Instructions to use li-yan/diffusion-aurora-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use li-yan/diffusion-aurora-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("li-yan/diffusion-aurora-256", 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
Download samples/0029.png from li-yan/diffusion-aurora-256: direct link, hf CLI and curl.
- Browser
- Download file 1.82 MB
-
https://huggingface.co/li-yan/diffusion-aurora-256/resolve/main/samples/0029.png
- Command line
-
hf download hf://li-yan/diffusion-aurora-256/samples/0029.png
-
curl -L -o 0029.png https://huggingface.co/li-yan/diffusion-aurora-256/resolve/main/samples/0029.png
1.82 MB

- Xet hash:
- 5f13df778413ee70658b02cc9cceb3124135cce468fd5f2f814452f0029f8331
- Size of remote file:
- 1.82 MB
- SHA256:
- 8804c6fc84cbcd7f87ea6f251a0d28276c2fdbf2e0008c48ee6667727efff482
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