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-5500/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-5500/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Nacholmo/controlnet-qr-pattern/checkpoint-5500/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Nacholmo/controlnet-qr-pattern/resolve/main/checkpoint-5500/controlnet/diffusion_pytorch_model.bin
1.45 GB
- Xet hash:
- 1554f31747a8029283ae205bf1b12970cbfb9a2e31e6a219d5b44974e16e9a8a
- Size of remote file:
- 1.45 GB
- SHA256:
- 71d52e8a08f3da8ee2c68f81d0403843f5a606de9b689cceadcc6283fb6e2bf9
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