Instructions to use fusing/bedroom_256-ncsnpp-ve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/bedroom_256-ncsnpp-ve with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/bedroom_256-ncsnpp-ve", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download diffusion_model.pt from fusing/bedroom_256-ncsnpp-ve: direct link, hf CLI and curl.
- Browser
- Download file 263 MB
-
https://huggingface.co/fusing/bedroom_256-ncsnpp-ve/resolve/main/diffusion_model.pt
- Command line
-
hf download hf://fusing/bedroom_256-ncsnpp-ve/diffusion_model.pt
-
curl -L -o diffusion_model.pt https://huggingface.co/fusing/bedroom_256-ncsnpp-ve/resolve/main/diffusion_model.pt
263 MB
- Xet hash:
- 0dfa73349c805d24d24b139fabe232f55ae5b25a3dc025f92f5fdd0c840b19f9
- Size of remote file:
- 263 MB
- SHA256:
- 86d2e1ac2df7b27f999f295e67531e176f9b793416cb959782469ff02c789f84
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