datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
vitaminc
Details
Fact Verification dataset created for Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence (Schuster et al., NAACL 21`) based on Wikipedia edits (revisions).
For more details see: https://github.com/TalSchuster/VitaminC
When using this dataset, please cite the paper:
BibTeX entry and citation info
@inproceedings{schuster-etal-2021-get,
title = "Get Your Vitamin {C}! Robust Fact Verification with Contrastive Evidence",
author =… See the full description on the dataset page: https://huggingface.co/datasets/tals/vitaminc.Llama-VITS_data
Dataset Card for Llama-VITS_data
The dataset repository contains data related with our work "Llama-VITS: Enhancing TTS Synthesis with Semantic Awareness", encapsulating:
Filtered dataset EmoV_DB_bea_sem
Filelists with semantic embeddings
Model checkpoints
Human evaluation templates
Dataset Details
Paper: Llama-VITS: Enhancing TTS Synthesis with Semantic Awareness
Curated by: Xincan Feng, Akifumi Yoshimoto
Funded by: CyberAgent Inc
Repository:… See the full description on the dataset page: https://huggingface.co/datasets/xincan/Llama-VITS_data.ViT-FineTunevitra-ego4d-videoViTTiny1022
ViTTiny1022
The dataset for Scaling Up Parameter Generation: A Recurrent Diffusion Approach.
Requirement
Install torch and other dependencies
conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia
pip install timm einops seaborn openpyxl
Usage
Test one checkpoint
cd ViTTiny1022
python test.py ./chechpoint_test/0000_acc0.9613_class0314_condition_cifar10_vittiny.pth
# python test.py… See the full description on the dataset page: https://huggingface.co/datasets/MTDoven/ViTTiny1022.features-dinov3-vith16plus-224-imagenet-22k-wdsVITRA-1M
VITRA-1M: Human Hand V-L-A Dataset
Dataset Summary
VITRA-1M is a large-scale Human Hand Visual-Language-Action (V-L-A) dataset constructed as described in the paper Scalable Vision-Language-Action Model Pretraining for Robotic Manipulation with Real-Life Human Activity Videos. It contains 1.2 million short episodes with segmented language annotations, camera parameters (corrected intrinsics/extrinsics), and 3D hand reconstructions (left and right… See the full description on the dataset page: https://huggingface.co/datasets/VITRA-VLA/VITRA-1M.VITRA-TeleData
VITRA Teleoperation Dataset
Dataset Summary
This dataset contains real-world robot teleoperation demonstrations collected
using a 7-DoF robotic arm equipped with a dexterous hand and a head-mounted RGB
camera. Each episode provides synchronized numerical state/action data
and video recordings. The dataset is used for finetuning in the project VITRA: Scalable Vision-Language-Action Model Pretraining for Robotic Manipulation with Real-Life Human Activity Videos
Project… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/VITRA-TeleData.behavior-1k-2025-challenge-vjepa2-vitg-demo-embeddings
V-JEPA 2 ViT-G Embeddings — BEHAVIOR-1K 2025 Challenge Demos (62h)
Precomputed video embeddings for a 62-hour subsample of the
BEHAVIOR-1K 2025 challenge demonstrations,
extracted with the V-JEPA 2 ViT-g encoder.
The goal is to make downstream experimentation faster and more reproducible by eliminating
repeated video decoding and encoder forward passes — lowering the barrier for teams
without access to large GPU clusters.
Field
Value
Source dataset… See the full description on the dataset page: https://huggingface.co/datasets/quastAI/behavior-1k-2025-challenge-vjepa2-vitg-demo-embeddings.vitac500vitco
ViTco
165,847,195 Vietnamese documents from 4 public corpora, 370.2 GB of Parquet, one schema
This dataset is the pinned public Vietnamese corpora as gao read them, every source put to one contract and one schema, before any cleaning.
Contents
What is it
What is in it
Where the text came from
How it is laid out
Reading it
What you can build with it
One row
The columns
What this repo is
What ships and what does not
Things to know before you use it
What this is… See the full description on the dataset page: https://huggingface.co/datasets/open-index/vitco.stanford_mask_vit_rawoakink2-vitra-streaming-v1
OakInk2 → VITRA Stage-1 (complete audited release)
This repository contains all 627 physical OakInk2-TaMF sequences converted to
VITRA Stage-1. Every sequence source pair is pinned to
kelvin34501/OakInk-v2 revision 21705616140d726607027e70d58b7837f442ffd8, aligned by exact
frame identity, converted across the four calibrated views, checked by geometry
and every-frame RGB audits, smoke-tested through the VITRA loader, uploaded,
and verified at an immutable commit before local… See the full description on the dataset page: https://huggingface.co/datasets/MIT-Media-Lab/oakink2-vitra-streaming-v1.CLIP-ViT-H-14-laion2B-s32B-b79K-all-checkpointsThis repository contains the intermediate checkpoints for the model https://huggingface.co/laion/CLIP-ViT-H-14-laion2B-s32B-b79K.
Each "epoch" corresponds to an additional (32B / 256) samples seen, consituting total of 256 "epochs"
The purpose of releasing these checkpoints and optimizer states is to enable analysis.
For the first 121 "epochs", training was done with float16 mixed precision before switching to bfloat16 after a loss blow up.
VITON-HD-TESTvitra-dinotxt-featuresfood101-vit-processedViTeX-Dataset
ViTeX-Dataset
📄 Paper ·
🌐 Project page ·
📊 Dataset ·
🧪 Code ·
🤖 Model weights ·
🏆 Leaderboard
Paired real-video dataset for video scene text editing: given a source video, a binary text-region mask, and a (source string → target string) pair, replace only the masked scene text across all frames while preserving the rest of the scene.
Accepted to NeurIPS 2026 E&D Track.
Authors: Xinghao Chen, Xiangbo Gao, Jiongze… See the full description on the dataset page: https://huggingface.co/datasets/ViTeX-Bench/ViTeX-Dataset.v2x_vitenergy-consumption-hourly-spainvitco-clean
ViTco Clean
2,279,914 Vietnamese documents from 2 public corpora, 10.6 GB of Parquet, one schema
This dataset is the same corpora after the cleaning line: normalized, measured, filtered to Vietnamese prose, deduplicated on identity, and with the personal identifiers covered.
Contents
What is it
What is in it
Where the text came from
How it is laid out
Reading it
What you can build with it
One row
The columns
What this repo is
What ships and what does not
Things… See the full description on the dataset page: https://huggingface.co/datasets/open-index/vitco-clean.VITS2_DatasetsVITON-HD-edit
VITON-HD-edit
This repository contains the VITON-HD-edit dataset presented in the paper CtrlVTON: Controllable Virtual Try-On via Visual-Instance-Prompt Segmentation.
Github Repository | Paper (arXiv)
Dataset Overview
The VITON-HD-edit dataset is a public benchmark built to support three evaluations:
Image-editing Virtual Try-On (VTO)
Instance-level visual-prompt segmentation
Spatial controllability
Training the editing model requires triplets $(p… See the full description on the dataset page: https://huggingface.co/datasets/NXN-Labs/VITON-HD-edit.viciebski-pralietaryj-yiddish
Viciebski Pralietaryj — Yiddish blocks
Blocks of newspaper text set in Yiddish (Hebrew script), cut from scans of
Viciebski pralietaryj («Віцебскі пралетарый»), a newspaper published in
Vitebsk, Byelorussian SSR (Belarus), in 1930, 1931 and 1933.
2684 images from 78 pages across 78 issues. No transcriptions —
this is a raw corpus for OCR/HTR work, not a labelled set.
Belarusian blocks are present. The Yiddish pages ran as inserts inside a
Belarusian newspaper, and blocks were… See the full description on the dataset page: https://huggingface.co/datasets/VItaldob/viciebski-pralietaryj-yiddish.wolt-food-clip-ViT-B-32-embeddings
wolt-food-clip-ViT-B-32-embeddings
Qdrant's Food Discovery demo relies on the dataset of food images from the Wolt
app. Each point in the collection represents a dish with a single image. The image is represented as a vector of 512
float numbers.
Generation process
The embeddings generated with clip-ViT-B-32 model have been generated using the following code snippet:
from PIL import Image
from sentence_transformers import SentenceTransformer
image_path =… See the full description on the dataset page: https://huggingface.co/datasets/Qdrant/wolt-food-clip-ViT-B-32-embeddings.VitaBench
🌱VitaBench: Benchmarking LLM Agents
with Versatile Interactive Tasks
📃 Paper • 🌐 Website • 🏆 Leaderboard • 🛠️ Code • 🤗 Dataset
🔔 News
[2026-01] Qwen3-Max-Thinking reported our Vita-Bench to evaluate and demonstrate its tool use capabilities (the averge score of 4 domains)！We invite the community to adopt Vita-Bench as the definitive touchstone for tool use performance assessment, and we appreciate diverse utilization & interpretation of our benchmark… See the full description on the dataset page: https://huggingface.co/datasets/meituan-longcat/VitaBench.vite-selfbench
Vite Selfbench
Vite Selfbench is a 27-task software-engineering benchmark for coding agents, packaged for the Harbor evaluation framework. Each task asks an agent to implement a change in a frozen revision of vitejs/vite, then checks the resulting patch with task-specific tests. Harbor provides isolated task environments and runs verification separately from the agent.
This repository contains the raw evaluation only. It does not include model outputs, scores, costs, or… See the full description on the dataset page: https://huggingface.co/datasets/dari-ai/vite-selfbench.sketch-graph-vitruvion
pretty_name: SketchGraphs, Vitruvion selection (rebuilt)
license: other
license_name: onshape-terms-of-use
license_link: https://www.onshape.com/legal/terms-of-use#your_content
size_categories:
- 1M<n<10M
tags:
- cad
- parametric-cad
- sketches
- geometric-constraints
- sketchgraphs
- vitruvion
SketchGraphs, Vitruvion selection (sg_filtered_unique.npy, rebuilt)
This is the dataset of Vitruvion (Seff et al., Vitruvion: A Generative Model of… See the full description on the dataset page: https://huggingface.co/datasets/benikm91/sketch-graph-vitruvion.AudioQA-1Msvi-benchmark
Stable Video Infinity (SVI) Benchmark Dataset
This benchmark dataset is introduced in the paper:
Stable Video Infinity: Infinite-Length Video Generation with Error Recycling
by Wuyang Li, Wentao Pan, Po-Chien Luan, Yang Gao, Alexandre Alahi (2025).
Project page: https://stable-video-infinity.github.io/homepage/
Code: https://github.com/vita-epfl/Stable-Video-Infinity
Abstract
We propose Stable Video Infinity (SVI) that is able to generate infinite-length videos with… See the full description on the dataset page: https://huggingface.co/datasets/epfl-vita/svi-benchmark.