Instructions to use ATSiem/sd-class-butterflies-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ATSiem/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("ATSiem/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:
- b7dfe1c4ff853c8ba87e110f861952aa96856fd40352033d0af70c03e421f903
- Size of remote file:
- 74.3 MB
- SHA256:
- 28b8eb6d3eba0a867ec9a2f750cc0fe0f9c7be2c2588c06a5d797e59eca3c796
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.