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
- Draw Things
- DiffusionBee
- Xet hash:
- 47a2b2e3503e792eb398c4d03660b714bd6ddeaddf7afc324b837851bb452d51
- Size of remote file:
- 47.5 MB
- SHA256:
- a34ad751975a95695f04a61a6569040511abf1ccbb0c6103a0b8558cb99c7aee
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