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.ptb-xllatent_worker_early3_2video-vec2wav2-tokenizer-3
video-vec2wav2-tokenizer-3
Version 3 - continuation shard of the video-to-AI-dataset tokenizer project.
Version 2 - continuation shard of the video-to-AI-dataset tokenizer project.
Production-ready pipeline (Python package video_vec2wav2_tokenizer, CLI command
video2dataset) that turns a folder of videos into clean AI training datasets
for speech recognition (ASR) and text-to-speech (TTS).
videos ──► audio (16 kHz mono PCM) ──► whisper transcript ──► clips ──►… See the full description on the dataset page: https://huggingface.co/datasets/k9cli/video-vec2wav2-tokenizer-3.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.terminal-bench-3.0
Terminal-Bench 3.0
The primary source is hosted on GitHub, please open issues and pull
requests there, not here.
The official published dataset is hosted on the Harbor Hub along with the official leaderboard. Usage e.g. harbor run -d terminal-bench/terminal-bench@3.0.0
This repo is a mirror of harbor-framework/terminal-bench
at tag v3.0.0, laid out so it can be consumed directly by
Harbor's
git-repos dataset support.
How to run via this Huggingface repo
Always… See the full description on the dataset page: https://huggingface.co/datasets/harborframework/terminal-bench-3.0.3GPP
3GPP specification mirror
Part of the Open-Telco Telecom Standards Corpus.Sibling mirrors: 3GPP · ETSI · ITU-T · O-RAN · GSMA · TM Forum · CAMARA
This dataset mirrors 3GPP's published specifications. Every source is kept twice: original/ is the document as 3GPP released it, and marked/ is that same document converted to Markdown for search and retrieval, one raw.md per document with any figures extracted beside it. The two trees share identical paths, so a file in original/… See the full description on the dataset page: https://huggingface.co/datasets/GSMA/3GPP.3DCode
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.latent_v1_fullrun_alpha3_04xP3xP3 (Crosslingual Public Pool of Prompts) is a collection of prompts & datasets across 46 of languages & 16 NLP tasks. It is used for the training of BLOOMZ and mT0, multilingual language models capable of following human instructions in dozens of languages zero-shot.dolma3_mix-6T
Dolma 3 Mix (6T)
The Dolma 3 Mix (6T) is the collection of data used during the pretraining stage to train the Olmo-3-1125-32B model. This dataset is made up of ~6 trillion tokens from a diverse mix of web content, academic publications, code, and more. The majority of this dataset comes from Common Crawl.
For more information on Dolma, please see our original release here.
Smaller Sample for Analysis Available!
If you would like a smaller sample of this mix… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_mix-6T.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.dolma3.5_pool⚠️ IMPORTANT NOTICE ⚠️
This is the Dolma 3.5 pool. It contains no quality upsampling or mixing. This is an updated version of the Dolma 3 pool with additional quality filtering and more data sources.
If you are interested in the data used to train Olmo 3 7B and Olmo 3 32B, visit allenai/dolma3_mix-6T-1025.
Dolma 3.5 Pool
The Dolma 3.5 pool is a dataset of nearly 10 trillion tokens from a diverse mix of web content, academic publications, code, and more. For detailed… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3.5_pool.3D-Fronttulu-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_quorefbild-deduped-3OpenVid-1M
Summary
This is the dataset proposed in our paper [ICLR 2025] OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation.
OpenVid-1M is a high-quality text-to-video dataset designed for research institutions to enhance video quality, featuring high aesthetics, clarity, and resolution. It can be used for direct training or as a quality tuning complement to other video datasets.
All videos in the OpenVid-1M dataset have resolutions of at least 512×512.… See the full description on the dataset page: https://huggingface.co/datasets/nkp37/OpenVid-1M.srtm30m-ozt2-v2
SRTM 30m OZT2 Elevation Tiles
This dataset contains SRTM 30-meter resolution elevation data encoded in the OZT2 tile format.
Format
OZT2 is a high-performance elevation tile format:
Compression: ~93% smaller than Terrarium PNG
Prediction: Gradient-based prediction (left neighbor + vertical gradient)
Quantization: Adaptive bit-depth (8/10/12/16-bit per channel)
Codec: Zstd q3 (30× faster encode than Brotli, same decode speed)
Each tile is 256×256 pixels in Web… See the full description on the dataset page: https://huggingface.co/datasets/aliasfox/srtm30m-ozt2-v2.OakInk-v2
Dataset Card for OakInk-v2
Project: https://oakink.net/v2
Paper: https://arxiv.org/pdf/2403.19417.pdf
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.nganvo31032latent_v1_fullrun_alpha3_06dolma3_dolmino_pool⚠️ IMPORTANT NOTICE ⚠️
This is the Dolma 3 Dolmino pool; it hasn't been mixed.
If you are interested in the data used to train:
Olmo 3 7B: allenai/dolma3_dolmino_mix-100B-1025
Olmo 3 32B: allenai/dolma3_dolmino_mix-100B-1125
Dolma 3 Dolmino dataset pool for Olmo 3 stage 2 annealing training
This dataset contains the high-quality pool of data considered for the second stage of Olmo 3 7B.
Dataset Sources
Source
Category
Tokens
Documents
TinyMATH Mind… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_dolmino_pool.latent_v1_fullrun_alpha3_13latent_v1_fullrun_alpha3_01imageslatent_v1_fullrun_alpha3_05latent_v1_fullrun_alpha3_03dolma3_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.