Instructions to use SargeZT/controlnet-sd-xl-1.0-depth-faid-vidit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SargeZT/controlnet-sd-xl-1.0-depth-faid-vidit with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("SargeZT/controlnet-sd-xl-1.0-depth-faid-vidit") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
controlnet-SargeZT/controlnet-sd-xl-1.0-depth-faid-vidit
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: the vaporwave hills from your nightmare, unsettling, light temperature 3500, light direction south-east

License
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Model tree for SargeZT/controlnet-sd-xl-1.0-depth-faid-vidit
Base model
stabilityai/stable-diffusion-xl-base-1.0