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:
- 7f422a237bf614a01c614425e925a5d72854b2fdab4a643129b6a52be24799ec
- Size of remote file:
- 1.45 GB
- SHA256:
- 208d550a521a9d503c4c1c2fc6cef8341449b0181ddc0027798e7808e0ffc667
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