Instructions to use joweyel/sd-class-butterflies-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use joweyel/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("joweyel/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
- Xet hash:
- d14f7c235df4fc97a6b3d0db8fd850a6f71872407eaeb155ac97e83833349ed0
- Size of remote file:
- 74.3 MB
- SHA256:
- 8ec08e8f543c97a819328c67a05d2df96e6ea7818970de240d33376be34f02fc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.