Datasets:

cfahlgren1
/

hub-stats

_id large_stringlengths 24 24	id large_stringlengths 4 123	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 2026-07-11 13:17:26	likes int64 0 9.76k	trendingScore float64 0 81	private bool 1 class	sha large_stringlengths 40 40	description large_stringlengths 0 6.67k ⌀	downloads int64 0 5.83M	downloadsAllTime int64 0 143M	mainSize float64 0 306,846B ⌀	tags listlengths 1 7.92k	createdAt timestamp[us]date 2022-03-02 23:29:22 2026-07-11 13:17:25	paperswithcode_id large_stringclasses 712 values	citation large_stringlengths 0 10.7k ⌀
6a437ed52e089285573dcfd3	markov-ai/gaming-500-hours	markov-ai	{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "metadata.jsonl"}]}]}	false	False	2026-06-30T11:56:39	133	81	false	5af703f2810306e7d75eb4394ae59591f1f6e8a2	Gaming Dataset (gaming-1) — 494.7 Hours Native PC/console gameplay screen-recordings, organized by game. Each workflow is one play session, trimmed to pure gameplay — login screens, launchers, desktop, collection-app references, and any watching/streaming are removed. In-game menus, lobbies, loading, and...	24,465	24,465	1,598,371,626,719	[ "size_categories:n<1K", "format:json", "modality:tabular", "modality:text", "modality:video", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us" ]	2026-06-30T08:31:17	null	null
6a2cd0828137fb18cecbcc06	Glint-Research/Fable-5-traces	Glint-Research	{"license": "agpl-3.0", "pretty_name": "Fable 5 Pi Agent Traces", "annotations_creators": ["machine-generated"], "language": ["en"], "size_categories": ["1K<n<10K"], "task_categories": ["text-generation"], "tags": ["agent-traces", "pi-agent", "claude-code", "fable-5", "chain-of-thought", "tool-use", "coding-agents", "s...	false	False	2026-06-29T15:10:20	590	62	false	e05c417852fc59fd8da758e68b352732423ca0cb	Glint Research Dataset Card Fable 5 Pi Agent Traces A compact, high-signal corpus of Fable 5 coding-agent traces converted into Hugging Face Agent Traces / Pi-compatible sessions for Data Studio inspection, tool-use policy learning, and reasoning/action distillation. ...	72,356	72,356	187,507,989	[ "task_categories:text-generation", "annotations_creators:machine-generated", "language:en", "license:agpl-3.0", "size_categories:1K<n<10K", "format:json", "format:agent-traces", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", ...	2026-06-13T03:37:38	null	null
69f68e2f5ec43b12d4e2735f	LiquidAI/antidoom-mix-v1.0	LiquidAI	{"license": "apache-2.0", "license_name": "mixed-permissive-mit-apache-2.0", "language": ["en"], "size_categories": ["100K<n<1M"], "task_categories": ["text-generation"], "pretty_name": "Antidoom Mix v1.0", "tags": ["antidoom", "prompt-only", "sharegpt", "preference-training"], "configs": [{"config_name": "default", "d...	false	False	2026-07-07T12:10:58	55	54	false	a4f6fff472529f55967cbc8b73cb5e2d1490da60	Antidoom Mix v1.0 [!Note] 📝 Blog post: https://www.liquid.ai/blog/antidoom 💻 GitHub: https://github.com/Liquid4All/antidoom Antidoom Mix v1.0 is a prompt-only training mixture for antidoom-style generation and preference-data pipelines. The dataset is intended to provide prompts only. Gold answers,...	394	424	597,999,787	[ "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:100K<n<1M", "region:us", "antidoom", "prompt-only", "sharegpt", "preference-training" ]	2026-05-02T23:52:15	null	null
6a3b7528ee2af5bbf328b350	ByteDance-Seed/EdgeBench	ByteDance-Seed	{"license": "cc-by-4.0", "task_categories": ["text-generation"], "language": ["en"], "pretty_name": "EdgeBench", "size_categories": ["n<1K"], "tags": ["benchmark", "code-agents", "evaluation", "long-horizon"], "configs": [{"config_name": "tasks", "data_files": "tasks.jsonl"}]}	false	False	2026-07-09T11:28:50	62	41	false	47846a4c3669ad447e0ea984833b0d352460c5f9	Overview EdgeBench is a benchmark of 134 real-world tasks for evaluating how autonomous AI agents learn from real-world environments. Instead of measuring one-shot performance, EdgeBench places agents in executable task environments with rea...	6,490	6,490	5,102,614	[ "task_categories:text-generation", "language:en", "license:cc-by-4.0", "size_categories:n<1K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "arxiv:2607.05155", "region:us", "benchmark", "code-agents", "evaluation", "long...	2026-06-24T06:11:52	null	null
6a4cc0ac90ce9cc602189d11	FlyRank/internship-warehouse	FlyRank	{"license": "other", "language": ["en"], "tags": ["seo", "content-performance", "data-warehouse", "tabular", "education", "flyrank-internship"], "pretty_name": "FlyRank Internship \u2014 Warehouse Star Schema (Pseudonymized, Gated)", "size_categories": ["10M<n<100M"], "extra_gated_prompt": "By requesting access you agr...	false	auto	2026-07-07T10:02:21	95	37	false	50cbf7c3909d07be4d1b5906b4d09e882e5acbf2	FlyRank Internship — Pseudonymized Warehouse Release (v20260703) The open-ended, warehouse-shaped dataset (~81.8M rows; daily fact 78,835,655 rows) for advanced capstone work. Star schema with salted, namespaced, fingerprinted hash keys. Built from warehouse v2 full history (frozen snapshot, export date ...	373	373	1,168,719,310	[ "language:en", "license:other", "size_categories:10M<n<100M", "modality:tabular", "modality:text", "region:us", "seo", "content-performance", "data-warehouse", "tabular", "education", "flyrank-internship" ]	2026-07-07T09:02:36	null	null
6a3becf673d60eeb0376d121	LiquidAI/ifstruct-v1.0	LiquidAI	{"pretty_name": "IFStruct v1.0", "language": ["en"], "tags": ["structured-output", "json", "yaml", "instruction-following", "schema-following"], "task_categories": ["text-generation"], "size_categories": ["1K<n<10K"], "configs": [{"config_name": "default", "data_files": [{"split": "test", "path": "test.parquet"}]}], "l...	false	False	2026-07-07T12:32:14	71	34	false	2e342ca5f2673fb1287411fdbadcdfde82b35682	IFStruct v1.0 [!Note] 📝 Blog post: https://www.liquid.ai/blog/ifstruct-v1.0 💻 GitHub: https://github.com/Liquid4All/ifstruct IFStruct is a benchmark for structured-output compliance: can a model produce valid JSON/YAML that follows a requested schema, when the requirements are phrased the many diffe...	689	689	2,931,798	[ "benchmark:official", "benchmark:eval-yaml", "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "structured-output...	2026-06-24T14:43:02	null	null
6a34e9d01b6b6e116d313e13	Crownelius/Complete-FABLE.5-traces-2M	Crownelius	{"license": "mit", "pretty_name": "Complete FABLE.5 Traces 2M", "annotations_creators": ["machine-generated"], "language": ["en"], "language_creators": ["found", "machine-generated"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "task_categories": ["text-generation"], "task_ids": ["language-mo...	false	False	2026-07-07T06:28:23	92	30	false	e4f555103f9a00179088702abe07ab02dda23dac	Complete FABLE.5 Traces 2M Provenance-cleaned FABLE.5 / Claude corpus — trimmed to content-verified traces only. Dataset Viewer \| Parquet This dataset is a post-closure compilation of FABLE.5 / Claude trace datasets found on Hugging Face after the closure of Fable and Mythos. It is deduplicated...	8,342	8,342	307,149,644	[ "task_categories:text-generation", "task_ids:language-modeling", "annotations_creators:machine-generated", "language_creators:found", "language_creators:machine-generated", "multilinguality:monolingual", "language:en", "license:mit", "size_categories:10K<n<100K", "format:parquet", "modality:tabu...	2026-06-19T07:03:44	null	null
6a2a47c4f5ff6c6dee016974	armand0e/claude-fable-5-claude-code	armand0e	{"pretty_name": "claude-fable-5 Agent Traces", "task_categories": ["text-generation"], "tags": ["agent-traces", "format:agent-traces", "claude", "distillation", "claude-fable-5", "teich"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "*.jsonl"}]}]}	false	False	2026-06-19T16:23:10	301	23	false	c19fb6831700da833b22d1c9cdac47fe8603685c	claude-fable-5 Agent Traces It's worth noting that our team was working with Glint-Research to collect as much fable data as possible. These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this sa...	17,952	18,060	75,140,629	[ "task_categories:text-generation", "size_categories:n<1K", "format:json", "format:agent-traces", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "region:us", "agent-traces", "format:agent-traces", "claude", "distillation",...	2026-06-11T05:29:40	null	null
6a423065974497b9b32a07db	kyutai/rocket-science	kyutai	{"license": "cc-by-nc-sa-4.0", "pretty_name": "Rocket Science", "language": ["en"], "size_categories": ["1M<n<10M"], "task_categories": ["other"], "tags": ["rocket-league", "world-model", "video", "reinforcement-learning", "multimodal", "game", "webdataset"], "extra_gated_prompt": "Rocket League \u00a9 Psyonix LLC / Ep...	false	auto	2026-07-09T17:14:36	24	23	false	5beb516fd8fa26e25af54911891b40aa534e257d	Rocket Science Time-aligned video, keyboard actions, game events, and per-frame game state for all four players, captured from a 2v2 Rocket League match. This is the dataset behind MIRA, a real-time multiplayer world model trained to simulate Rocket League gameplay — by General Intuition and Kyutai, in c...	17,982	17,982	29,235,516,909,904	[ "task_categories:other", "language:en", "license:cc-by-nc-sa-4.0", "size_categories:1M<n<10M", "modality:video", "library:webdataset", "arxiv:2607.05352", "region:us", "rocket-league", "world-model", "video", "reinforcement-learning", "multimodal", "game", "webdataset" ]	2026-06-29T08:44:21	null	null
6a3907f29ed50d27aa76cb3a	bigfacing/GOKU-2M	bigfacing	{"license": "cc-by-nc-4.0", "task_categories": ["text-to-video", "video-to-video"], "language": ["en"], "tags": ["video-editing", "instruction-based-editing", "video"], "size_categories": ["1M<n<10M"]}	false	auto	2026-07-05T14:26:56	28	20	false	f289f4b245648dc57db04afaaeb68659440c0fa6	Goku: A Million-Scale Universal Dataset and Benchmark for Instruction-Based Video Editing GOKU-2M is a large-scale, unified instruction-based video-editing dataset covering 10 editing tasks. Each sample provides a source video, an edited target video, and one or more natural-language instructions ...	13,336	13,336	5,110,664,518,059	[ "task_categories:text-to-video", "task_categories:video-to-video", "language:en", "license:cc-by-nc-4.0", "size_categories:1M<n<10M", "modality:image", "modality:video", "arxiv:2606.30599", "region:us", "video-editing", "instruction-based-editing", "video" ]	2026-06-22T10:01:22	null	null
670befa7623c91990f914eb6	mlabonne/open-perfectblend	mlabonne	{"dataset_info": {"features": [{"name": "conversations", "list": [{"name": "from", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "source", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2951380166, "num_examples": 1420909}], "download_size": 1483360321, "dataset_size": 2951380166}...	false	False	2025-01-15T20:01:32	165	19	false	af60f3c18201652a83a93f46fcfee1b646ba3df7	🎨 Open-PerfectBlend Open-PerfectBlend is an open-source reproduction of the instruction dataset introduced in the paper "The Perfect Blend: Redefining RLHF with Mixture of Judges". It's a solid general-purpose instruction dataset with chat, math, code, and instruction-following data. Data s...	4,639	16,733	1,483,365,514	[ "license:apache-2.0", "arxiv:2409.20370", "region:us" ]	2024-10-13T16:04:55	null	null
69d185a53c023c2c9072697a	netflix/Vera-Layered-Video-Dataset	netflix	{"license": "apache-2.0", "task_categories": ["text-to-video"], "tags": ["diffusion", "layered-diffusion", "video", "layered-video-dataset", "video-editing", "video-generation"]}	false	False	2026-06-29T02:13:49	21	19	false	d56723462a1cfbeeb8854ef96a634eccdbb70b80	Dataset for Vera: A Layered Diffusion Model for Content-Preserving Video Editing Hongkai Zheng¹²*  ·  Ta-Ying Cheng²  ·  Benjamin Klein²  ·  Yisong Yue²  ·  Zhuoning Yuan²† ¹California Institute of Technology    ²Netflix, Inc. *Work done...	12,452	12,475	319,639,945,834	[ "task_categories:text-to-video", "license:apache-2.0", "size_categories:10K<n<100K", "modality:video", "arxiv:2606.23610", "region:us", "diffusion", "layered-diffusion", "video", "layered-video-dataset", "video-editing", "video-generation" ]	2026-04-04T21:41:57	null	null
6a2a1f91f76bc9ca45b048d1	CMRobot/MotionDecode	CMRobot	{"dataset_info": {"license": "other", "license_name": "chingmu-terms", "license_link": "LICENSE", "language": ["en", "zh"], "pretty_name": "ChingMu Robot Motion Dataset", "tags": ["motion-capture", "humanoid-robotics", "imitation-learning", "optical-mocap", "bvh", "dexterous-hands", "whole-body-control"], "size_categor...	false	False	2026-07-08T02:03:19	20	18	false	888bc2706c0fc3b12e21912cb4a9c84c5ccb4bb8	ChingMu 1000-Hour Embodied Motion Dataset High-precision optical motion capture data for humanoid robots, dexterous hands, embodied AI, and virtual production. Duration 1000+ hours @ 120 Hz Scenarios 15+ real-world scenes Tasks 500+ standardized tasks Objects 200+ tracked...	7,254	7,287	56,505,014,934	[ "region:us" ]	2026-06-11T02:38:09	null	null
625552d2b339bb03abe3432d	openai/gsm8k	openai	{"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-generation"], "task_ids": [], "paperswithcode_id": "gsm8k", "pretty_na...	false	False	2026-03-23T10:18:13	1,439	16	false	740312add88f781978c0658806c59bc2815b9866	Dataset Card for GSM8K Dataset Summary GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems. The dataset was created to support the task of question answering on basic mathematical problems that require multi-step reasoning. ...	977,142	13,327,648	5,900,352	[ "benchmark:official", "benchmark:eval-yaml", "task_categories:text-generation", "annotations_creators:crowdsourced", "language_creators:crowdsourced", "multilinguality:monolingual", "source_datasets:original", "language:en", "license:mit", "size_categories:10K<n<100K", "format:parquet", "modal...	2022-04-12T10:22:10	gsm8k	null
6a4690678f943cc81115bbd0	ProCreations/grug-think	ProCreations	{"license": "apache-2.0", "task_categories": ["text-generation"], "language": ["en"], "tags": ["function-calling", "tool-use", "agents", "reasoning", "synthetic", "grug"], "pretty_name": "grug-think", "size_categories": ["100K<n<1M"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "dat...	false	False	2026-07-09T05:46:25	21	16	false	7d7bd0660d7649628f98e4b4cb62b39c29746b4b	grug-think grug make dataset. dataset make model think like grug. grug think short. short think cheap. cheap think good. big-brain model think 400 token before poke one tool. grug model think 11 word. same tool poke. same work done. many token saved. token = money. grug like money stay in pocket. ...	394	394	1,481,131,372	[ "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:100K<n<1M", "format:json", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "function-calling", "tool-use", "agents", "reasoning", "synth...	2026-07-02T16:23:03	null	null
6a4392395e59e531d1fc5ffd	sensenova/SenseNova-Vision-Corpus-50M	sensenova	{"language": ["en"], "license": "cc-by-nc-4.0", "size_categories": ["10M<n<100M"], "pretty_name": "SenseNova-Vision-Corpus-50M", "task_categories": ["any-to-any"], "configs": [{"config_name": "Structure", "default": true, "data_files": [{"split": "train", "path": "SenseNova-Vision_structure_300samples.parquet"}]}, {"co...	false	False	2026-07-10T06:56:02	15	15	false	9864efa37fb9666cbedef21f738d341938026ddf	Vision as Unified Multimodal Generation English \| 简体中文 This repository contains the dataset for the paper Vision as Unified Multimodal Generation. SenseNova Vision Corpus 50M Overview SenseNova Vision Corpus 50M (SN-VC-50M) is a large-scale multimodal ...	3,859	3,859	8,743,018,259,571	[ "task_categories:any-to-any", "language:en", "license:cc-by-nc-4.0", "size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "arxiv:2607.06560", "region:us" ]	2026-06-30T09:54:01	null	null
6a3404497e03daf35bd3202e	scholarweave/arxiv-latex	scholarweave	{"license": "other", "license_name": "dual-license", "license_link": "LICENSE", "task_categories": ["text-generation", "feature-extraction"], "language": ["en"], "tags": ["science", "arxiv", "latex", "academic"], "pretty_name": "arXiv LaTeX Source Dataset", "size_categories": ["1M<n<10M"], "configs": [{"config_name": "...	false	False	2026-07-11T11:33:29	69	14	false	fe768a240d684ee5eaa3506d80c568e21395cb3a	arXiv LaTeX Source Dataset This dataset provides the entire corpus of arXiv's LaTeX source files, pre-parsed, formatted, and aligned with official metadata in ready-to-query Parquet files. Why I Built This If you have ever tried to work with the complete histor...	31,177	31,177	287,414,291,874	[ "task_categories:text-generation", "task_categories:feature-extraction", "language:en", "license:other", "size_categories:1M<n<10M", "modality:text", "region:us", "science", "arxiv", "latex", "academic" ]	2026-06-18T14:44:25	null	null
6a382f6fa519cd301493b37b	Syn4D/Syn4D	Syn4D	{"license": "cc-by-4.0", "arxiv": 2605.05207, "pretty_name": "Syn4D: A Multiview Synthetic 4D Dataset", "viewer": false}	false	False	2026-07-08T17:00:26	16	14	false	181c6a2da735b216826ab9411b08e0d1d225aced	Syn4D: A Multiview Synthetic 4D Dataset Syn4D is a synthetic 4D dataset with multi-view RGB videos, depth, masks, tracking geometry, and supporting object mesh metadata. Layout data/ syn4d_v1_stride_1/ # Syn4D V1, every frame can be a tracking reference frame syn4d_v1_stride_...	18,575	18,575	1,701,805,420,189	[ "license:cc-by-4.0", "arxiv:2605.05207", "region:us" ]	2026-06-21T18:37:35	null	null
6a394ba974e3ccb07645f8a7	Qwen/AgentWorldBench	Qwen	{"license": "apache-2.0", "task_categories": ["text-generation"], "language": ["en"], "tags": ["world-model", "agent", "benchmark", "evaluation", "environment-simulation", "qwen"], "size_category": "1K<n<10K"}	false	False	2026-07-04T12:59:38	76	14	false	6b8d28437042434dcdd168434227ca0de408c5ba	AgentWorldBench AgentWorldBench is a comprehensive evaluation benchmark for language world models, constructed from real-world observations of frontier model trajectories on established benchmarks such as Tool Decathlon, Terminal-Bench 1.0 & 2.0, and OSWorld-Verified. Every evaluation sample is paired wi...	2,321	2,321	257,213,344	[ "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:1K<n<10K", "format:json", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2606.24597", "region:us", "world-model", "agent", ...	2026-06-22T14:50:17	null	null
6a49979953e5330d3a43e0c4	SupraLabs/reasoning-summaries-61k	SupraLabs	{"license": "apache-2.0", "task_categories": ["summarization", "text-generation"], "language": ["en"], "tags": ["reasoning", "summary", "summarization", "reasoning-summary"], "pretty_name": "Rewritten Reasoning Chains", "size_categories": ["10K<n<100K"]}	false	False	2026-07-05T02:21:57	14	14	false	1e93e6769b7ee4967d38a089b6bf55a56a3830a3	Reasoning Summaries · 61K cleaned samples Reasoning summary dataset is a dataset that summarizes and adds extra metadata to a reasoning chain or a block from the reasoning chain (for models like qwen3.5+, gemma4, GLM-5.2) About Dataset This dataset is designed for training and evaluating reasoning s...	168	168	79,389,987	[ "task_categories:summarization", "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:10K<n<100K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "arxiv:2103.03874", "region:us", "reasoning"...	2026-07-04T23:30:33	null	null
6a3bf717fc9799bfca0ced29	RekaAI/CS2-10k	RekaAI	{"license": "cc-by-nc-4.0", "pretty_name": "CS2-10k", "task_categories": ["other"], "tags": ["counter-strike", "cs2", "gaming", "egocentric", "first-person", "video", "world-models", "imitation-learning", "action-prediction", "webdataset"], "size_categories": ["100K<n<1M"], "configs": [{"config_name": "default", "data_...	false	False	2026-06-29T17:14:11	26	13	false	5bff96ad139daec3b83a42590a024a7f6cff8cf7	CS2-10k: A Large-Scale Egocentric Counter-Strike 2 Dataset CS2-10k is a large-scale egocentric gameplay dataset built from professional CS2 matches. It contains 600,000+ player-round videos spanning 10,000+ hours of first-person footage, paired with per-frame annotations covering keyboard state, m...	70,774	70,774	63,484,680,387,407	[ "task_categories:other", "license:cc-by-nc-4.0", "size_categories:100K<n<1M", "modality:video", "library:webdataset", "region:us", "counter-strike", "cs2", "gaming", "egocentric", "first-person", "video", "world-models", "imitation-learning", "action-prediction", "webdataset" ]	2026-06-24T15:26:15	null	null
69b0a69caab02f7aaec0e66f	bones-studio/seed	bones-studio	{"license": "other", "license_name": "bones-seed-license", "license_link": "https://bones.studio/info/seed-license", "task_categories": ["robotics", "text-to-video", "video-text-to-text"], "tags": ["motion-capture", "humanoid-robotics", "human-motion", "physical-ai", "whole-body-control", "NVIDIA-SOMA", "Unitree-G1", "...	false	auto	2026-05-03T15:03:12	178	12	false	2f59b2077b9da34dd4e43618e705c7cb962c9a66	BONES-SEED: Skeletal Everyday Embodiment Dataset BONES-SEED is an open dataset of 142,220 annotated human motion animations for humanoid robotics. It provides motion capture data in SOMA and Unitree G1 formats, with natural language descriptions, temporal segmentation, and detailed skeletal metadata. Proj...	3,209	19,285	null	[ "task_categories:robotics", "task_categories:text-to-video", "task_categories:video-text-to-text", "language:en", "license:other", "size_categories:100K<n<1M", "region:us", "motion-capture", "humanoid-robotics", "human-motion", "physical-ai", "whole-body-control", "NVIDIA-SOMA", "Unitree-G...	2026-03-10T23:17:48	null	null
6a05fb804b04c5157df46866	WithinUsAI/claude_mythos_distilled_25k	WithinUsAI	{"license": "apache-2.0", "language": ["en"], "tags": ["synthetic", "claude", "mythos", "distillation", "cybersecurity", "coding", "reasoning", "agentic", "frontier-model-mirror", "sft", "instruction-tuning"], "size_categories": ["10K<n<100K"], "pretty_name": "Claude Mythos Distilled 25K", "dataset_info": {"features": ...	false	False	2026-05-18T00:45:03	153	12	false	2c5e638c51a22b8b883def51bab685ae7e282c72	Claude Mythos Distilled 25K A high-quality synthetic supervised fine-tuning (SFT) dataset designed to train and fine-tune any LLM to mirror the capabilities, reasoning style, agentic behavior, and technical depth of Anthropic's Claude Mythos (distilled frontier model). Dataset Summary Siz...	3,972	5,128	55,202,753	[ "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", "synthetic", "claude", "mythos", "distillation", "cybersecurity", "coding", "reasoning", "a...	2026-05-14T16:42:40	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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