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 2026-10-09 13:18:39	likes int64 0 9.85k	trendingScore float64 0 141	private bool 1 class	sha large_stringlengths 40 40	description large_stringlengths 0 6.67k ⌀	downloads int64 0 4.27M	downloadsAllTime int64 0 143M	mainSize float64 0 306,846B ⌀	tags listlengths 1 7.92k	createdAt timestamp[us]date 2022-03-02 23:29:22 2026-10-09 13:17:17	paperswithcode_id large_stringclasses 719 values	citation large_stringlengths 0 10.7k ⌀
6ac0e39df4f1ce50a992796a	datasocial/tiktok-5.6B-videos	datasocial	{"license": "cc-by-nc-4.0", "pretty_name": "TikTok Videos (5.6 billion)", "tags": ["tiktok", "social-media", "short-video", "creators"], "size_categories": ["n>1T"], "configs": [{"config_name": "default", "data_files": "data/*.parquet"}]}	false	False	2026-10-07T18:55:25	153	141	false	8904c3a99100e4f7538b0c842c86d0768665eac5	Contact Telegram: @hashfunction_dev X: @hashfunction Email: hashfunction.dev@gmail.com TikTok scraper source code The code that collected these 5.6 billion videos. TikTok's mobile API: 24 endpoints, request signing, device registration. Technical guide + source code → Columns Co...	8,728	8,728	460,480,293,922	[ "license:cc-by-nc-4.0", "size_categories:1B<n<10B", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "region:us", "tiktok", "social-media", "short-video", "creators" ]	2026-10-03T11:14:37	null	null
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	888	110	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...	104,589	104,589	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	286	54	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...	3,275	3,275	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
6a75aceba8e651eb9e1507ce	LightwheelAI/EgoStandard	LightwheelAI	{"pretty_name": "EgoSuite-Open100K - EgoStandard", "language": ["en"], "license": "other", "license_name": "commercial-training-no-resale-v1.0", "size_categories": ["10K<n<100K"], "task_categories": ["video-classification"], "tags": ["video", "egocentric-video", "embodied-ai", "human-demonstration", "human-pose", "hand...	false	auto	2026-10-09T01:53:50	188	50	false	1592f0412a116373f27a925e5cbf2faecca1d4ed	EgoStandard The 90,000-hour head-view line of EgoSuite-Open100K. Data Bucket · Collection · EgoDemo · EgoPro · Project page Explore EgoSuite-Open100K ↗ Data location: EgoStandard is distributed through the LightwheelAI/EgoStandard Bucket. This Git repository is the dataset card and access point;...	692	5,958	23,961	[ "task_categories:video-classification", "language:en", "license:other", "size_categories:10K<n<100K", "modality:video", "region:us", "video", "egocentric-video", "embodied-ai", "human-demonstration", "human-pose", "hand-pose", "body-pose", "multimodal", "lerobot", "mcap", "robotics" ...	2026-08-07T10:01:15	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	2026-10-07T18:03:31	227	48	false	81d802f45a1c1e1f5331260484dacf1fbea81981	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...	180,224	180,224	55,654,792,929,062	[ "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
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	652	46	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...	167,226	167,226	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
6a71e7bcef3e736c2c40876c	bakrianoo/jabarti-llm-dataset	bakrianoo	{"language": ["ar", "en"], "license": "cc-by-sa-4.0", "task_categories": ["text-generation", "question-answering"], "tags": ["arabic", "egyptian-history", "bilingual", "llm-training", "from-scratch", "wikipedia"], "configs": [{"config_name": "pretrain", "data_files": [{"split": "train", "path": "pretrain/train-*"}, {"s...	false	False	2026-09-23T09:19:55	49	42	false	7b7aeaaff76fdc254a9d245146c9d8a624bbd552	jabarti-llm-dataset Cleaned, section-chunked training corpus for a small bilingual LLM (Arabic + English), combining a curated Egyptian-history collection with general Wikipedia coverage from CohereLabs/wikipedia-2023-11-embed-multilingual-v3. Every pretrain record is a contiguous span of 120-1500 charac...	1,131	1,307	2,510,048,373	[ "task_categories:text-generation", "task_categories:question-answering", "language:ar", "language:en", "license:cc-by-sa-4.0", "size_categories:1M<n<10M", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "re...	2026-08-04T13:23:08	null	null
69bef5949ef8aa048dac190d	witfoo/precinct6-cybersecurity	witfoo	{"license": "apache-2.0", "task_categories": ["text-classification", "graph-ml"], "language": ["en"], "tags": ["cybersecurity", "intrusion-detection", "provenance-graphs", "MITRE-ATT&CK", "SOAR", "security-operations", "IDS", "network-security", "threat-detection", "labeled-dataset", "lead-rules"], "pretty_name": "WitF...	false	False	2026-09-22T10:50:16	46	38	false	96311c2e29611d8ddbf1c0d59f531f6a362b8233	WitFoo Precinct6 Cybersecurity Dataset Version 2.1.0 (built 2026-09-22). Regenerated to address feedback from the University of Canterbury PIDS evaluation: attacks and normal traffic now share a timeline, usernames are wired into the provenance graph, mis-parsed timestamps are repaired, and every number ...	3,326	9,413	8,414,352,183	[ "task_categories:text-classification", "task_categories:graph-ml", "language:en", "license:apache-2.0", "size_categories:1M<n<10M", "region:us", "cybersecurity", "intrusion-detection", "provenance-graphs", "MITRE-ATT&CK", "SOAR", "security-operations", "IDS", "network-security", "threat-...	2026-03-21T19:46:28	null	null
6a22a21cc8842b3b35401c7e	aidigestorg/ai-village	aidigestorg	{"pretty_name": "AI Village", "license": "other", "license_name": "ai-village-research-terms", "language": ["en"], "tags": ["agents", "llm-agents", "computer-use", "ai-safety", "agentic-behavior"], "size_categories": ["1M<n<10M"], "extra_gated_heading": "Request access to the AI Village dataset", "extra_gated_prompt": ...	false	manual	2026-10-07T16:09:45	123	37	false	97b4df02205dee0140cc83a74c64ba7fe544b7cf	AI Village dataset AI Village is an ongoing experiment by AI Digest in which a group of AI agents — built on frontier models from Anthropic, OpenAI, and Google — live together in a long-running virtual environment. They have their own computers, interact with the real world, are in a group chat with each...	1,937	3,908	209,146,370,263	[ "language:en", "license:other", "size_categories:1M<n<10M", "region:us", "agents", "llm-agents", "computer-use", "ai-safety", "agentic-behavior" ]	2026-06-05T10:17:00	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	2026-10-09T12:36:28	287	36	false	5836103248bb5ada80e29caddf982bd6543c124a	Important Please go to https://huggingface.co/datasets/MoreThought/Fable-5.1-Max-Reasoning-Cleaned-10000x for the training-ready data 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 ...	5,087	5,616	2,538,730,851	[ "task_categories:text-generation", "task_categories:question-answering", "language:en", "license:apache-2.0", "size_categories:10K<n<100K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "fable 5.1", "coding", "...	2026-09-02T12:52:47	null	null
6a8dc3821e1a8830826a1749	docling-project/DeskForge-1M	docling-project	{"pretty_name": "DeskForge-1M", "license": "mit", "task_categories": ["image-to-text", "object-detection"], "language": ["en"], "tags": ["gui", "gui-grounding", "screen-parsing", "computer-use", "desktop", "accessibility", "webdataset"], "size_categories": ["1M<n<10M"], "configs": [{"config_name": "default", "default":...	false	False	2026-10-09T12:18:26	31	31	false	7a3923760e65974825aba6f21073e4e146a361c5	DeskForge-1M DeskForge-1M is a corpus of 1.21M annotated desktop screenshots with 159.7M element instances and 917K recorded click transitions, generated with DeskForge, a controllable desktop environment that composes and explores real applications. Live demo · Project page · Code · DeskForge-Qwen3.5-4B...	2,300	2,377	1,143,060,131,973	[ "task_categories:image-to-text", "task_categories:object-detection", "language:en", "license:mit", "size_categories:1M<n<10M", "library:webdataset", "arxiv:2610.02320", "region:us", "gui", "gui-grounding", "screen-parsing", "computer-use", "desktop", "accessibility", "webdataset" ]	2026-08-25T16:32:02	null	null
6a96c11d1be93f5d15eff9f0	venvoo/china-a-share-l2-level2-limit-order-book-tick-data	venvoo	{"license": "other", "license_name": "research-use-only", "license_link": "LICENSE", "gated": "manual", "extra_gated_heading": "Two steps before you request access / \u7533\u8bf7\u524d\u8bf7\u5148\u5b8c\u6210\u4e24\u6b65", "extra_gated_description": "1. Like (\u2665) this repository \u2014 the button is at the top ...	false	manual	2026-09-30T21:01:33	217	30	false	8d942a74865a67de55ba01b0b982d7ac8743f456	China A-Share Level-2 Archive 2017–2026 · Quotes, orders and trades · Parquet A historical archive of Chinese exchange Level-2 data, supplied through a vendor export. It includes ten-level quote snapshots, individual order messages and trade-stream records. The files cover A-share stocks and non-stock in...	71,788	75,935	6,297,310,467,090	[ "license:other", "size_categories:n>1T", "region:us", "finance", "trading", "stock-market", "china", "a-share", "level-2", "limit-order-book", "tick-data", "high-frequency", "market-microstructure" ]	2026-09-01T12:12:13	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	2026-10-08T03:24:02	153	30	false	e039ebffcc280174dd354227424fb2b249f191de	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...	34,547	34,547	2,166,801	[ "benchmark:official", "benchmark:eval-yaml", "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...	2026-09-16T07:42:28	null	null
639244f571c51c43091df168	Anthropic/hh-rlhf	Anthropic	{"license": "mit", "tags": ["human-feedback"]}	false	False	2023-05-26T18:47:34	2,396	26	false	09be8c5bbc57cb3887f3a9732ad6aa7ec602a1fa	Dataset Card for HH-RLHF Dataset Summary This repository provides access to two different kinds of data: Human preference data about helpfulness and harmlessness from Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. These data are meant to train p...	28,709	2,054,783	94,745,957	[ "license:mit", "size_categories:100K<n<1M", "format:json", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2204.05862", "region:us", "human-feedback" ]	2022-12-08T20:11:33	null	null
6a9560f9ba572a7516598144	openbmb/UltraData-SFT-Agent-2609	openbmb	{"language": ["en", "zh"], "license": "apache-2.0", "size_categories": ["100K<n<1M"], "task_categories": ["text-generation", "question-answering"], "pretty_name": "UltraData-SFT-Agent-2609", "tags": ["llm", "sft", "supervised-fine-tuning", "post-training", "agent", "tool-use", "function-calling", "code-agent", "search-...	false	False	2026-09-06T01:59:01	289	25	false	f684cc1a9f3e19f6f4929102cd9b06cc0b895b8a	UltraData-SFT-Agent-2609 📦 UltraData Collection \| 🌐 UltraData \| 🤗 MiniCPM5 Series English \| 中文 📚 Introduction UltraData-SFT-Agent-2609 is the L3 refined data for Agent instruction-tuning within UltraData's L0-L4 tiered data management framework. Built for the post-training...	28,524	33,233	54,221,444,130	[ "task_categories:text-generation", "task_categories:question-answering", "language:en", "language:zh", "license:apache-2.0", "size_categories:100K<n<1M", "format:json", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2602.09003", "region...	2026-08-31T11:09:45	null	null
6ab03e4d1ce52d54824a8b47	ZefanCai/Open-Jev	ZefanCai	{"license": "cc0-1.0", "language": ["en", "zh", "tr"], "task_categories": ["text-classification"], "tags": ["open-jev", "synthetic", "typed-decisions", "probability-estimation", "control"], "size_categories": ["100K<n<1M"], "configs": [{"config_name": "release-v2-redistributable", "default": true, "data_files": [{"spli...	false	False	2026-09-20T22:49:59	89	25	false	c67699e13d0ae25e35b77165a4b6b079bedc8aba	Open-Jev: typed decision datasets Open-Jev turns a state and a question into a typed decision: a yes/no probability, a distribution over choices, independent label probabilities, or a discrete numeric/ordinal decision. This repository publishes twelve separate, frozen data configs from the Open-Jev proje...	5,327	5,327	86,774,571	[ "task_categories:text-classification", "language:en", "language:zh", "language:tr", "license:cc0-1.0", "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "open-jev", "synthetic", "t...	2026-09-20T20:13:01	null	null
6abced7eb6707dec9bfc7a2b	ankitjh4/bharat-government-documents	ankitjh4	{"pretty_name": "Bharat Guide \u2014 Indian public information documents", "task_categories": ["question-answering", "text-retrieval"], "multilinguality": ["multilingual"], "license": "other", "license_name": "source-specific-rights", "license_link": "https://huggingface.co/datasets/ankitjh4/bharat-government-documents...	false	False	2026-10-04T19:19:07	57	25	false	1b76e58adbb0a69e113e27626a15b97d039d897e	Bharat Guide: screened Indian public information documents This snapshot contains 64,964 distinct normalized text bodies and 77,526 source records. Generated 2026-10-03T01:10:02.179230+00:00. Contents and provenance One Parquet row represents one normalized source body, with original extra...	749	749	171,498,827,066	[ "task_categories:question-answering", "task_categories:text-retrieval", "multilinguality:multilingual", "license:other", "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "region:us" ]	2026-09-30T11:07:42	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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