Instructions to use KittyArtPhysics/controlnet-fill-circle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KittyArtPhysics/controlnet-fill-circle with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("KittyArtPhysics/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:
- cb55c966a7d34f12346434a80a287b60ac671851c74bd0f49f88025f645f5f18
- Size of remote file:
- 1.45 GB
- SHA256:
- 64db157ab97c90a7f42f087410ae80d924a22ac94d96f208447aa0c21ce46776
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.