Instructions to use maze/controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maze/controlnet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maze/controlnet", 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:
- 62de782c2af298c4ec69c5976d00daecf602e7b78ea60021d4748b7287c9d038
- Size of remote file:
- 1.45 GB
- SHA256:
- 252fb41c0165565c3fa9f9ed4b3f5a99229ebf422dedce2663d366932f88edfb
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