Hugging Face's logo

vidfom
/
Wan-T2V_14B

Diffusers
Safetensors
Model card Files
xet
 Community
1
Wan-T2V_14B / DiffSynth-Studio /examples /TeaCache /README.md
vidfom's picture
vidfom
Upload folder using huggingface_hub
9c63087 verified
preview code
|
Raw History Blame Contribute Delete
1.19 kB
# TeaCache
TeaCache ([Timestep Embedding Aware Cache](https://github.com/ali-vilab/TeaCache)) is a training-free caching approach that estimates and leverages the fluctuating differences among model outputs across timesteps, thereby accelerating the inference.
## Examples
### FLUX
Script: [./flux_teacache.py](./flux_teacache.py)
Model: FLUX.1-dev
Steps: 50
GPU: A100
|TeaCache is disabled|tea_cache_l1_thresh=0.2|tea_cache_l1_thresh=0.8|
|-|-|-|
|23s|13s|5s|
|![image_None](https://github.com/user-attachments/assets/2bf5187a-9693-44d3-9ebb-6c33cd15443f)|![image_0 2](https://github.com/user-attachments/assets/5532ba94-c7e2-446e-a9ba-1c68c0f63350)|![image_0 8](https://github.com/user-attachments/assets/d8cfdd74-8b45-4048-b1b7-ce480aa23fa1)
### Hunyuan Video
Script: [./hunyuanvideo_teacache.py](./hunyuanvideo_teacache.py)
Model: Hunyuan Video
Steps: 30
GPU: A100
The following video was generated using TeaCache. It is nearly identical to [the video without TeaCache enabled](https://github.com/user-attachments/assets/48dd24bb-0cc6-40d2-88c3-10feed3267e9), but with double the speed.
https://github.com/user-attachments/assets/cd9801c5-88ce-4efc-b055-2c7737166f34