datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
the_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.MDCOmniEdit-Filtered-1.2M
OmniEdit
In this paper, we present OMNI-EDIT, which is an omnipotent editor to handle seven different image editing tasks with any aspect ratio seamlessly. Our contribution is in four folds: (1) OMNI-EDIT is trained by utilizing the supervision
from seven different specialist models to ensure task coverage. (2) we utilize importance sampling based on the scores provided by large multimodal models (like GPT-4o) instead of CLIP-score to improve the data quality.
📃Paper | 🌐Website |… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/OmniEdit-Filtered-1.2M.typed_digital_signatures
Typed Digital Signatures Dataset
This comprehensive dataset contains synthetic digital signatures rendered across 30 different Google Fonts, specifically selected for their handwriting and signature-style characteristics. Each font contributes unique stylistic elements, making this dataset ideal for robust signature analysis and font recognition tasks.
Dataset Overview
Total Fonts: 30 different Google Fonts
Images per Font: 3,000 signatures
Total Dataset Size:… See the full description on the dataset page: https://huggingface.co/datasets/Benjy/typed_digital_signatures.imagefolder_with_metadatatasksThis dataset is for storing assets for https://huggingface.co/tasks and https://github.com/huggingface/huggingface.js/tree/main/packages/tasks
TABLET-Large
TABLET-Large
This is the Large sized train set of the TABLET dataset. It contains all train examples for all TABLET tasks, resulting in a total of 3,505,311 training examples across 17 tasks.This dataset is self-contained, each example includes a table image, its HTML representation, and the associated task data.However, if you're interested in downloading just the TABLET tables, check out TABLET-tables.
All TABLET Subsets:
(train) TABLET-Small: The smallest TABLET subset… See the full description on the dataset page: https://huggingface.co/datasets/alonsoapp/TABLET-Large.textvqa
Large-scale Multi-modality Models Evaluation Suite
Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval
🏠 Homepage | 📚 Documentation | 🤗 Huggingface Datasets
This Dataset
This is a formatted version of TextVQA. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.
@inproceedings{singh2019towards,
title={Towards vqa models that can read},
author={Singh, Amanpreet and… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/textvqa.documentation-imagestcga-wsi-uni2h-features
TCGA WSI UNI2H Features
Dataset Summary
This dataset provides tile-level UNI2-h embeddings extracted from TCGA whole-slide images (WSIs) using a reproducible, auditable pipeline designed for computational pathology research.
Data is organized by project (for example TCGA-HNSC) and currently exposes:
features/ containing H5 feature files with tile-level embeddings
vis/ containing overlay images for quality inspection and pipeline verification
[!IMPORTANT]
Unlike the… See the full description on the dataset page: https://huggingface.co/datasets/W8Yi/tcga-wsi-uni2h-features.ScienceQA
Dataset Card Creation Guide
Dataset Summary
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
Supported Tasks and Leaderboards
Multi-modal Multiple Choice
Languages
English
Dataset Structure
Data Instances
Explore more samples here.
{'image': Image,
'question': 'Which of these states is farthest north?',
'choices': ['West Virginia', 'Louisiana', 'Arizona', 'Oklahoma'],
'answer': 0… See the full description on the dataset page: https://huggingface.co/datasets/derek-thomas/ScienceQA.documentation-mediatiny-testCRA5-Dataset
Climate science data can be compressed efficiently by dual-stage extreme compression with a variational auto-encoder transformer
Introduction and get started
CRA5 dataset now is available at OneDrive
Paper Summary
We introduce VAEformer, a variational autoencoder transformer designed for the extreme compression of climate data. Addressing the storage challenges of massive datasets like ERA5, VAEformer utilizes a… See the full description on the dataset page: https://huggingface.co/datasets/taohan10200/CRA5-Dataset.server
2026-05-20 Non-distance Refresh Bundle
This bundle contains refreshed paper-facing outputs copied from the server-side
TabQueryBench/code_snapshot/Evaluation/... tree after the v2 refresh runs.
Included:
subgroup_breakdown/final
conditional_breakdown/final
conditional_locality_support_final
missingness_breakdown/final
missingness_regime_diagnostic
tail_breakdown/final
tail_support_diagnostics_final
tail_threshold_final
compare_updated_figures.pdf
compare_updated_figures.tex… See the full description on the dataset page: https://huggingface.co/datasets/TabQueryBench2026/server.WSI_Embedding
WSI_Embedding
Patch and slide embeddings for whole-slide images, plus the run records used to produce them.
Original WSIs are not in this repo. They stay on HPC / the source dataset remotes. Do not expect .svs / .tif here.
Repo: thanminh01/WSI_Embedding
Top-level layout
Path
What it is
Download when
embeddings/<dataset>/<model>/<mag>x_<patch>px_<overlap>px_overlap/
Encoder tensors (.h5 / .pt / WSI-LLaVA json) and per-model TRIDENT _config_ / _logs_
You… See the full description on the dataset page: https://huggingface.co/datasets/thanminh01/WSI_Embedding.SteamScreenshots-Bugs
Samples
trashpair_touch_13m
PairTouch 13M Dataset
Multi-modal tactile dataset with pose, force, and tactile sensor data.
Configs
Config
Description
Sensors
pose_data
Pose estimation data
tac02/xela + camera
force_data
Force measurement data
tac02/xela + gelsight
tacniq_gsmini
TacNIQ + GSMini data
tacniq + gsmini
xela_9dtact
XELA + 9DTact data
xela + 9dtact
Usage
from datasets import load_dataset
# Load specific config
ds =… See the full description on the dataset page: https://huggingface.co/datasets/BorisGuo/pair_touch_13m.hle_text_only
Humanity's Last Exam - (Text only)
🌐 Website | 📄 Paper | GitHub
Center for AI Safety & Scale AI
Humanity's Last Exam (HLE) is a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. Humanity's Last Exam consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and… See the full description on the dataset page: https://huggingface.co/datasets/macabdul9/hle_text_only.UrbanVerse-Training-Scenes
UrbanVerse Training Scenes (Urban Cousins)
A collection of ready-to-simulate urban 3D scenes in OpenUSD
for NVIDIA Isaac Sim / Isaac Lab, released by the
VAIL-UCLA lab. Each scene is a self-contained
USD stage with all of its materials and textures, so it can be opened and
simulated directly.
The scenes are generated with UrbanVerse — Scaling Urban Simulation by
Watching City-Tour Videos (Liu et al., ICLR 2026,
arXiv:2510.15018,
project page) — whose UrbanVerse-Gen
pipeline… See the full description on the dataset page: https://huggingface.co/datasets/UCLA-VAIL/UrbanVerse-Training-Scenes.fixtures_ade20kturkey-all-universitiesCertainly! Here’s the dataset description in Markdown format:
All Universities in Turkey Dataset
Description
This dataset contains detailed information about various universities. Each record represents a single university and includes attributes such as the university's name, type, city, website, address, logo URL, and a button for accessing additional details. This data is typically extracted from a web page listing universities.
Fields
1. id… See the full description on the dataset page: https://huggingface.co/datasets/h8st6ptv/turkey-all-universities.terminal-bench-2
Terminal-Bench-2.0 Beta
Welcome to Terminal-Bench-2.0! If you’re reading this you’re a member of the Terminal-Bench community that we’ve selected to get a sneak peek at the latest version of the benchmark.
Getting Started
First, clone Harbor (formerly “Sandboxes”):
git clone https://github.com/laude-institute/harbor.git
From inside the Harbor directory run:
uv sync
This will install Harbor, our new package for running agent evals.
You should now be able to run TB 2.0!… See the full description on the dataset page: https://huggingface.co/datasets/penfever/terminal-bench-2.tiny-imagenet
Dataset Card for tiny-imagenet
Dataset Summary
Tiny ImageNet contains 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images, and 50 test images.
Languages
The class labels in the dataset are in English.
Dataset Structure
Data Instances
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64 at 0x1A800E8E190,
'label': 15
}… See the full description on the dataset page: https://huggingface.co/datasets/zh-plus/tiny-imagenet.fine-t2i
Fine-T2I: An Open, Large-Scale, and Diverse Dataset for High-Quality T2I Fine-Tuning [arxiv]
by Xu Ma, Yitian Zhang,
Qihua Dong, Yun Fu
Northeastern Univeristy
Please see our [Dataset Explore] to view detailed samples (loading is slow, be patient).
🆕 What's New
[2026.02.20]: Fine-T2I reaches the #1 spot among Hugging Face Datasets Trending list ⭐️⭐️⭐️
[2026.02.16]: Fine-T2I tops the Hugging Face Datasets Trending list, reaching the #2 spot and #1… See the full description on the dataset page: https://huggingface.co/datasets/ma-xu/fine-t2i.tokenizers-benchCauldron-JA
Dataset Card for The Cauldron-JA
Dataset description
The Cauldron-JA is a Vision Language Model dataset that translates 'The Cauldron' into Japanese using the DeepL API. The Cauldron 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.
To create a Japanese Vision Language Dataset, datasets related to OCR, coding, and graphs were excluded because translating them into Japanese… See the full description on the dataset page: https://huggingface.co/datasets/turing-motors/Cauldron-JA.TEDWB10k-preview
TEDWB10k — Preview
This is a preview/browsing repo. The full tracked dataset is at
initialneil/TEDWB10k
(gated, requires EULA acceptance).
This repo contains:
Per-subject thumbnails (metadata/previews/<id>.jpg) — 1024×1024 first source frame
Tracking QC grids (metadata/{ehm,flame,base}/<id>.jpg) — full-res overlay visualizations
Parquet tables with embedded previews for the HF Dataset Viewer
Stats
10077 train / 1119 test subjects
License: CC-BY-NC-ND 4.0 (TED… See the full description on the dataset page: https://huggingface.co/datasets/initialneil/TEDWB10k-preview.stanford_cars
Stanford Cars Dataset
Dataset Overview
Splits:
Training: 8144 images used for model training.
Test: 8041 images used for evaluation.
Contrast: 8041 images with high contrast for robustness testing.
Gaussian Noise: 8041 images corrupted by Gaussian noise for robustness testing.
Impulse Noise: 8041 images corrupted by impulse noise for robustness testing.
JPEG Compression: 8041 compressed images for robustness testing.
Motion Blur: 8041 images with motion blur for… See the full description on the dataset page: https://huggingface.co/datasets/tanganke/stanford_cars.