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:
- 49b8d90c24db084c5933f13a1a9df3fb02a5d2a1bbb470b7e0de6ca905574660
- Size of remote file:
- 5 GB
- SHA256:
- edf33a2662e4f270d4eeeff3a56292bed7a050eba13841d07bba8a213f08a090
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