Instructions to use jax-diffusers-event/canny-coyo1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jax-diffusers-event/canny-coyo1m with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("jax-diffusers-event/canny-coyo1m") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 6a14072444f43cf56633a6812e452e27867fbb26473eacc3e3cfbf4c0463d23b
- Size of remote file:
- 5.96 MB
- SHA256:
- e54306778ecb7f3395f087365ffd29d0653b41dce0586d2217b439807eba5d2e
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