Instructions to use baicuya/controlnet-fill-circle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use baicuya/controlnet-fill-circle with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("baicuya/controlnet-fill-circle") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 48621ed64d9140f6bc8cd7d139a397cf198a27bb532da8e0fd565ee4a7fe4bd5
- Size of remote file:
- 1.45 GB
- SHA256:
- 2f2755803c42d818ed3f0eb6356abf34eeb3bc7acf3578f1bcc2f61c37608c84
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.