Instructions to use qiongzhouh/anime_canny_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use qiongzhouh/anime_canny_test with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("qiongzhouh/anime_canny_test") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline
controlnet = ControlNetModel.from_pretrained("qiongzhouh/anime_canny_test")
pipe = StableDiffusionControlNetPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", controlnet=controlnet
)controlnet-qiongzhouh/anime_canny_test
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning.
You can find some example images below.
prompt: anime face of a girl with brown hair and brown eyes on a white background
prompt: anime face of a boy with black hair and orange eyes on a white background

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Model tree for qiongzhouh/anime_canny_test
Base model
runwayml/stable-diffusion-v1-5