Instructions to use FastVideo/Waypoint-1-Small-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FastVideo/Waypoint-1-Small-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/Waypoint-1-Small-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
Download vae/diffusion_pytorch_model.safetensors from FastVideo/Waypoint-1-Small-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 142 MB
-
https://huggingface.co/FastVideo/Waypoint-1-Small-Diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://FastVideo/Waypoint-1-Small-Diffusers/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/FastVideo/Waypoint-1-Small-Diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
142 MB
- Xet hash:
- 033055bf46f30a1d25ac634d5cc225d34da5dab5a23a33ee8f2059eb8ee9beab
- Size of remote file:
- 142 MB
- SHA256:
- ecdebf692a6b02610163948251dcf264c5793da12b3729986fb4a3e3c4dc4d1f
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