datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
P3
Dataset Card for P3
Dataset Summary
P3 (Public Pool of Prompts) is a collection of prompted English datasets covering a diverse set of NLP tasks. A prompt is the combination of an input template and a target template. The templates are functions mapping a data example into natural language for the input and target sequences. For example, in the case of an NLI dataset, the data example would include fields for Premise, Hypothesis, Label. An input template would be If… See the full description on the dataset page: https://huggingface.co/datasets/bigscience/P3.stack-v3-train
🥞 The Stack v3
What is it?
What is being released
How to download and use it
Dataset statistics
Dataset structure
Dataset creation
Considerations for using the data
Additional information
What is it?
The Stack v3 is the largest, most up-to-date open dataset of source code, crawled directly from GitHub and built to pre-train code LLMs with full-repository context. It is the successor to The Stack v2 and, like its predecessor, is released to make the training… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceCode/stack-v3-train.agibot_alpha_v30This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "AgiBot_A2D",
"total_episodes": 28122,
"total_frames": 47613574,
"total_tasks": 30,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 500,
"fps": 30,
"splits": {
"train": "0:28122"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/cadene/agibot_alpha_v30.tulu-3-sft-mixture
Tulu 3 SFT Mixture
Note that this collection is licensed under ODC-BY-1.0 license; different licenses apply to subsets of the data. Some portions of the dataset are non-commercial. We present the mixture as a research artifact.
The Tulu 3 SFT mixture was used to train the Tulu 3 series of models.
It contains 939,344 samples from the following sets:
CoCoNot (ODC-BY-1.0), 10,983 prompts (Brahman et al., 2024)
FLAN v2 via ai2-adapt-dev/flan_v2_converted, 89,982 prompts (Longpre et… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-mixture.multispan_quoref3DCode
Project page
Paper
Code
3dcodebench.com
arXiv:2606.01057
gaoypeng/3dcodebench
News
[06/01/2026] Paper released on arXiv: 3DCodeBench: Benchmarking Agentic Procedural 3D Modeling Via Code.
Note. This is an open-source reproduction of 3DCodeBench.
⚠️ Under final check. The 3DCodeData/ code is still undergoing final
quality review and may contain occasional issues (non-executable scripts, mismatched
captions/renders, or imperfect geometry). If you run… See the full description on the dataset page: https://huggingface.co/datasets/YipengGao/3DCode.deform360
Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models
Project Page | Paper | GitHub Repository
Deform360 is a massive multi-view visuotactile dataset for deformable-object research, featuring 198 daily-life objects, 1,980 interaction sequences, and over 215 hours of observations from 41 surround-view cameras and bimanual tactile grippers to capture both global motion and contact-induced local deformations.
Where the data lives… See the full description on the dataset page: https://huggingface.co/datasets/brownu/deform360.dolma3_pool⚠️ IMPORTANT NOTICE ⚠️
This is the Dolma 3 pool, pre–quality upsampling and mixing.
If you are interested in the data used to train Olmo 3 7B and Olmo 3 32B, visit allenai/dolma3_mix-6T-1025.
Dolma 3 Pool
The Dolma 3 pool is a dataset of over 9 trillion tokens from a diverse mix of web content, academic publications, code, and more. For detailed documenation on Dolma 3 processing and data, please see our Dolma 3 Github repository. For more information on Dolma in general… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_pool.Ultra-FineWeb-L3
Ultra-FineWeb-L3
📜 Ultra-FineWeb Technical Report |
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
Ultra-FineWeb-L3 is the L3 refined data for general high-quality web data within UltraData's L0-L4 tiered data management framework. Moving beyond L2 quality selection, it transforms high-value web corpora into structured, high-learnability training data with clearer reasoning signals and richer educational… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/Ultra-FineWeb-L3.BVD-I-300M-URLs
LAION-BVD - 300M Video Frame URLs
This repository contains the URLs for ~300 million keyframes extracted from publicly available web videos. No image data is included, only the source video URL and the frame timestamp needed to reproduce each frame.
Frames were extracted from BVD-RAW and cover YouTube, Dailymotion, and Vimeo content.
Dataset structure
Column
Type
Description
webpage_url
string
URL of the source video
frame_pts_time
float
Presentation… See the full description on the dataset page: https://huggingface.co/datasets/laion/BVD-I-300M-URLs.TxT360-v2
TxT360-v2
Dataset Description
Pre-training sources for the K2 Horizon training data release. This repository is part of the K2 Horizon collection.
The repository is organized into multiple subsets. Every subset has a train split backed by Parquet shards.
K2 Horizon Dataset Series
Dataset repository
Focus
Subsets
IFM/TxT360-v2
Web and question-answering text
3
IFM/Code-Reasoning
Code reasoning and task synthesis
7
IFM/Math-Reasoning… See the full description on the dataset page: https://huggingface.co/datasets/IFM/TxT360-v2.3D-ADAMRepository for the 3D-ADAM (3D Anomaly Detection in Additive Manufacturing) Dataset. This is the raw data for our complete dataset, separated by part-instance to allow users to utilise the dataset as desired.
We provide a single-camera (using the MechMind-Nano) subset prepared for unsupervised training at anomaly detection, localisation and segementation tasks through the anomalib library in a separate repository: here
Our ArXiv paper can also be found here: 3D-ADAM Dataset
This project has… See the full description on the dataset page: https://huggingface.co/datasets/pmchard/3D-ADAM.OpenThoughts3-1.2M
paper |
dataset |
model
[!NOTE]
We have released a paper for OpenThoughts! See our paper here.
OpenThoughts3-1.2M
Open-source state-of-the-art reasoning dataset with 1.2M rows. 🚀
OpenThoughts3-1.2M is the third iteration in our line of OpenThoughts datasets, building on our previous OpenThoughts-114k and OpenThoughts2-1M.
This time around, we scale even further and generate our dataset in a much more systematic way -- OpenThoughts3-1.2M is the result of a… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts3-1.2M.symile-m3
Dataset Card for Symile-M3
Symile-M3 is a multilingual dataset of (audio, image, text) samples. The dataset is specifically designed to test a model's ability to capture higher-order information between three distinct high-dimensional data types: by incorporating multiple languages, we construct a task where text and audio are both needed to predict the image, and where, importantly, neither text nor audio alone would suffice.
Paper: https://arxiv.org/abs/2411.01053
GitHub:… See the full description on the dataset page: https://huggingface.co/datasets/arsaporta/symile-m3.VideoChat3-LV116k
VideoChat3-LV116K
VideoChat3-LV116K is the long-video instruction data used by VideoChat3. It is designed to complement short academic video data with supervision over longer temporal contexts, where evidence can be sparse, delayed, and distributed across multiple video segments.
The dataset is constructed through a long-video synthesis pipeline. Candidate long videos are filtered for visual quality, semantic content, and temporal coherence. Videos are then split into manageable… See the full description on the dataset page: https://huggingface.co/datasets/MCG-NJU/VideoChat3-LV116k.GTSinger
GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks
Yu Zhang*, Changhao Pan*, Wenxiang Guo*, Ruiqi Li, Zhiyuan Zhu, Jialei Wang, Wenhao Xu, Jingyu Lu, Zhiqing Hong, Chuxin Wang, LiChao Zhang, Jinzheng He, Ziyue Jiang, Yuxin Chen, Chen Yang, Jiecheng Zhou, Xinyu Cheng, Zhou Zhao | Zhejiang University
Dataset of GTSinger (NeurIPS 2024 Spotlight): A Global Multi-Technique Singing Corpus with Realistic Music Scores for All… See the full description on the dataset page: https://huggingface.co/datasets/AaronZ345/GTSinger.deform360
Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models
Project Page | Paper | GitHub Repository
Deform360 is a massive multi-view visuotactile dataset for deformable-object research, featuring 198 daily-life objects, 1,980 interaction sequences, and over 215 hours of observations from 41 surround-view cameras and bimanual tactile grippers to capture both global motion and contact-induced local deformations.
Installation
To load and… See the full description on the dataset page: https://huggingface.co/datasets/liuyibing/deform360.LAION-Audio-300MGPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.tulu-3-sft-personas-instruction-following
Dataset Descriptions
This dataset contains 29980 examples and is synthetically created to enhance model's capabilities to follow instructions precisely and to satisfy user constraints. The constraints are borrowed from the taxonomy in IFEval dataset.
To generate diverse instructions, we expand the methodology in Ge et al., 2024 by using personas. More details and exact prompts used to construct the dataset can be found in our paper.
Curated by: Allen Institute for AI
Paper: TBD… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-personas-instruction-following.the-stack-v2-smollm3
The Stack v2 — materialized source code
Upstream dataset:
bigcode/the-stack-v2
Exact upstream commit:
e565caa3a78c2423bd374333a472b049eb090e47
Primary source-content endpoint:
https://softwareheritage.s3.amazonaws.com/content/{blob_id}
Configurations
TypeScript
Swift
Ruby
Rust
Go
Shell
Jupyter_Notebook
HTML
Python
Java
JavaScript
C
C++
C-Sharp
PHP
SQL
Markdown
Added columns
content: decoded source content
download_error: null on successful… See the full description on the dataset page: https://huggingface.co/datasets/jordangong/the-stack-v2-smollm3.M3_VOS
[CVPR 2025] M3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object Segmentation
If you like our project, please give us a star ⭐ on GitHub for the latest update.
💡 Description
Venue: CVPR2025
Repository: 🛠️Tool, 🏠Page
Paper: arxiv.org/html/2412.13803v2
Point of Contact: Jiaxin Li , Zixuan Chen
📁 Structure
This dataset contains annotated videos and images for object segmentation tasks with phase transition information. The directory… See the full description on the dataset page: https://huggingface.co/datasets/Lijiaxin0111/M3_VOS.dolma3_mix-6T-1025-7B
⚠️ WARNING: This dataset is intended ONLY for reproducing Olmo 3 7B ⚠️
For all other training use cases, including training from scratch, please utilize our primary dolma 3 data mix: https://huggingface.co/datasets/allenai/dolma3_mix-6T.
Note: Some olmOCR science PDFs in the current dataset have been redacted following the training of Olmo 3 7B. These texts are indicated with [REMOVED] in the text field. This will affect reproducibility of Olmo 3 7B.
For this reason, please use… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_mix-6T-1025-7B.genshin-voice
Genshin Voice
Genshin Voice is a dataset of voice lines from the popular game Genshin Impact.
Hugging Face 🤗 Genshin-Voice
ModelScope Genshin-Voice
Per-speaker downloads are grouped by language and ZIP size. Browse every archive in the ZIP index.
Last update at 2026-08-13
654252 wavs
7291 without speaker (1%)
52693 without transcription (8%)
1088 without inGameFilename (0%)
Dataset Details
Dataset Description
The dataset contains voice lines… See the full description on the dataset page: https://huggingface.co/datasets/simon3000/genshin-voice.cc3m-wds
Dataset Card for Conceptual Captions (CC3M)
Dataset Summary
Conceptual Captions is a dataset consisting of ~3.3M images annotated with captions. In contrast with the curated style of other image caption annotations, Conceptual Caption images and their raw descriptions are harvested from the web, and therefore represent a wider variety of styles. More precisely, the raw descriptions are harvested from the Alt-text HTML attribute associated with web images. To arrive at the… See the full description on the dataset page: https://huggingface.co/datasets/pixparse/cc3m-wds.behaviour1k-Qwen3-features
BEHAVIOR-1K Qwen3 skill features
Per-frame conditioned features e_t = Phi(f_t, L_sub^(j), L), mean-pooled primitive skill latents S_j, aligned proprioception q_t, actions a_t, and subtask progress p_t.
These are the inputs and targets for a Primitive Skill Composer VLA Skill Predictor.
Ground-truth primitives come from BEHAVIOR-1K's hand-authored
primitive_annotation, so the segmentation is human-labelled rather than
predicted, and nothing here depends on a keyframe detector.… See the full description on the dataset page: https://huggingface.co/datasets/erl-hub/behaviour1k-Qwen3-features.TxT360-Midas
TxT360-MidAS: Mid-training Actual and Synthetic data
Dataset Summary
TxT360-Midas is a mid-training dataset designed to extend language model context length up to 512k tokens while injecting strong reasoning capabilities via synthetic data.
TxT360-Midas was used to mid-train the K2-V2 LLM, yielding base model with strong long-context performance and reasoning abilities. Resulting model demonstrates strong performance on complex mathematical and logic puzzle tasks.… See the full description on the dataset page: https://huggingface.co/datasets/IFM/TxT360-Midas.dolma3_dolmino_mix-100B-1025
Dolma 3 Dolmino Mix (100B)
The Dolma 3 Dolmino Mix (100B) is the mixture of high-quality data used for the second stage of training for Olmo 3 7B model.
Dataset Sources
Source
Category
Tokens
Documents
TinyMATH Mind
Math (synth)
898M (0.9%)
1.52M
TinyMATH PoT
Math (synth)
241M (0.24%)
758K
CraneMath
Math (synth)
5.62B (5.63%)
7.24M
MegaMatt
Math (synth)
1.73B (1.73%)
3.23M
Dolmino Math
Math (synth)
10.7B (10.7%)
22.3M
StackEdu (FIM)
Code
10.0B… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_dolmino_mix-100B-1025.Openthoughts_math_30k_opsdWan2.2-Syn-121x704x1280_32k
FastVideo Synthetic Wan2.2 720P dataset
FastVideo Team
Paper |
Github |
Project Page
Abstract
Scaling video diffusion transformers (DiTs) is limited by their quadratic 3D attention, even though most of the attention mass concentrates on a small subset of positions. We turn this observation into VSA, a trainable, hardware-efficient sparse attention that replaces full attention at \emph{both} training and inference. In VSA, a… See the full description on the dataset page: https://huggingface.co/datasets/Hahshshsshbs/Wan2.2-Syn-121x704x1280_32k.