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:
- 6f18c59d52e33f33ed1681e07eed91ac3034c0aea8ef099aaae3635cd03cfda3
- Size of remote file:
- 1.45 GB
- SHA256:
- d24a3bfbf572e48b7f4ca381aaea463b5d743748787551cfc1575bcf1b1723ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.