Instructions to use camenduru/champ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camenduru/champ with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camenduru/champ", 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:
- e6ea1b24464398453c18d3e5500fb740b09fd424d15bed2cd512ed0b75efa5c8
- Size of remote file:
- 2.65 GB
- SHA256:
- 0680fd45ec8a3d861be4ed9fa17177b3f52ad51e6fe0c988bcd59c83a79ba12c
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