Instructions to use diffusers/controlnet-canny-sdxl-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/controlnet-canny-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("diffusers/controlnet-canny-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
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- d15397048fe7d613a0d14bd7f62d19a0d34efec269eb1444206ca220b234e59a
- Size of remote file:
- 8.51 MB
- SHA256:
- b2ecd942a61e5ee4f8b5d1c8d108232a0e3a012036eaa4b8865ebfd0b7e15346
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