ali-vilab/TeaCache

★ 1,380⑂ 60

Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model

About ali-vilab/TeaCache

ali-vilab/TeaCache is an open-source project on GitHub, mainly written in Python. Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model It currently holds 1,380 stars and 60 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).

Project Overview

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GitHub Repository Details

Repository ali-vilab/TeaCache · default branch - · size 0 KB · watchers 0 · source: GitHub REST API and repository README

README

[CVPR 2025 Highlight] Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model

Feng Liu1* Shiwei Zhang2 Xiaofeng Wang1,3 Yujie Wei4 Haonan Qiu5
Yuzhong Zhao1 Yingya Zhang2 Qixiang Ye1 Fang Wan1
1University of Chinese Academy of Sciences,  2Alibaba Group
3Institute of Automation, Chinese Academy of Sciences
4Fudan University,  5Nanyang Technological University
(* Work was done during internship at Alibaba Group. † Project Leader. ‡ CorresCorresponding author.)

hf_paper arXiv Home Page License github

visualization

🫖 Introduction

We introduce Timestep Embedding Aware Cache (TeaCache), a training-free caching approach that estimates and leverages the fluctuating differences among model outputs across timesteps, thereby accelerating the inference. TeaCache works well for Video Diffusion Models, Image Diffusion models and Audio Diffusion Models. For more details and results, please visit our project page.

🔥 Latest News

🧩 Community Contributions

If you develop/use TeaCache in your projects and you would like more people to see it, please inform us.(liufeng20@mails.ucas.ac.cn)

Model

ComfyUI

Parallelism

Engine

🎉 Supported Models

Text to Video Image to Video Text to Image Text to Audio

🤖 Instructions for Supporting Other Models

💐 Acknowledgement

This repository is built based on VideoSys, Diffusers, Open-Sora, Open-Sora-Plan, Latte, CogVideoX, HunyuanVideo, ConsisID, FLUX, Mochi, LTX-Video, Lumina-T2X, TangoFlux, Cosmos, Wan2.1, HiDream-I1 and Lumina-Image-2.0. Thanks for their contributions!

🔒 License

📖 Citation

If you find TeaCache is useful in your research or applications, please consider giving us a star ⭐ and citing it by the following BibTeX entry.
@article{liu2024timestep,
  title={Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model},
  author={Liu, Feng and Zhang, Shiwei and Wang, Xiaofeng and Wei, Yujie and Qiu, Haonan and Zhao, Yuzhong and Zhang, Yingya and Ye, Qixiang and Wan, Fang},
  journal={arXiv preprint arXiv:2411.19108},
  year={2024}
}

GitHub Stars & Activity

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GitHub stars1,380
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