Lumina-Image 2.0: A Unified and Efficient Image Generative Framework

 

   

📰 News

• [2025-2-20] Diffusers team released a LoRA fine-tuning script for Lumina2. Find out more here.
• [2025-2-12] Lumina 2.0 is now available in Diffusers. Check out the docs to know more.
• [2025-2-10] The official Hugging Face Space for Lumina-Image 2.0 is now available.
• [2025-2-10] Preliminary explorations of video generation with Lumina-Video 1.0 have been released.
• [2025-2-5] ComfyUI now supports Lumina-Image 2.0! 🎉 Thanks to ComfyUI@ComfyUI! 🙌 Feel free to try it out! 🚀
• [2025-1-31] We have released the latest .pth format weight file Hugging Face.
• [2025-1-25] 🚀🚀🚀 We are excited to release Lumina-Image 2.0, including:
  • 🎯 Checkpoints, Fine-Tuning and Inference code.
  • 🎯 Website & Demo are live now! Check out the Huiying and Gradio Demo!

📑 Open-source Plan

• Inference
• Checkpoints
• Web Demo (Gradio)
• Finetuning code
• ComfyUI
• Diffusers
• Technical Report
• Unified multi-image generation
• Control
• PEFT (LLaMa-Adapter V2)

🎥 Demo

Demo.mp4

🎨 Qualitative Performance

📊 Quantatitive Performance

🎮 Model Zoo

Resolution	Parameter	Text Encoder	VAE	Download URL
1024	2.6B	Gemma-2-2B	FLUX-VAE-16CH	hugging face

💻 Finetuning Code

1. Create a conda environment and install PyTorch

conda create -n Lumina2 -y
conda activate Lumina2
conda install python=3.11 pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia -y

2.Install dependencies

pip install -r requirements.txt

3. Install flash-attn

pip install flash-attn --no-build-isolation

4. Prepare data

You can place the links to your data files in ./configs/data.yaml. Your image-text pair training data format should adhere to the following:

{
    "image_path": "path/to/your/image",
    "prompt": "a description of the image"
}

5. Start finetuning

bash scripts/run_1024_finetune.sh

🚀 Inference Code

We support multiple solvers including Midpoint Solver, Euler Solver, and DPM Solver for inference.

Note

Both the Gradio demo and the direct inference method use the .pth format weight file, which can be downloaded from Google Drive.

Note

You can also directly download from huggingface. We have uploaded the .pth weight files, and you can simply specify the --ckpt argument as the download directory.

• Gradio Demo

python demo.py \
    --ckpt /path/to/your/ckpt \
    --res 1024 \
    --port 12123

• Direct Batch Inference

bash scripts/sample.sh

Citation

If you find the provided code or models useful for your research, consider citing them as:

@misc{lumina2,
    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},
    title={Lumina-Image 2.0: A Unified and Efficient Image Generative Framework},
    year={2025},
    howpublished={\url{https://github.com/Alpha-VLLM/Lumina-Image-2.0}},
}