Instructions to use yuna199/controlnet-circle-example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yuna199/controlnet-circle-example with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("yuna199/controlnet-circle-example") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d501b8eb9d1c2c02c01ba3d69c5cc33be51e654511e932b6a2e9dfe89fa454cf
- Size of remote file:
- 563 Bytes
- SHA256:
- c13d19a790c3b70de0c58d8be6eda53cbc852819b276ffcfe81fcb4f0bbdb79a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.