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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7b95d9bd73228dfc10fce128a79f9502e67c6669fb8602ba19505d57ae6aded2
- Size of remote file:
- 1.45 GB
- SHA256:
- 8a75a707a95f2cf2818d447093cb9c6b13ecf7c2328a575c52979de8e19cb1dc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.