Instructions to use Montey/lua-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Montey/lua-edge with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Montey/lua-edge", 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:
- 817ce572a8a26537af171d00fb3e28fa9e7b17cdc80e754e8d2d96433e448c62
- Size of remote file:
- 687 MB
- SHA256:
- 4ca58697e0025abc011c46f214df6e0850206b11287a91e79b4fe631d1a8adaa
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