Datasets:

cfahlgren1
/

hub-stats

_id large_stringlengths 24 24	id large_stringlengths 5 123	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 2026-07-17 13:19:10	likes int64 0 9.76k	trendingScore float64 0 148	private bool 1 class	sha large_stringlengths 40 40	description large_stringlengths 0 6.67k ⌀	downloads int64 0 6.62M	downloadsAllTime int64 0 143M	mainSize float64 0 306,846B ⌀	tags listlengths 1 7.92k	createdAt timestamp[us]date 2022-03-02 23:29:22 2026-07-17 13:15:25	paperswithcode_id large_stringclasses 712 values	citation large_stringlengths 0 10.7k ⌀
6a292cbbe1b5c7903e6fbe30	openbmb/UltraX-Preview	openbmb	{"language": ["en"], "license": "apache-2.0", "size_categories": ["10B<n<100B"], "task_categories": ["text-generation"], "pretty_name": "UltraX", "tags": ["llm", "pretraining", "web-corpus", "data-refinement", "programmatic-editing", "function-calling"], "configs": [{"config_name": "UltraX-FineWeb", "data_files": [{"sp...	false	False	2026-07-17T03:02:12	204	148	false	a88527587389fd4ab352e9ad1273f4c0a234d8df	UltraX: Refining Pre-Training Data at Scale with Adaptive Programmatic Editing 📜 Paper \| 💻 Code \| 🤖 Models \| 📦 UltraData Collection English \| 中文 📚 Introduction UltraX is a function-calling refinement framework for large-scale pre-training data that ad...	1,894	1,897	486,915,481,612	[ "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:100M<n<1B", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2607.08646", "region:us", "llm", "pretraining", "web-corpus", "dat...	2026-06-10T09:22:03	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	250	71	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 ...	1,352	1,352	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
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	174	50	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...	29,415	29,415	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
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	97	44	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,...	674	715	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
69df2c30f5f5a426fc2ba699	AlicanKiraz0/Turkce-Atlas-Instruct	AlicanKiraz0	{"pretty_name": "T\u00fcrk\u00e7e Atlas \u2014 Instruct SFT", "language": ["tr"], "license": "mit", "task_categories": ["text-generation", "question-answering", "summarization"], "size_categories": ["100K<n<1M"], "tags": ["turkish", "instruction-tuning", "sft", "conversational", "chat", "text"], "configs": [{"config_na...	false	False	2026-07-12T12:00:15	39	39	false	c387738c5deacbb35667ab4057930adc34e647e8	Türkçe Atlas — Büyük Ölçekli Türkçe Instruct SFT Veri Kümesi Türkçe Atlas, Türkçe komut takibi ve sohbet modeli eğitimi için hazırlanmış, konuşma biçiminde 336.146 örnek içeren bir denetimli ince ayar (Supervised Fine-Tuning, SFT) veri kümesidir. Her kayıt tek bir messages alanından oluşur ve sabit olara...	162	165	510,891,226	[ "task_categories:text-generation", "task_categories:question-answering", "task_categories:summarization", "language:tr", "license:mit", "size_categories:100K<n<1M", "format:json", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "...	2026-04-15T06:12:00	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	625	30	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. ...	75,628	78,619	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
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	2026-07-16T18:20:04	110	23	false	f4530f12b1a1f46531f26051d66b62f2ad2de63c	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 deduplic...	10,022	10,022	497,799,384	[ "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
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	2026-07-15T07:25:03	36	22	false	4f144b7cae1107a5a59fe6356620f155d147b9c1	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 ...	10,040	10,040	8,742,973,601,503	[ "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
6a4e1fe2df56b09d5f449aa8	SupraLabs/reasoning-corpus-4K-5M-v1	SupraLabs	{"license": "apache-2.0", "task_categories": ["text-generation"], "language": ["en"], "tags": ["reasoning", "CoT", "code", "agentic", "thinking", "think", "deepseek-v4", "qwen3", "qwen3next"], "pretty_name": "Reasoning Corpus 5M", "size_categories": ["1M<n<10M"]}	false	False	2026-07-10T19:05:23	24	20	false	89fde8c507a35371978d4da7ca34b1dab3d1153f	Reasoning Corpus 5M · Within 5k sequence length About Dataset This dataset contains reasoning chains from major AI models, such as: DeepSeek-v4 (both Pro and Flash), DeepSeek-r1 (DS-r1, Llama-DS, Qwen-DS), Qwen3, Qwen3.5/3.6 (both OpenSource and API models), Gemma4-31B derived from many other reposito...	205	205	68,664,433,007	[ "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:1M<n<10M", "format:json", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "reasoning", "CoT", "code", "agentic", "thinking", "think", ...	2026-07-08T10:01:06	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	1,296	15	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...	224,984	2,610,233	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
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	42	15	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 ...	14,327	14,327	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
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	77	15	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...	8,559	8,559	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
645e8da96320b0efe40ade7a	roneneldan/TinyStories	roneneldan	{"license": "cdla-sharing-1.0", "task_categories": ["text-generation"], "language": ["en"]}	false	False	2024-08-12T13:27:26	1,072	14	false	f54c09fd23315a6f9c86f9dc80f725de7d8f9c64	Dataset containing synthetically generated (by GPT-3.5 and GPT-4) short stories that only use a small vocabulary. Described in the following paper: https://arxiv.org/abs/2305.07759. The models referred to in the paper were trained on TinyStories-train.txt (the file tinystories-valid.txt can be used for validation los...	80,771	1,555,512	7,621,978,240	[ "task_categories:text-generation", "language:en", "license:cdla-sharing-1.0", "size_categories:1M<n<10M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2305.07759", "region:us" ]	2023-05-12T19:04:09	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	2026-07-17T01:33:49	33	14	false	8e0b98ee9bce66fdae345e75aa766ef7c0a04d4e	Dataset for Vera: A Layered Diffusion Model for Content-Preserving Video Editing Hongkai Zheng¹²*  ·  Ta-Ying Cheng²  ·  Benjamin Klein²  ·  Yisong Yue¹  ·  Zhuoning Yuan²† ¹California Institute of Technology    ²Netflix, Inc. *Work done...	17,254	17,279	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
69e15643062441e6b7109caa	nvidia/Open-SWE-Traces	nvidia	{"configs": [{"config_name": "openhands", "data_files": [{"split": "minimax_m25", "path": "data/minimax_m25_openhands_trajectories/.parquet"}, {"split": "qwen35_122b", "path": "data/qwen35_openhands_trajectories/.parquet"}]}, {"config_name": "sweagent", "data_files": [{"split": "minimax_m25", "path": "data/minimax_m2...	false	False	2026-07-16T23:39:27	55	14	false	9c0e4579a4ee0effa3e5f7a552494a045f29377d	Open-SWE-Traces: Advancing Distillation for Software Engineering Agents Data Overview Open-SWE-Traces is an agentic instruction tuning dataset designed to advance the capabilities of LLMs in software engineering. This dataset comprises 200k+ agent trajectories collected using the SWE-agen...	8,013	8,264	18,338,445,575	[ "license:cc-by-4.0", "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2606.16038", "region:us", "code", "synthetic", "tools", "agents", "software" ]	2026-04-16T21:36:03	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	315	14	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...	15,830	18,897	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

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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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