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", torch_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:
- c3d83a944afa2c6cca37469de039ecbc81117b0c85a77bb500e4e14a899bec34
- Size of remote file:
- 1.96 kB
- SHA256:
- 291ae050720fcc5d2ed6d51a7d4b2f80f83972e2469e9b0362fce490b2fd1d6b
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