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
Download images/3_compressed.png from alimama-creative/SD3-Controlnet-Inpainting: direct link, hf CLI and curl.
- Browser
- Download file 1.25 MB
-
https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/resolve/main/images/3_compressed.png
- Command line
-
hf download hf://alimama-creative/SD3-Controlnet-Inpainting/images/3_compressed.png
-
curl -L -o 3_compressed.png https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/resolve/main/images/3_compressed.png
1.25 MB

- Xet hash:
- 43fb72df0e33c71d2f0d3ac678063c493b0d8fc75d7ae3faef736e0f954c2a14
- Size of remote file:
- 1.25 MB
- SHA256:
- 00ff2cb2269536cbf200d6ea02ed7067f6d0c7a26dd586e68dccd53c1d3bd966
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.