Instructions to use aa-studio/aa_studio_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aa-studio/aa_studio_data with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aa-studio/aa_studio_data", 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:
- c24750af12e9914deb68c199e8b191c9306e666333bb79834487cef2e3774e95
- Size of remote file:
- 2.5 GB
- SHA256:
- 8ba4dfaa1958f1f68e5dc7f9839f9ef4e153aef0d330291e5cf966c925f97477
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