Instructions to use SwePalm/sd-class-butterflies-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SwePalm/sd-class-butterflies-64 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SwePalm/sd-class-butterflies-64", 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:
- cdd8581e7aa9c3c88d3d570d3a85e110ba26de6c0748a330c18323c4896541e5
- Size of remote file:
- 455 MB
- SHA256:
- fdf0878d028210166ee9647d426ffeb005bd41d76cd1109982ffe3a717066ee1
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