Instructions to use Alpha-VLLM/Lumina-Image-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alpha-VLLM/Lumina-Image-2.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Alpha-VLLM/Lumina-Image-2.0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Improve model card with metadata and citation
#16
by nielsr HF Staff - opened
README.md
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---
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pipeline_tag: text-to-image
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---
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Lumina-Image-2.0 is a 2 billion parameter flow-based diffusion transformer capable of generating images from text descriptions. For more information, visit our [GitHub](https://github.com/Alpha-VLLM/Lumina-Image-2.0).
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generator=torch.Generator("cpu").manual_seed(0)
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).images[0]
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image.save("lumina_demo.png")
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```
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---
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pipeline_tag: text-to-image
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library_name: diffusers
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license: apache-2.0
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---
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Lumina-Image-2.0 is a 2 billion parameter flow-based diffusion transformer capable of generating images from text descriptions. For more information, visit our [GitHub](https://github.com/Alpha-VLLM/Lumina-Image-2.0).
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generator=torch.Generator("cpu").manual_seed(0)
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).images[0]
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image.save("lumina_demo.png")
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```
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This is a Hugging Face Diffusers implementation of the paper [Lumina-Image 2.0: A Unified and Efficient Image Generative Framework](https://arxiv.org/abs/2503.21758).
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## Citation
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If you find the provided code or models useful for your research, consider citing them as:
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```bib
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@misc{lumina2,
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author={Qi Qin and Le Zhuo and Yi Xin and Ruoyi Du and Zhen Li and Bin Fu and Yiting Lu and Xinyue Li and Dongyang Liu and Xiangyang Zhu and Will Beddow and Erwann Millon and Victor Perez,Wenhai Wang and Yu Qiao and Bo Zhang and Xiaohong Liu and Hongsheng Li and Chang Xu and Peng Gao},
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title={Lumina-Image 2.0: A Unified and Efficient Image Generative Framework},
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year={2025},
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eprint={2503.21758},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/pdf/2503.21758},
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}
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```
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