Instructions to use ucfzl/ControlNet_Canny_CPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ucfzl/ControlNet_Canny_CPO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ucfzl/ControlNet_Canny_CPO", 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:
- 8654685b068054c09c2d304c3694fd4e28c9a98d95553b7afe0e102c62a2524e
- Size of remote file:
- 1.45 GB
- SHA256:
- 7af951958580839a717411812a9605c804a29146c69126b20143d4c9e49c7bf1
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