Instructions to use latentcat/control_v1u_sd15_brightness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use latentcat/control_v1u_sd15_brightness with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("latentcat/control_v1u_sd15_brightness") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
controlnet- ioclab/control_v1u_sd15_brightness
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images in the following.
prompt: a painting of a village in the mountains
prompt: three people walking in an alleyway with hats and pants

- Downloads last month
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Model tree for latentcat/control_v1u_sd15_brightness
Base model
runwayml/stable-diffusion-v1-5