Instructions to use EventDiffusion/combined_controlnet_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EventDiffusion/combined_controlnet_all with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EventDiffusion/combined_controlnet_all", 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:
- 1dc701b32106dbbe777d9b074f6c950463733b7a9f09182af80659eea666da15
- Size of remote file:
- 1.45 GB
- SHA256:
- a1360cfc65a738e37c901e77d351a81610c96e3be37f2001c22a3ccf28d7386a
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