Datasets:

cfahlgren1
/

hub-stats

_id large_stringlengths 24 24	id large_stringlengths 5 123	author large_stringlengths 2 42	cardData large_stringlengths 2 2.4M ⌀	disabled bool 1 class	gated large_stringclasses 3 values	lastModified timestamp[us]date 2021-02-05 16:03:35 2026-10-01 13:20:33	likes int64 0 9.85k	trendingScore float64 0 570	private bool 1 class	sha large_stringlengths 40 40	description large_stringlengths 0 6.67k ⌀	downloads int64 0 4.46M	downloadsAllTime int64 0 143M	mainSize float64 0 306,846B ⌀	tags listlengths 1 7.92k	createdAt timestamp[us]date 2022-03-02 23:29:22 2026-10-01 13:20:22	paperswithcode_id large_stringclasses 719 values	citation large_stringlengths 0 10.7k ⌀
6ab65a7f909092518dca860f	XiaomiMiMo/MiMo-V2.6-RL-oss	XiaomiMiMo	{"license": "apache-2.0", "configs": [{"config_name": "code", "data_files": "code.parquet"}, {"config_name": "cyber", "data_files": "cyber.parquet"}, {"config_name": "general", "data_files": "general/train.parquet"}, {"config_name": "webdev", "data_files": "webdev.parquet"}, {"config_name": "music", "data_files": "musi...	false	False	2026-09-26T01:40:41	625	570	false	639865fd3374018d6cb29b9fb82dd531406fcf5f	Agentic RL Environments RL training environments for LLM agents. Domain Task Family Verifier Code Software engineering Executable tests Cyber Vulnerability reproduction Rule checks General Knowledge work Rubric-based judging Visual Web development Visual grading Music Symbolic music co...	53,053	53,053	12,102,484,722	[ "license:apache-2.0", "size_categories:1K<n<10K", "format:parquet", "modality:document", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us" ]	2026-09-25T11:26:55	null	null
6ab831e64edba2b438670785	nisten/opus5-5-doctor-patient-conversations-all-human-diseases	nisten	{"license": "apache-2.0", "language": ["en"], "task_categories": ["question-answering", "text-generation"], "tags": ["medical", "healthcare", "clinical", "synthetic", "doctor-patient", "chatml", "rag", "conversational"], "size_categories": ["1K<n<10K"], "pretty_name": "Doctor-Patient Conversations \u2014 All Human Dise...	false	False	2026-09-27T16:02:46	125	85	false	9277244e642a8ba02cb8c1d26408e5792932045b	Opus-5.5 generated Doctor-Patient Conversations for All Human Diseases The sequel to nisten/opus-doctor-patient-conversations-all-human-diseases (Opus 4.8). Same disease list, same 20-key schema, same ChatML conversations — regenerated from scratch with Claude Opus 5.5, one agent per disease, and held to...	859	859	75,466,355	[ "task_categories:question-answering", "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:1K<n<10K", "region:us", "medical", "healthcare", "clinical", "synthetic", "doctor-patient", "chatml", "rag", "conversational" ]	2026-09-26T20:58:14	null	null
6aa321e46caea5109a90c179	secemp9/arxiv-complete	secemp9	{"license": "other", "license_name": "mixed-arxiv-author-licenses", "license_link": "LICENSE", "pretty_name": "arXiv Complete Corpus", "language": ["en"], "task_categories": ["text-generation", "text-retrieval"], "tags": ["arxiv", "scientific-papers", "latex", "preprints", "full-text"], "size_categories": ["10M<n<100M"...	false	False	2026-09-19T20:39:46	556	83	false	cee894837962fede5612cccf2a4c7cacf49b4c3a	arXiv Complete Corpus A snapshot of arXiv's metadata, version history, submission files and rendered documents. It covers 3,148,796 papers and includes file contents, paths, sizes and SHA-256 digests. Metadata comes from arXiv's OAI-PMH arXivRaw interface; files come from the GCS mirror, S3 source archiv...	122,248	122,248	16,076,057,281,538	[ "task_categories:text-generation", "task_categories:text-retrieval", "language:en", "license:other", "size_categories:100M<n<1B", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2401.18030", "region:...	2026-09-10T21:32:20	null	null
6a34c6065edc6bacb0b36213	espnet/yodas3	espnet	{"license": "cc-by-3.0", "task_categories": ["audio-to-audio", "automatic-speech-recognition", "text-to-speech", "translation"], "dataset_info": [{"config_name": "preview", "features": [{"name": "audio", "dtype": "audio"}, {"name": "lang", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "shard", "dtype"...	false	False	2026-10-01T01:57:30	107	82	false	7527f6fb8d7e4e2781efe7a034fb364798893d61	YODAS v3 Paper YODAS v3 is a large web-crawled dataset containing over 1.1 million hours of audio that were originally released under a CC-BY-3.0 license. The dataset contains audio in over 100 languages. YODAS v3 can be used for a variety of multi-modal tasks, including Automatic Speech Recognition, Tex...	56,558	56,558	55,654,792,926,650	[ "task_categories:audio-to-audio", "task_categories:automatic-speech-recognition", "task_categories:text-to-speech", "task_categories:translation", "license:cc-by-3.0", "size_categories:1M<n<10M", "format:parquet", "modality:audio", "modality:tabular", "modality:text", "library:datasets", "libr...	2026-06-19T04:31:02	null	null
6a981c1f3a639ff95e1342fa	MoreThought/Fable-5.1-Max-Reasoning-Filtered-10000x	MoreThought	{"license": "apache-2.0", "task_categories": ["text-generation", "question-answering"], "language": ["en"], "pretty_name": "The First And Best Fable 5.1 Reasoning Data", "tags": ["fable 5.1", "coding", "synthetic", "thinking", "think", "reason", "reasoning", "distill", "distillation", "agent", "agentic", "SFT", "CoT", ...	false	False	2026-09-24T14:27:20	238	70	false	602d49c99c4af5530cc02327dd2d90827c84292a	Dataset Description This dataset contains 10,000 agentic coding and reasoning multi-turn high-quality traces generated by the new Fable 5.1 model using max reasoning effort. It holds almost 500,000,000 tokens of step-by-step chain-of-thought programming across multiple complex domains. It has also been ...	4,386	4,386	2,594,907,881	[ "task_categories:text-generation", "task_categories:question-answering", "language:en", "license:apache-2.0", "size_categories:10K<n<100K", "format:json", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "fable 5.1", "coding", "synthetic", "thin...	2026-09-02T12:52:47	null	null
6ab4f16cb386daf00b9d61ee	FineEnvs/SmolDataEnvs	FineEnvs	{"license": "mit", "task_categories": ["question-answering", "table-question-answering"], "tags": ["smoldataenvs", "data-analysis", "agent", "rl-environment", "reinforcement-learning", "code-agent"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "pat...	false	False	2026-09-30T05:24:11	64	64	false	6c439f075cf550793b1bfd7b887a41e51f3b23ab	📈 SmolDataEnvs 5.5K+ RL tasks for hill-climbing small models in code and data science. A 2B model on these tasks. Left: what it optimises. Right: 144 held-out tasks it never trains on. Two runs over the same 5,000 tasks: shuffled against a curriculum ordered easiest to hardest. Data-anal...	3,808	3,808	4,436,042	[ "task_categories:question-answering", "task_categories:table-question-answering", "license:mit", "size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "smoldataenvs", "d...	2026-09-24T09:46:20	null	null
621ffdd236468d709f184284	wikimedia/wikipedia	wikimedia	{"language": ["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", "bpy", "br", "bs", "bug", "bxr", "ca", "cbk", "cdo", "ce", "ceb"...	false	False	2024-01-09T09:40:51	1,606	59	false	b04c8d1ceb2f5cd4588862100d08de323dccfbaa	Dataset Card for Wikimedia Wikipedia Dataset Summary Wikipedia dataset containing cleaned articles of all languages. The dataset is built from the Wikipedia dumps (https://dumps.wikimedia.org/) with one subset per language, each containing a single train split. Each example contains the co...	275,609	3,278,410	71,792,022,791	[ "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", "...	2022-03-02T23:29:22	null	null
6aaa4864f37373a4ce11d91a	LocalLLaMA/typed-decisions	LocalLLaMA	{"license": "apache-2.0", "language": ["en"], "pretty_name": "Typed Decisions", "size_categories": ["n<1K"], "task_categories": ["text-classification"], "tags": ["structured-decisions", "calibration", "probabilistic-classification", "system-one", "workflow-evaluation", "synthetic"], "configs": [{"config_name": "agent_t...	false	False	2026-10-01T01:21:30	90	55	false	d0e2f0c42fef86cc15d1688d25a19f5ba7c85b18	Typed Decisions A benchmark for typed probabilistic decisions. A model gets one piece of unstructured state and answers five typed questions about it at once, and every answer is a probability distribution, not a single label. The schema follows the System One primitives (noul, choice, score) used by Typ...	21,940	21,940	2,166,801	[ "task_categories:text-classification", "language:en", "license:apache-2.0", "size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "structured-decisions", "calibration", ...	2026-09-16T07:42:28	null	null
6a9559ff16ac55f9f3d5ef72	Zaevlad/audit-findings-dataset	Zaevlad	{"license": "other", "language": ["en"], "task_categories": ["text-classification", "text-generation"], "tags": ["security", "smart-contracts", "code-audit", "vulnerability", "solidity"], "pretty_name": "Smart Contract Audit Findings", "size_categories": ["10K<n<100K"], "configs": [{"config_name": "default", "data_file...	false	False	2026-08-31T10:41:42	66	40	false	58b2dd4662e25b0d6438162ffe8f61cfc134efc3	Smart Contract Audit Findings This is raw, semi-structured data — not a ready-to-train dataset. It still requires further cleaning and preparation (deduplication, severity/label normalization, filtering low-quality or malformed entries, etc.) before it should be used to train or fine-tune an AI model. ...	1,014	1,030	146,574,384	[ "task_categories:text-classification", "task_categories:text-generation", "language:en", "license:other", "size_categories:10K<n<100K", "region:us", "security", "smart-contracts", "code-audit", "vulnerability", "solidity" ]	2026-08-31T10:39:59	null	null
6ab03e4d1ce52d54824a8b47	ZefanCai/Open-Jev	ZefanCai	"{\"license\": \"cc0-1.0\", \"language\": [\"en\", \"zh\", \"tr\"], \"task_categories\": [\"text-cla(...TRUNCATED)	false	False	2026-09-20T22:49:59	61	34	false	c67699e13d0ae25e35b77165a4b6b079bedc8aba	"\n\t\n\t\t\n\t\n\t\n\t\tOpen-Jev: typed decision datasets\n\t\n\nOpen-Jev turns a state and a quest(...TRUNCATED)	3,798	3,798	86,774,571	["task_categories:text-classification","language:en","language:zh","language:tr","license:cc0-1.0","(...TRUNCATED)	2026-09-20T20:13:01	null	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

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