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-3000/scheduler.bin from Nacholmo/controlnet-qr-pattern: direct link, hf CLI and curl.
- Browser
- Download file 563 Bytes
-
https://huggingface.co/Nacholmo/controlnet-qr-pattern/resolve/main/checkpoint-3000/scheduler.bin
- Command line
-
hf download hf://Nacholmo/controlnet-qr-pattern/checkpoint-3000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/Nacholmo/controlnet-qr-pattern/resolve/main/checkpoint-3000/scheduler.bin
563 Bytes
- Xet hash:
- 69807f3b9a1c85d181be291e7862ea051f75a4eb5381f5ed013fef4109849916
- Size of remote file:
- 563 Bytes
- SHA256:
- 3d6ec0338061ab706b1805a9e2966ca126b26619cd90bb73133127681b9de370
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.