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:
- 5ed56180333001fe8483897d725f5c0dc9a75eb2b8be912a1cc91c5f61a3b2d9
- Size of remote file:
- 1.45 GB
- SHA256:
- 75a6bd039a9356ae48bc3589989f6725b6f29e00b8c968589fccc9999262f50f
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