Instructions to use krnl/control_v11p_sd15_inpaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use krnl/control_v11p_sd15_inpaint with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("krnl/control_v11p_sd15_inpaint") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9cc6b77d4bafc8fdbfce7c042d964bc2efa8cad77e3d7c7097b7c5536ad918a7
- Size of remote file:
- 723 MB
- SHA256:
- 361c0cf3e3d4d13130b12f9b89fe251f9fc9b97e23af1fc277d4003c607fc6c5
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