Instructions to use discus0434/lumina-accessory-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use discus0434/lumina-accessory-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("discus0434/lumina-accessory-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
| { | |
| "_class_name": "Lumina2Pipeline", | |
| "_diffusers_version": "0.34.0", | |
| "_name_or_path": "hanzogak/neta-lumina-v1.0-diffusers", | |
| "scheduler": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "Gemma2Model" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "GemmaTokenizer" | |
| ], | |
| "transformer": [ | |
| "src.transformer_lumina2_accessory", | |
| "Lumina2Transformer2DModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } |