Instructions to use Nacholmo/controlnet-qr-pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nacholmo/controlnet-qr-pattern with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Nacholmo/controlnet-qr-pattern") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
Download checkpoint-9000/controlnet/diffusion_pytorch_model.bin from Nacholmo/controlnet-qr-pattern: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/Nacholmo/controlnet-qr-pattern/resolve/main/checkpoint-9000/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Nacholmo/controlnet-qr-pattern/checkpoint-9000/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Nacholmo/controlnet-qr-pattern/resolve/main/checkpoint-9000/controlnet/diffusion_pytorch_model.bin
1.45 GB
- Xet hash:
- 83dbaf981ecd8ce76d81d062bd1ce23e74c4f390fca527217785ba77aff27df7
- Size of remote file:
- 1.45 GB
- SHA256:
- 923c271c92dc9478f1bc7dd4c15d0a8d3cedd3460a704a7e2405664519705367
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