Instructions to use CruzPesto666/SD3-Controlnet-Inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CruzPesto666/SD3-Controlnet-Inpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CruzPesto666/SD3-Controlnet-Inpainting", 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
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- e94d3fe25ee683e203b4e37fb0e305c1b53c543fca7a52d83bca68df4dd74c56
- Size of remote file:
- 1.25 MB
- SHA256:
- 19bea5c3b46f8ab3971b3c2ccfab039e079825bcb4a6655f02ad9d67d53a24be
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