Instructions to use ucfzl/ControlNet_Depth_CPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ucfzl/ControlNet_Depth_CPO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ucfzl/ControlNet_Depth_CPO", 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:
- f752dcb0062006d6e12aa40eb94e1c3a798748c1ff4f80d31de68a6cca110eeb
- Size of remote file:
- 1.45 GB
- SHA256:
- 61c89546d051a908beae89451071ed8528bff2c76cdbe4003f4ce6c996bb8420
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