datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Vchitect_T2V_DataVerse
Vchitect-T2V-Dataverse
Vchitect Team1
1Shanghai Artificial Intelligence Laboratory
Paper |
Project Page |
Data Overview
The Vchitect-T2V-Dataverse is the core dataset used to train our text-to-video diffusion model, Vchitect-2.0: Parallel Transformer for Scaling Up Video Diffusion Models.
It comprises 14 million high-quality videos collected from the Internet, each paired with detailed textual… See the full description on the dataset page: https://huggingface.co/datasets/Vchitect/Vchitect_T2V_DataVerse.vbvr-latent-cache-832x832x33f-t2v-only
VBVR Latent Cache (832×832 × 33f, Wan2.2-TI2V-5B VAE + UMT5-XXL)
Pre-encoded latent cache for the
Video-Reason/VBVR-Dataset
geometric / logical reasoning video corpus, prepared for Equilibrium Matching
(EqM) post-training of Wan-AI/Wan2.2-TI2V-5B-Diffusers on AWS Trainium2.
This is a working cache, not a primary dataset. It exists to skip the
~5 s/sample VAE+T5 encode cost during training. The original videos +
prompts live in the upstream VBVR-Dataset repo.
Source →… See the full description on the dataset page: https://huggingface.co/datasets/Central-Cat/vbvr-latent-cache-832x832x33f-t2v-only.Wan2.1-T2V-1.3B_vidprom_81x480x832_40step_5cfg_5.0shift_4tEvalCrafter_T2V_Dataset
EvalCrafter Text-to-Video (ECTV) Dataset 🎥📊
Code · Project Page · Huggingface Leaderboard · Paper@ArXiv · Prompt list
Welcome to the ECTV dataset! This repository contains around 10000 videos generated by various methods using the Prompt list. These videos have been evaluated using the innovative EvalCrafter framework, which assesses generative models across visual, content, and motion qualities using 17 objective metrics and subjective user opinions.
Dataset Details 📚… See the full description on the dataset page: https://huggingface.co/datasets/RaphaelLiu/EvalCrafter_T2V_Dataset.Vchitect_T2V_DataVerse_256p_8fps_wdshttps://huggingface.co/datasets/Vchitect/Vchitect_T2V_DataVerse resampled to 256p. Intended for training https://github.com/NilanEkanayake/TiTok-Video
Wan2.2-T2V-Activations-FP4wan_t2v_distillation_datasetViBeThis repository contains the data presented in ViBe: A Text-to-Video Benchmark for Evaluating Hallucination in Large Multimodal Models.
ViBe Annotations and Category Labels
Order of Model Annotations
The annotations for the models in metadata.csv are organized in the following order:
animatelcm
zeroscopeV2_XL
show1
mora
animatelightning
animatemotionadapter
magictime
zeroscopeV2_576w
ms1.7b
hotshotxl
Step-Video-T2V-EvalThis dataset contains the data of the paper Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model.
Code: https://github.com/stepfun-ai/Step-Video-T2V
Project page: https://yuewen.cn/videos
t2v-sampled-videoscrush-smol_processed_t2vt2v-distill-benchmark
T2V Distillation Benchmark
A benchmark comparison of Text-to-Video distillation/acceleration models based on Wan2.1-14B.
Models Compared
Model
Steps
Source
FastVideo CausalWan2.2
8
FastVideo/CausalWan2.2-I2V-A14B-Preview-Diffusers
Krea Realtime-Video
4
krea/krea-realtime-video
LightX2V CausVid
9
lightx2v/Wan2.1-T2V-14B-CausVid
NVlabs rCM 14B
4
worstcoder/rcm-Wan
Helios-Distilled
3 (pyramid 2-2-2)
BestWishYsh/Helios-Distilled… See the full description on the dataset page: https://huggingface.co/datasets/hffordata/t2v-distill-benchmark.FLARE-1k-Unified-T2VAChinaOpen1k-T2V
ChinaOpen-1k T2V retrieval
Multilingual video retrieval built from
ChinaOpen-1k:
1,092 Bilibili videos with human-written Chinese captions and their
English translations. Both language configs share the same videos, so
the two subsets form a controlled comparison.
Built by scripts/data/chinaopen_retrieval/create_data.py in
mteb.
Please cite the original dataset:
@inproceedings{chen2023chinaopen,
title = {ChinaOpen: A Dataset for Open-world Multimodal Learning},
author =… See the full description on the dataset page: https://huggingface.co/datasets/shriyasudhakar/ChinaOpen1k-T2V.FLARE-1k-Audio-T2VAvbench-wan22-t2v-dense93-xpu
VBench dense93 — Wan2.2 T2V videos (Intel XPU / vLLM-Omni)
93 text-to-video generations for the VBench "dense93" prompt set, produced
with Wan2.2-T2V-A14B (Diffusers) served by vLLM-Omni on Intel XPU
(oneAPI, 720x1280 @ 16fps, 81 frames, 40 denoise steps, guidance 4.0/3.0,
boundary 0.875, flow shift 5.0, seed 42, MXFP8 linear + cache-dit +
Sage V3 hybrid attention with SDPA fallback on blocks 33,34,38,39).
One video per prompt; file name = <prompt>-0.mp4
(prompt list:… See the full description on the dataset page: https://huggingface.co/datasets/Yi30/vbench-wan22-t2v-dense93-xpu.Wan2.2-T2V-Activations-INT4T2V-CompBench-VideosWan_2.2_T2V_10steps_GGUFcinepile-t2v-split_scenes_single_shot_uniform
Important Columns for Captioning
Caption_t2v_style: Expressive and long caption generated by Gemini Flash 2.5 for the extracted shot.
Caption_t2v_style_short: Short caption generated by Gemini Flash 2.5 for the extracted shot.
Avg-Aesthetic-Score-Laion-Aesthetics: Average (over frames) aesthetic score of the extracted shot from Laion Aesthetics.
Frame-Aesthetic-Scores-Laion-Aesthetics: Aesthetic scores of each frame of the extracted shot from Laion Aesthetics.… See the full description on the dataset page: https://huggingface.co/datasets/CinematicT2vData/cinepile-t2v-split_scenes_single_shot_uniform.Wan_2.2_T2V_10stepst2v_data_v2
DenseDPO T2V Broad-Pair Dataset (v2)
Cross-model text-to-video (T2V) generation pairs for training video reward
models (RM) and DPO-style preference learning.
The HF Dataset Viewer renders each row as prompt + two videos side-by-side.
Generation task
All videos are generated T2V from a shared text prompt. For every pair,
both videos share the same prompt, so the primary comparison axis is the model
identity itself.
Plan-A tier structure
Models are grouped into… See the full description on the dataset page: https://huggingface.co/datasets/qgfvadfuvads/t2v_data_v2.FLARE-1k-Audio-T2VAWan21_CausVid_14B_T2V_lora_rank32.safetensorsazm-archive-20260909-t2v-needlabel-videos
t2v_data_needlabel_videos.tar
Backup of an existing dataset archive, preserving its original bytes.
File: t2v_data_needlabel_videos.tar
Size: 4,675,983,360 bytes
SHA256: 8672488cef23b55e2a70d3279327a38ddbbd8e2809661600d7c707d59b9e1e18
Verify the downloaded archive with sha256sum -c SHA256SUMS.
FLARE-1k-Unified-T2VAT2VFLARE-1k-Vision-T2Vmixkit-t2vInfo_Wan_Video_2.2_T2V-A14B
Model Index by Creator
423748 Page
Model
Base Model
Full Model Page
Archive Link
wan2.2,t2v,low,zzzyixuan.
Wan Video 2.2 T2V-A14B
View
View
Version Links
Model
Version
Base Model
Version Link
wan2.2,t2v,low,zzzyixuan.
v1.0
Wan Video 2.2 T2V-A14B
View
Aaron_PP Page
Model
Base Model
Full Model Page
Archive Link
NSFW WAN 2.2 T2V Bunny girl, red patent leather tights, black high stockings, red high heels
Wan Video 2.2… See the full description on the dataset page: https://huggingface.co/datasets/ApacheOne/Info_Wan_Video_2.2_T2V-A14B.