Instructions to use cross-attention/asymmetric-autoencoder-kl-x-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cross-attention/asymmetric-autoencoder-kl-x-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cross-attention/asymmetric-autoencoder-kl-x-2", 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:
- 83270b241ed8104e1c9f196eaf442161f6bbfe20cfc6129d72bbe56845a8758b
- Size of remote file:
- 1.62 GB
- SHA256:
- 9d8bf37bcf0b253256a18485a98aa35fdcc9f87375ad617128a687ae26a974e1
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