Instructions to use fusing/unet-ldm-dummy-update with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/unet-ldm-dummy-update with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fusing/unet-ldm-dummy-update", 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:
- 88832753e1e0e0af5823f751c7c1c7508f83581647534ab5922db0390d642f74
- Size of remote file:
- 3.73 MB
- SHA256:
- e37e519cf89960501f9ea78e893268686e7fead6c3afc8dd640dbdea2bf2f651
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