Top AI Repos โ open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
๐ Collection of awesome generation acceleration resources.
| Date | Stars |
|---|---|
| 2026-07-24 | 402 |
| 2026-07-25 | 402 |
| 2026-07-28 | 402 |
| 2026-07-30 | 402 |
| 2026-08-06 | 402 |
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<div align=center> # ๐จ Awesome Generation Acceleration ๐ <p> [](https://github.com/sindresorhus/awesome)  [](https://github.com/Naereen/StrapDown.js/graphs/commit-activity) [](https://github.com/xuyang-liu16/Awesome-Diffusion-Acceleration) [](https://github.com/xuyang-liu16/Awesome-Generation-Acceleration.git) ๐๐ If you would like to contribute to this repository, feel free to email me at `[email protected]`! ๐๐ </p> </div> ## ๐ฅ <span id="head1"> *News* </span> * **`2025/02/22`** ๐ฅ๐ฅ Our work [ToCa](https://arxiv.org/abs/2410.05317) has been accepted by **ICLR 2025**! Congratulations to all collaborators! * **`2024/12/24`** ๐ค๐ค We release an open-sourse repo "[Awesome-Token-level-Model-Compression](https://github.com/xuyang-liu16/Awesome-Token-level-Model-Compression)", which collects recent awesome token reduction papers! Feel free to contribute your suggestions! * **`2024/10/12`** ๐๐ We release our work [ToCa](https://arxiv.org/abs/2410.05317) about accelerating DiT models for FREE, which achieves nearly lossless acceleration of **1.51ร** on FLUX, **1.93ร** on PixArt-ฮฑ, and **2.36ร** on OpenSora! [Code](https://github.com/Shenyi-Z/ToCa) is now available! * **`2024/07/15`** ๐ค๐ค We release an open-sourse repo "[Awesome-Generation-Acceleration](https://github.com/xuyang-liu16/Awesome-Generation-Acceleration)", which collects recent awesome generation accleration papers! Feel free to contribute your suggestions! ## ๐ <span id="head1"> *Contents* </span> - [Awesome Generation Acceleration](README.md) - [Fast Sampling](#fast-sampling) - [Pruning](#pruning) - [Quantization](#quantization) - [Distillation](#distillation) - [Cache Mechanism](#cache-mechanism) - [Efficient Attention](#efficient-attention) - [Dynamic Neural Networks](#dynamic-neural-networks) - [Deployment Optimization](#deployment-optimization) - [Training-free Generation Acceleration](TRAIN-FREE.md) - [Stable Diffusion](TRAIN-FREE.md#Training-free-Stable-Diffusion-Acceleration) - [Diffusion Transformer](TRAIN-FREE.md#Training-free-Diffusion-Transformer-Acceleration) - [Auto-Regressive Generation](TRAIN-FREE.md#Training-free-Auto-Regressive-Generation-Acceleration) - [Token-wise Generation Acceleration](TOKEN-WISE.md) - [Image Generation](TOKEN-WISE.md#image-generation) - [Video Generation](TOKEN-WISE.md#video-generation) ## ๐ฌ <span id="head1"> *Keywords* </span>    ## ๐ <span id="head1"> *Papers* </span> ### Fast Sampling - **[1] Denoising Diffusion Implicit Models**, ICLR 2021. *Song, Jiaming and Meng, Chenlin and Ermon, Stefano.* [[Paper](https://arxiv.org/abs/2010.02502)] [[Code](https://github.com/ermongroup/ddim)]    - **[2] DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps**, NeurIPS 2022. *Lu, Cheng and Zhou, Yuhao and Bao, Fan and Chen, Jianfei and Li, Chongxuan and Zhu, Jun.* [[Paper](https://arxiv.org/abs/2206.00927)] [[Code](https://github.com/LuChengTHU/dpm-solver)]    ![](https://img.shields.io/badge/Sampling_So
Excerpt of 49,577 characters
Read on GitHubWould you bet a product on this? Bounded 0โ100 and slow moving.
matched fp:91d0a87d3e13d119, topic:diffusion-models, topic:image-generation, topic:text-to-image
matched fp:91d0a87d3e13d119, topic:video-generation, topic:text-to-video, readme:video generation