Instructions to use svjack/ControlNet-Canny-Zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use svjack/ControlNet-Canny-Zh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("svjack/ControlNet-Canny-Zh", 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:
- 4c12918f69bb858643e5a76873e7b6ffb146e3c65235363c39da807f0fe56917
- Size of remote file:
- 1.45 GB
- SHA256:
- 0caad6951098eb0a2ed27499fee07947c05d04ff604e2fd0abd1b74a01fab2cd
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