Instructions to use jise/controlnet-X-ray with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jise/controlnet-X-ray with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("jise/controlnet-X-ray") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 766e1b1bd0db46bfe7c5a40bffaf7a3a453d1eb86c8228758e27ac4bf10f707d
- Size of remote file:
- 1.45 GB
- SHA256:
- b99398ffce8767ec68007b8d7b502e7d44c7c7333688512401a589db40a294f0
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