Instructions to use callgg/lumina-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/lumina-decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("callgg/lumina-decoder", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 536c29ffc7dad3ce86b9783d4816844255f82ed25097ffd198be482802f90571
- Size of remote file:
- 10.5 GB
- SHA256:
- 898bc331f257559fcce583f90c820780a99d7432d36e6bc0abc22295c1cbe5c0
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