Instructions to use nghenzi/sd-class-butterflies-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nghenzi/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("nghenzi/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:
- b78eeb932e1bc1387ae365cae3d02af36baabfe88df932e950948d43ceb19e2f
- Size of remote file:
- 74.3 MB
- SHA256:
- c4e8fe41e069a235f7a916395ac05dffbce553a65df47f0b0f82a4ec5b4227d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.