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:
- 533c0eee71e5d844f537921f525ab2da58e2c4373118a0c388f9853a4415709c
- Size of remote file:
- 4.38 MB
- SHA256:
- b55b269808c454540d56a2f88ddad5ca917050facc8a4096ce3a790d79907602
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