Instructions to use alimama-creative/SD3-Controlnet-Inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alimama-creative/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("alimama-creative/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:
- 778ec66db943e3e1bbc1b70321edbd6666d1eacae25bcb61b7f1cc264ead0cee
- Size of remote file:
- 4.6 MB
- SHA256:
- 0584cbaf6f7b06994b0af219e8bd92d04fa0f6eca10a679c95ee2595c58afa60
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.