Instructions to use Viggle/Viggle-Animate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Viggle/Viggle-Animate with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Viggle/Viggle-Animate", 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:
- cdaad34d2768bfb829bae3f1be7dd58e217ef652406b7302739d0eefcf9dca28
- Size of remote file:
- 541 kB
- SHA256:
- 5a01824f3023f305bb04b054b236c498030c2e9a3b76e1a3ccacdddea19f49cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.