Instructions to use recoilme/ae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use recoilme/ae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("recoilme/ae", 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
Upload unet640.zip with huggingface_hub
Browse files- unet640.zip +3 -0
unet640.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:7d651db024b4261d3e8b65b128ceb3239a344631d432112b15aafb7d4deb2683
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size 3302476713
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