Instructions to use latentcat/control_v1u_sd15_illumination with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use latentcat/control_v1u_sd15_illumination with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("latentcat/control_v1u_sd15_illumination") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- cc4679fff37b8e7aea44df5f8f90190a9516a11c36cba2ee55d64cf1d8f8cdee
- Size of remote file:
- 1.45 GB
- SHA256:
- d8b575152d6363421e2097fe59ec6ee0ce868a25d4d925b30bb6a32438ef012d
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