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:
- 4ea4f595a1551e4a4fbbe195c583db8821a122c524debe91754adca0079697c5
- Size of remote file:
- 2.03 kB
- SHA256:
- 661e64407e425966297c0f6ea1a62c3a7e322bc52b7c4e72eb6a48fadba9e4a7
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