Instructions to use patrickvonplaten/controlnet-depth-sdxl-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use patrickvonplaten/controlnet-depth-sdxl-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("patrickvonplaten/controlnet-depth-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f128187d5234047bdd629156cfacb2e2e1e04aa0b5ca54cdb0a3a064af9ed2f8
- Size of remote file:
- 2.5 GB
- SHA256:
- 7b139b4fb4b2819868616b27e3dc2935c8b4b55ec57b115c031a2d2807a61e53
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