Instructions to use Jinstudio/control_v11p_sd15_canny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jinstudio/control_v11p_sd15_canny with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Jinstudio/control_v11p_sd15_canny") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
Download diffusion_pytorch_model.bin from Jinstudio/control_v11p_sd15_canny: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/Jinstudio/control_v11p_sd15_canny/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Jinstudio/control_v11p_sd15_canny/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Jinstudio/control_v11p_sd15_canny/resolve/main/diffusion_pytorch_model.bin
1.45 GB
- Xet hash:
- 97c4ecd2b9c77dd00e7bc04c8e6d00693342f4c3d1c3bb4a8ca6d3173f8f9acc
- Size of remote file:
- 1.45 GB
- SHA256:
- 62364453cb4230f0e94669b4d36d723c292622268c3d5e30ed4aff128c7509f1
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