmark.com/) is a collection of resources for training, evaluating, and analyzing natural language understanding systems. Supported Tasks and Leaderboards The ...	755,188	43,035,051	162,286,103	glue	[ "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...	2022-03-02T23:29:22	null
6a98505380510c166c9a5e52	kuben-developer/tiktok-videos-4b	kuben-developer	{"license": "other", "license_name": "research-use", "pretty_name": "TikTok Videos, 4.5 Billion", "size_categories": ["n>1T"], "task_categories": ["text-classification", "text-generation", "feature-extraction"], "language": ["en", "es", "pt", "id", "ar"], "tags": ["tiktok", "social-media", "short-video", "recommender-s...	false	False	2026-09-02T17:42:55	82	79	false	cbcda8f790dc21caa5cea19165e309526281e35a	TikTok Videos: 4.5 billion posts with engagement metrics 4.5 billion TikTok video records with captions, engagement counts, sound identifiers and timing. Collected from TikTok's mobile API over roughly three weeks. Every content_id appears exactly once. This is the largest public TikTok dataset I am awar...	3,072	3,072	289,467,105,693	null	[ "task_categories:text-classification", "task_categories:text-generation", "task_categories:feature-extraction", "language:en", "language:es", "language:pt", "language:id", "language:ar", "license:other", "size_categories:1B<n<10B", "format:parquet", "modality:tabular", "modality:text", "li...	2026-09-02T16:35:31	null
6a8b056d71b57e788ea7ef6a	hamzabagirsakci/turkish-court-decisions	hamzabagirsakci	{"language": ["tr"], "license": "cc0-1.0", "pretty_name": "T\u00fcrk \u0130\u00e7tihat Korpusu (11M Karar)", "size_categories": ["10M<n<100M"], "task_categories": ["text-generation", "text-retrieval", "text-classification", "summarization", "question-answering"], "tags": ["legal", "law", "turkish", "t\u00fcrk\u00e7e", ...	false	False	2026-09-02T05:57:26	131	38	false	d7db91819d81f7155a0d1fa90c109ece8659f46a	Türk İçtihat Korpusu — 11.045.085 Mahkeme Kararı Türkiye'nin kamuya açık mahkeme kararlarından derlenmiş, bilinen en büyük Türkçe hukuk metni veri seti. 11.045.085 karar, 31.5 milyar karakter düz metin (5.52 GB Parquet), 1962'den 2026'ya. Yargıtay, Danıştay, Anayasa Mahkemesi ve UYAP Emsal üzerinden yere...	3,374	3,374	5,521,419,355	null	[ "task_categories:text-generation", "task_categories:text-retrieval", "task_categories:text-classification", "task_categories:summarization", "task_categories:question-answering", "language:tr", "license:cc0-1.0", "size_categories:10M<n<100M", "format:parquet", "modality:tabular", "modality:text"...	2026-08-23T14:36:29	null
6a8c7db148f47777cb08c465	SageBio/mva-hackathon-2026-data	SageBio	{"license": "cc-by-4.0", "tags": ["hackathon", "rare-disease"], "size_categories": ["n<1K"], "pretty_name": "Rare Disease, Real Kid: MVA Hackathon 2026", "viewer": false, "extra_gated_prompt": "You must understand and agree to follow the Hackathon Rules.", "extra_gated_fields": {"Institution": {"type": "text", "require...	false	auto	2026-08-26T19:35:26	115	26	false	59e322d27f399006b398d366d33e703e48a29914	Rare Disease, Real Kid: MVA Hackathon 2026 - Dataset Challenge Space: SageBio/rare-disease-real-kid-mva-hackathon-2026 Submission Period: 24 August 2026 – 24 October 2026 Dataset Size: ~85 GB Quickstart Python from huggingface_hub import hf_hub_download # Download a specific file ...	1,291	1,291	84,985,955,967	null	[ "license:cc-by-4.0", "size_categories:n<1K", "region:us", "hackathon", "rare-disease" ]	2026-08-24T17:21:53	null
6799c7f5754836e22dc052ec	llm-jp/AnswerCarefully	llm-jp	{"extra_gated_prompt": "### AnswerCarefully Dataset \u5229\u7528\u898f\u7d04\n - \u5229\u7528\u898f\u7d04\n - \u672c\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f\u3001\u65e5\u672c\u8a9e\u304a\u3088\u3073\u4ed6\u306e\u8a00\u8a9e\u306eLLM\u306e\u5b89\u5168\u6027\u3092\u5411\u4e0a\u3055\u305b\u308b\u3068\u3044\u3046\u76e...	false	manual	2026-08-20T01:02:50	128	23	false	d1d4e57cd4d7aecb44f879e7488832011fcaddb0	AnswerCarefully 概要 AnswerCarefullyは日本語LLM 出力の安全性・適切性に特化したインストラクションデータセットです。このデータセットは、英語の要注意回答を集めた Do-Not-Answer データセットの包括的なカテゴリ分類に基づき、人手で質問・回答ともに日本語サンプルを集めたオリジナルのデータセットです。データセットの詳細については、こちらをご覧ください。 Overview AnswerCarefully is an instruction dataset specifically aimed at ensuring safety and appropriate...	10,852	23,353	1,767,742	null	[ "language:ja", "language:en", "license:other", "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us" ]	2025-01-29T06:17:25	null
621ffdd236468d709f184284	wikimedia/wikipedia	wikimedia	"{\"language\": [\"ab\", \"ace\", \"ady\", \"af\", \"alt\", \"am\", \"ami\", \"an\", \"ang\", \"anp\(...TRUNCATED)	false	False	2024-01-09T09:40:51	1,411	21	false	b04c8d1ceb2f5cd4588862100d08de323dccfbaa	"\n\t\n\t\t\n\t\n\t\n\t\tDataset Card for Wikimedia Wikipedia\n\t\n\n\n\t\n\t\t\n\t\n\t\n\t\tDataset(...TRUNCATED)	254,370	3,028,573	71,792,022,791	null	["task_categories:text-generation","task_categories:fill-mask","task_ids:language-modeling","task_id(...TRUNCATED)	2022-03-02T23:29:22	null
6a669b60c7c5f26e04472453	r0b0tlab/qwen3.8-max-glm5.2-kimi-k3-distillation	r0b0tlab	"{\"license\": \"other\", \"language\": [\"en\", \"zh\", \"es\", \"fr\", \"de\", \"ja\"], \"task_cat(...TRUNCATED)	false	False	2026-08-02T01:32:23	240	21	false	7a3473446840bcc397928cd8183d4b3ba3ca13a7	"\n\t\n\t\t\n\t\n\t\n\t\tMulti-Teacher Distillation Dataset (57,937 traces)\n\t\n\nA quality-filtere(...TRUNCATED)	9,438	10,064	827,297,284	null	["task_categories:text-generation","language:en","language:zh","language:es","language:fr","language(...TRUNCATED)	2026-07-26T23:42:24	null

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Changelog

NEW Changes March 11th 2026

Added new split: arxiv_papers, sourced from the Hugging Face /api/papers endpoint
papers continues to point to daily_papers.parquet, which is the Daily Papers feed

NEW Changes July 25th

added baseModels field to models which shows the models that the user tagged as base models for that model

Example:

{
  "models": [
    {
      "_id": "687de260234339fed21e768a",
      "id": "Qwen/Qwen3-235B-A22B-Instruct-2507"
    }
  ],
  "relation": "quantized"
}

NEW Changes July 9th

Fixed issue with gguf column with integer overflow causing import pipeline to be broken over a few weeks ✅

NEW Changes Feb 27th

Added new fields on the models split: downloadsAllTime, safetensors, gguf
Added new field on the datasets split: downloadsAllTime
Added new split: papers which is all of the Daily Papers

Updated Daily

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