Instructions to use fansstar/butterfly-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fansstar/butterfly-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("fansstar/butterfly-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 diffusion_pytorch_model.safetensors from fansstar/butterfly-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 74.2 MB
-
https://huggingface.co/fansstar/butterfly-diffusers/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://fansstar/butterfly-diffusers/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/fansstar/butterfly-diffusers/resolve/main/diffusion_pytorch_model.safetensors
74.2 MB
- Xet hash:
- 8339576dc8b36e7449b47e17a570b13b66049a4d36903821f2d2ca56949f9784
- Size of remote file:
- 74.2 MB
- SHA256:
- 2894f94df32d94beefbc737a026ec801df52f39a18925a711fb62123393b5414
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