Instructions to use xiaobinzhuang/videofoley with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xiaobinzhuang/videofoley with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xiaobinzhuang/videofoley", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from xiaobinzhuang/videofoley: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/xiaobinzhuang/videofoley/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://xiaobinzhuang/videofoley/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/xiaobinzhuang/videofoley/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- fb281793c5dfeab25387186a09681902928cb2808a1ecd9a5f9320cfadf88407
- Size of remote file:
- 335 MB
- SHA256:
- 9150709b493d7ee1be671736aeafdd2b53b39766a4acfc14071519d70c52ca0a
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