Instructions to use Abhi5ingh/ControlnetDresscode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Abhi5ingh/ControlnetDresscode with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Abhi5ingh/ControlnetDresscode") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 0fd24b4c7ad79dc8789080e1deb520037d7868ad1cfc11ea681736d9835de3c9
- Size of remote file:
- 4.43 MB
- SHA256:
- 0c52787ddb315bb5859c9e476c6b06921498f927bb1eb5e2f6699b98a8423a75
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