Instructions to use jeblance/sd-class-butterflies-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jeblance/sd-class-butterflies-32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jeblance/sd-class-butterflies-32", 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.bin from jeblance/sd-class-butterflies-32: direct link, hf CLI and curl.
- Browser
- Download file 74.3 MB
-
https://huggingface.co/jeblance/sd-class-butterflies-32/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://jeblance/sd-class-butterflies-32/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/jeblance/sd-class-butterflies-32/resolve/main/diffusion_pytorch_model.bin
74.3 MB
- Xet hash:
- 7171e331192a26a72707c9aca71cfbed47a6e1c063c46d08a2b89ce03e1d8f1f
- Size of remote file:
- 74.3 MB
- SHA256:
- cfbad024fb6d132d3f42bc0dd8460b8809034cb0d3b3aa91781de3c9526a0fa7
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