datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
documentation-images
This dataset contains images used in the documentation of HuggingFace's libraries.
HF Team: Please make sure you optimize the assets before uploading them.
My favorite tool for this is https://tinypng.com/.
banned-historical-archives
和谐历史档案馆数据集 - Banned Historical Archives Datasets
和谐历史档案馆数据集包含已录入 https://banned-historical-archives.github.io 和暂未未录入的原始文件。
目录结构
banned-historical-archives.github.io # 已录入该网站的原始数据，不定期从 github 仓库中同步
raw # 原始文件
config # 配置文件
todo # 存放暂未录入网站的文件
部分报纸和图片资料存放在单独的仓库:
名称
地址
状态
参考消息
https://huggingface.co/datasets/banned-historical-archives/ckxx
未录入
人民日报
https://huggingface.co/datasets/banned-historical-archives/rmrb
已精选重要的文章录入
文汇报… See the full description on the dataset page: https://huggingface.co/datasets/banned-historical-archives/banned-historical-archives.imgbedosworld_v2_assetsgeonamebase_1the_cauldron
Dataset Card for The Cauldron
Dataset description
The Cauldron is part of the Idefics2 release.
It is a massive collection of 50 vision-language datasets (training sets only) that were used for the fine-tuning of the vision-language model Idefics2.
Load the dataset
To load the dataset, install the library datasets with pip install datasets. Then,
from datasets import load_dataset
ds = load_dataset("HuggingFaceM4/the_cauldron", "ai2d")
to download… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceM4/the_cauldron.course-imagesdocumentation-imagesjat-dataset
JAT Dataset
Dataset Description
The Jack of All Trades (JAT) dataset combines a wide range of individual datasets. It includes expert demonstrations by expert RL agents, image and caption pairs, textual data and more. The JAT dataset is part of the JAT project, which aims to build a multimodal generalist agent.
Paper: https://huggingface.co/papers/2402.09844
Usage
>>> from datasets import load_dataset
>>> dataset =… See the full description on the dataset page: https://huggingface.co/datasets/jat-project/jat-dataset.imgbedbadges
Badges
A set of badges you can use anywhere. Just update the anchor URL to point to the correct action for your Space. Light or dark background with 4 sizes available: small, medium, large, and extra large.
How to use?
With markdown, just copy the badge from: https://huggingface.co/datasets/huggingface/badges/blob/main/README.md?code=true
With HTML, inspect this page with your web browser and copy the outer html.
Available sizes
Small
Medium… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/badges.RekaDaily-10k-raw
RekaDaily-10k (raw)
Raw, unscripted, first-person daily-life video, collected through
Claru, Reka's data collection marketplace — recorded by
paid collectors in their own homes and workplaces on head-mounted and handheld
phones, across multiple regions.
Videos are delivered as recorded — no cuts, no trimming, no editing, no
filtering beyond basic integrity checks. A processed tier (short clips with
machine captions) is released separately under the same RekaDaily-10k prefix.… See the full description on the dataset page: https://huggingface.co/datasets/RekaAI/RekaDaily-10k-raw.terminal-bench-2.1
Terminal-Bench 2.1 (Harbor git-repos dataset)
Harbor website · Harbor GitHub
This is a private mirror of the task content from
harbor-framework/terminal-bench-2-1
at commit 7131e43
(the source repo has no tagged releases yet), laid out so it can be consumed directly
by Harbor's
git-repos dataset support.
The primary source is the GitHub repository above — please open issues and pull
requests there, not here.
How to run
Always pass the full URL, not org/name — a… See the full description on the dataset page: https://huggingface.co/datasets/harborframework/terminal-bench-2.1.seedance-2-prompts-datasets
🎞️ Seedance-2-prompts-datasets
🎞️ The ultimate Seedance-2 video prompt dataset (50GB+). 8100+ video generation prompts with full metadata and preview frames. Truly open source: No login, no ads, no redirection. Just pure data for AI video creators.
This project is a massive collection of prompts used for Bytedance's Seedance 2.0 and the resulting generated videos. The entire dataset exceeds 50GB and contains 8100+ videos, all structured into a comprehensive dataset.
Due… See the full description on the dataset page: https://huggingface.co/datasets/GokuScraper/seedance-2-prompts-datasets.cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain… See the full description on the dataset page: https://huggingface.co/datasets/uoft-cs/cifar10.LLaVA-OneVision-2-Data
LLaVA-OneVision-2-Data
Training data for the LLaVA-OneVision-2 multimodal model family. The release contains large-scale video data at several duration ranges, video captions and source mappings, and spatial-reasoning data used for mid-training.
At a Glance
The dataset is split across two Hugging Face repositories because of its size:
Repository
What it contains
Part 1 (this repository)
~60-second video shards, captions for all duration ranges… See the full description on the dataset page: https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-2-Data.Leopard-Instruct
Leopard-Instruct
Paper | Github | Models-LLaVA | Models-Idefics2
Summaries
Leopard-Instruct is a large instruction-tuning dataset, comprising 925K instances, with 739K specifically designed for text-rich, multiimage scenarios. It's been used to train Leopard-LLaVA [checkpoint] and Leopard-Idefics2 [checkpoint].
Loading dataset
to load the dataset without automatically downloading and process the images (Please run the following codes with datasets==2.18.0)… See the full description on the dataset page: https://huggingface.co/datasets/wyu1/Leopard-Instruct.brand-assetsimage_dummy\IntuitivePhysics
WorldBench
WorldBench is a new benchmark designed to evaluate the physical understanding and prediction of modern world models and vision-language models. There are two components:
Video based: This is a benchmark designed to evaluate video-to-video world foundation models such as Cosmos. It consists of videos 132 frames long of 425 simulated scenes with RGB, Normals, Depth, Flow, and Segmentations.
Text based: This is a subset which adds text-based questions to 181 videos from… See the full description on the dataset page: https://huggingface.co/datasets/worldbenchmark/IntuitivePhysics.terminal-bench
Terminal-Bench
The primary source is hosted on GitHub, please open issues and
pull requests there, not here.
Terminal-Bench is now a continuous benchmark: new versions are released periodically as tags on the source repo
instead of one-off snapshots. This dataset mirrors that model on the Hub: instead of a separate
terminal-bench-X.Y repo per release, one repo, tagged per version. main always tracks the latest published
version; each release is additionally available as an… See the full description on the dataset page: https://huggingface.co/datasets/harborframework/terminal-bench.course-assetsOceanDepths
OceanDepths GeoTIFF Raster and Aligned ARGO Dataset
This dataset package contains the model-ready Ocean variables (ARGO submarine data, sea surface height, sea surface temperature and
salinity, as well as GLORYS reanalysis information for 50 depth levels. The ARGO data has been projected onto the GLORYS grid in order
to build a ML-ready dataset. The intention is that users can create tensors easily for CV-inspired ML approaches to ocean-variable
reconstruction. While… See the full description on the dataset page: https://huggingface.co/datasets/ESA-philab/OceanDepths.chengyu時間：
2018年做成網站 https://chengyu.18dao.net
2024年用AI將文本生成圖片
2025年上傳到Hugging Face的Datasets
数据集中的文件总数: 20609
目录 "Text-to-Image/" 下的文件数量: 10296，子目錄數：5148，每個子目錄兩個文件，一個原始的文生圖png圖片，一個圖片解釋txt文件
目录 "image-chengyu/" 下的文件数量: 5155，加字的圖片jpg文件
目录 "text-chengyu/" 下的文件数量: 5156，文字解釋txt文件
RT-PosePaper
RT-Pose: A 4D Radar Tensor-based 3D Human Pose Estimation and Localization Benchmark (ECCV 2024)
RT-Pose introduces a human pose estimation (HPE) dataset and benchmark by integrating a unique combination of calibrated radar ADC data, 4D radar tensors, stereo RGB images, and LiDAR point clouds.
This integration marks a significant advancement in studying human pose analysis through multi-modality datasets.
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/andaba/RT-Pose.EmbodiedGenDatahttps://huggingface.co/spaces/HorizonRobotics/EmbodiedGen-Gallery-Explorer
zidian时间线：
2018年搭建成网站 https://zidian.18dao.net
2024年使用AI技術為《國語字典》生成配圖。
2025年上傳到Hugging Face做成數據集。
数据集中的文件:
目录 "image/" 下的文件数量: 4307，文生圖原始png圖片
目录 "image-zidian/" 下的文件数量: 4307，加字後的jpg圖片
目录 "text-zidian/" 下的文件数量: 4307，圖片解釋文字
目录 "pinyin/" 下的文件数量: 1702，拼音mp3文件
witwaqfeya-library
Waqfeya Library
📖 Overview
Waqfeya is one of the primary online resources for Islamic books, similar to Shamela. It hosts more than 10,000 PDF books across over 80 categories.
In this dataset, we processed the original PDF files using Google Document AI APIs and extracted their contents into two additional formats: TXT and DOCX.
📊 Dataset Contents
The dataset includes 22,443 PDF files (spanning 8,978,634 pages) representing 10,150 Islamic books. Each book is… See the full description on the dataset page: https://huggingface.co/datasets/ieasybooks-org/waqfeya-library.MathNet
Quick Start · Overview · Tasks · Comparison · Dataset Stats · Data Sources · Pipeline · Schema · License · Citation
This is the official MathNet v0. A larger version v1 will be uploaded soon (more countires, problems and richer metadata). Schema is stable but field values may be revised in v1.
Quick start
from datasets import load_dataset
# Default: all problems
ds = load_dataset("ShadenA/MathNet", split="train")
# Or a specific country / competition-body config… See the full description on the dataset page: https://huggingface.co/datasets/ShadenA/MathNet.