Instructions to use dskill/sd-class-butterflies-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dskill/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("dskill/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 dskill/sd-class-butterflies-32: direct link, hf CLI and curl.
- Browser
- Download file 74.3 MB
-
https://huggingface.co/dskill/sd-class-butterflies-32/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://dskill/sd-class-butterflies-32/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/dskill/sd-class-butterflies-32/resolve/main/diffusion_pytorch_model.bin
74.3 MB
- Xet hash:
- 41df9a5b7438418b10f12fe1e272a41598be3c5722a6e13babb2cf0fd0ee8540
- Size of remote file:
- 74.3 MB
- SHA256:
- c40424376fd7ec373997172ffdd45d7d7b6900dc087aa6a203e85fe3f2cb232b
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