Instructions to use EventDiffusion/combined_unet_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EventDiffusion/combined_unet_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_unet_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:
- 359dc2c3ece51eb782ef003bd0cbe290a8918976931b5fe3a8a45b3f57663994
- Size of remote file:
- 3.44 GB
- SHA256:
- 049aa5945f46ae9914e9f6caeac3bb318086110fdc5ad36fa8361165bd7e7573
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