Instructions to use ucfzl/ControlNet_segmentation_ADE20K_CPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ucfzl/ControlNet_segmentation_ADE20K_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_segmentation_ADE20K_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:
- 64cf2a96e1b88ec629efafdf24c52fdd2af161f87ce318a70d738954edd0c01a
- Size of remote file:
- 1.45 GB
- SHA256:
- 8e752e4f411cfaf6a7e4371b50ba245934cabf97d83fba18ee2623b97df182c4
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