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-8000/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-8000/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Nacholmo/controlnet-qr-pattern/checkpoint-8000/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Nacholmo/controlnet-qr-pattern/resolve/main/checkpoint-8000/controlnet/diffusion_pytorch_model.bin
1.45 GB
- Xet hash:
- 5ce627db7a166a7a6828ceb257eb86a4bfa4a4108e507a9afe87cd8f747e1d81
- Size of remote file:
- 1.45 GB
- SHA256:
- 6175fa8eb5ca74eef498df3f3fcd6a1a110d58d67ff65ca4add69ec24b0479ea
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