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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | 216 | 192 | 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... | 12,263 | 12,263 | 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 | 908 | 95 | 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... | 113,898 | 113,898 | 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 |
6a75aed0ed632a5e84e266c7 | LightwheelAI/EgoDemo | LightwheelAI | {"pretty_name": "EgoSuite-Open100K - EgoDemo", "language": ["en"], "license": "other", "license_name": "commercial-training-no-resale-v1.0", "size_categories": ["1K<n<10K"], "task_categories": ["video-classification"], "tags": ["video", "egocentric-video", "embodied-ai", "human-demonstration", "public-demo", "provenanc... | false | manual | 2026-10-10T01:18:07 | 187 | 51 | false | 407b960db2fe1c91b75854848d49c5cf920f68b9 |
EgoDemo
A 50-hour sample from EgoSuite-Open100K, covering every annotated subset plus two raw-video variants.
Collection ·
EgoStandard ·
EgoPro ·
Project page
Explore EgoSuite-Open100K ↗
EgoSuite-Open100K Overview
Collection:
EgoSuite-Open10... | 61,148 | 176,519 | 1,477,463,053,328 | [
"task_categories:video-classification",
"language:en",
"license:other",
"size_categories:1K<n<10K",
"modality:video",
"region:us",
"video",
"egocentric-video",
"embodied-ai",
"human-demonstration",
"public-demo",
"provenance",
"human-pose",
"hand-pose",
"body-pose",
"wrist-camera",
"... | 2026-08-07T10:09:20 | 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 | 2026-10-10T01:15:03 | 175 | 42 | false | 3f71c7e2df7dd40a7bccd59e8ab37d22d442d141 |
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... | 34,529 | 45,500 | 24,220 | [
"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 |
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 | 63 | 40 | 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... | 1,592 | 1,770 | 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 |
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 | 232 | 37 | 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... | 225,009 | 225,009 | 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 |
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 | 293 | 36 | 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... | 3,501 | 3,501 | 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 |
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 | 2026-10-10T12:16:08 | 300 | 34 | false | 4904ca0c09044f447aff16e4f66b6f2f53c9f702 |
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 ... | 5,286 | 5,942 | 2,538,730,713 | [
"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 |
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 | 657 | 34 | 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... | 175,887 | 175,890 | 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 |
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 | 34 | 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... | 5,457 | 5,534 | 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 | 238 | 28 | 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... | 86,479 | 91,736 | 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 |
6ac31f1b2983b839ba627404 | harvardMadsys/freeinference_agentic_trace | harvardMadsys | {"pretty_name": "FreeInference Agentic Trace", "license": "cc-by-4.0", "tags": ["agents", "llm-inference", "tool-use", "prefix-caching", "traces"], "size_categories": ["1M<n<10M"], "configs": [{"config_name": "traces", "default": true, "data_files": [{"split": "week_2026_05_17", "path": "viewer/traces/2026-05-17_2026-0... | false | False | 2026-10-06T21:27:44 | 29 | 28 | false | 90a627adefb7f7b88708484bcbea64010f76492a |
FreeInference Agentic Trace
This dataset contains 16 weeks (2026-05-17 to 2026-09-05) of coding and assistant agents interacting with LLMs through the FreeInference gateway: 12,002 agent sessions from 267 accounts and 14 agent harnesses, with 1,186,582 LLM requests and 1,213,347 tool calls.
The dataset ... | 1,122 | 1,122 | 8,933,343,127 | [
"license:cc-by-4.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"agents",
"llm-inference",
"tool-use",
"prefix-caching",
"traces"
] | 2026-10-05T03:52:59 | 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 | 2026-10-10T06:59:27 | 161 | 26 | false | 6a7927fa3c8ac114e29f5300eacb86f6f37a6447 |
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... | 38,542 | 38,542 | 2,166,985 | [
"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 |
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 | 55 | 22 | 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 ... | 3,324 | 9,884 | 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 | 127 | 22 | 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... | 2,076 | 4,058 | 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 |
6ac7c84c08d72b7d5fe7f7ca | FineEnvs/openai-math | FineEnvs | {"license": "apache-2.0", "task_categories": ["other"], "tags": ["harbor", "rl-environment", "reinforcement-learning", "code-agent", "lean4", "mathlib", "theorem-proving", "openai-math"], "pretty_name": "openai/math as Harbor environments"} | false | False | 2026-10-09T05:53:45 | 22 | 22 | false | d7056fd31c19fd1a0aed0a0bc3e99026d412b2ca |
openai/math as Harbor environments
Experimental. Built on a research release that is itself new and not yet independently
reviewed. Expect rough edges, and read any proof that scores 1 before relying on it.
We ported the math problems from OpenAI's openai/math release
(commit adc7f12) into Harbor envir... | 1,810 | 1,810 | 27,355,650 | [
"task_categories:other",
"license:apache-2.0",
"size_categories:n<1K",
"modality:text",
"library:datasets",
"library:harbor",
"library:mlcroissant",
"region:us",
"harbor",
"rl-environment",
"reinforcement-learning",
"code-agent",
"lean4",
"mathlib",
"theorem-proving",
"openai-math"
] | 2026-10-08T16:43:56 | 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
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