Instructions to use FastVideo/FastMochi-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FastVideo/FastMochi-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FastVideo/FastMochi-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- f7b18b9e6d3f952fc78ee90b370e7cf5b1b2ad0f7030c7fc38607263951e005a
- Size of remote file:
- 5.4 MB
- SHA256:
- d197f16d38bfe9acd99463e510137215c8891e02824a7792e2ed8dc110ea694d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.