Instructions to use neta-art/Neta-Lumina-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use neta-art/Neta-Lumina-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("neta-art/Neta-Lumina-diffusers", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4fc7b8e6f75df7cec5813bee93816f186a67d3db9b073a6b793950a6d6a66e0d
- Size of remote file:
- 5.22 GB
- SHA256:
- 808ad9012fdbf8c3a6947fa463f09c516d06d6d4b7095c595fe513aee0eb6722
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