Instructions to use ortal-le/controlnet-traffic-diffusion-xl-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ortal-le/controlnet-traffic-diffusion-xl-1024 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("ortal-le/controlnet-traffic-diffusion-xl-1024") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
controlnet-ortal-le/controlnet-traffic-diffusion-xl-1024
These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning.
You can find some example images below.
prompt: A stop sign surrounded by a sky on a very cloudy day.
prompt: A stop sign on a rainy day, under a cloudy sky, with rain falling around
prompt: The warm sunlight should cast long, soft shadows,
prompt: The environment should be clear with no cloud cover, allowing the sunlight to illuminate the scene.
prompt: The scene should reflect the cold and crisp atmosphere of a snowy day
prompt: The sky should be dark, scattered with stars that twinkle

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Model tree for ortal-le/controlnet-traffic-diffusion-xl-1024
Base model
stabilityai/stable-diffusion-xl-base-1.0