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@ -46,6 +46,7 @@ If your work has improved **Wan2.1** and you would like more people to see it, p
- [CFG-Zero](https://github.com/WeichenFan/CFG-Zero-star) enhances **Wan2.1** (covering both T2V and I2V models) from the perspective of CFG.
- [TeaCache](https://github.com/ali-vilab/TeaCache) now supports **Wan2.1** acceleration, capable of increasing speed by approximately 2x. Feel free to give it a try!
- [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) provides more support for **Wan2.1**, including video-to-video, FP8 quantization, VRAM optimization, LoRA training, and more. Please refer to [their examples](https://github.com/modelscope/DiffSynth-Studio/tree/main/examples/wanvideo).
- EasyCache (Training-Free Video Diffusion Acceleration via Runtime-Adaptive Caching): [EasyCache](https://github.com/H-EmbodVis/EasyCache) by [Dingkang Liang](https://github.com/dk-liang) and [Xin Zhou](https://github.com/LMD0311)
## 📑 Todo List