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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 | 766 | 239 | 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... | 69,711 | 69,711 | 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 |
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 | 178 | 100 | 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... | 112,775 | 112,775 | 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 |
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 | 235 | 98 | 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... | 2,177 | 2,177 | 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 | 605 | 66 | 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... | 145,230 | 145,230 | 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 |
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 | 92 | 56 | 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.
... | 1,094 | 1,240 | 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 |
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 | 260 | 50 | 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 ... | 4,544 | 4,745 | 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 |
6a75ae682e9494298b53f94c | LightwheelAI/EgoPro | LightwheelAI | {"pretty_name": "EgoSuite-Open100K - EgoPro", "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-pose... | false | manual | 2026-08-22T04:24:36 | 117 | 46 | false | c477c8d8c5052d18adfd322eb957630c0258f6bb |
EgoPro
The 10,000-hour head-and-wrist line of EgoSuite-Open100K.
Data Bucket ·
Collection ·
EgoDemo ·
EgoStandard ·
Project page
Explore EgoSuite-Open100K ↗
Data location: EgoPro is distributed through the LightwheelAI/EgoPro Bucket. This Git repository is the dataset card and access point; down... | 35,395 | 45,329 | 4,560 | [
"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",
"wrist-camera",
"multimodal",
"lerobot",
"mc... | 2026-08-07T10:07:36 | 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 | 105 | 46 | 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... | 26,430 | 26,430 | 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 |
6ab50803edb0b4d3636e2ed4 | Cirquar-Tech/wm_imagined | Cirquar-Tech | null | false | False | 2026-09-29T23:41:02 | 42 | 40 | false | ee4b42fdcefb8f4c90f97fd884126be4e3504dc0 |
Imagined Data
This repository hosts imagined interaction data generated by world models across different environments, tasks, and data sources. Data are organized into separate subdatasets, with additional types of imagined data to be added over time.
The repository currently contains only the RoboTwin2.... | 6,998 | 6,998 | 1,533,571,330,418 | [
"region:us"
] | 2026-09-24T11:22:43 | 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 | 2026-10-03T01:28:44 | 41 | 39 | false | b974a6c507424593d505665c6ad8ed221eeda1d1 |
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... | 364 | 364 | 42,760,537,830 | [
"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 |
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 | 2026-09-20T13:54:41 | 99 | 38 | false | 838b4150303ca8228e8edb432d8b8ccae353d258 |
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... | 1,537 | 3,478 | 176,865,369,812 | [
"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 |
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 | manual | 2026-10-01T21:34:12 | 139 | 38 | false | 234086a9c3de2187d3f0e535daede12381c87c4d |
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;... | 379 | 5,583 | 4,622 | [
"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 |
End of preview. Expand in Data Studio
Changelog
NEW Changes March 11th 2026
- Added new split:
arxiv_papers, sourced from the Hugging Face/api/papersendpoint paperscontinues to point todaily_papers.parquet, which is the Daily Papers feed
NEW Changes July 25th
- added
baseModelsfield 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
ggufcolumn with integer overflow causing import pipeline to be broken over a few weeks ✅
NEW Changes Feb 27th
Added new fields on the
modelssplit:downloadsAllTime,safetensors,ggufAdded new field on the
datasetssplit:downloadsAllTimeAdded new split:
paperswhich is all of the Daily Papers
Updated Daily
- Downloads last month
- 9,846