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 video_encoder/diffusion_pytorch_model.bin from xiaobinzhuang/videofoley: direct link, hf CLI and curl.
- Browser
- Download file 131 MB
-
https://huggingface.co/xiaobinzhuang/videofoley/resolve/main/video_encoder/diffusion_pytorch_model.bin
- Command line
-
hf download hf://xiaobinzhuang/videofoley/video_encoder/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/xiaobinzhuang/videofoley/resolve/main/video_encoder/diffusion_pytorch_model.bin
131 MB
- Xet hash:
- 757609934272b7d0a413b04df93c7b50d90686f2cbe1bfb93d13e5b47aae0549
- Size of remote file:
- 131 MB
- SHA256:
- 62d6d2f715927c5d57edac8182ec79be11ccfbb41e2343c007a253ba09749210
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