Instructions to use YishaoAI/controlnet-wc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YishaoAI/controlnet-wc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YishaoAI/controlnet-wc", 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:
- d36d798b3062716498b246bf2b2df5ecac3be97511575d2b6091640bf31755cb
- Size of remote file:
- 3.58 GB
- SHA256:
- 6a8f0bf51785355ae4f8715b6b25d5617500bca3ae7aa583080a09a0d91ad100
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