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license: llama2 |
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--- |
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# SEED Multimodal |
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[Project Homepage](https://ailab-cvc.github.io/seed/) |
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**Powered by [CV Center, Tencent AI Lab](https://ailab-cvc.github.io), and [ARC Lab, Tencent PCG](https://github.com/TencentARC).** |
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## Usage |
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### Dependencies |
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- Python >= 3.8 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux)) |
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- [PyTorch >= 1.11.0](https://pytorch.org/) |
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- NVIDIA GPU + [CUDA](https://developer.nvidia.com/cuda-downloads) |
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### Installation |
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1. Clone repo |
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```bash |
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git clone https://github.com/AILab-CVC/SEED.git |
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cd SEED |
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``` |
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2. Install dependent packages |
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```bash |
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pip install -r requirements.txt |
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``` |
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### Model Weights |
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We provide the pretrained SEED Tokenizer and De-Tokenizer, instruction tuned SEED-LLaMA-8B and SEED-LLaMA-14B. |
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Please download the checkpoints and save under the folder `./pretrained`. |
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To reconstruct the image from the SEED visual codes using unCLIP SD-UNet, please download the pretrained [unCLIP SD](https://huggingface.co/stabilityai/stable-diffusion-2-1-unclip). |
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Rename the checkpoint directory to **"diffusion_model"** and create a soft link to the "pretrained/seed_tokenizer" directory. |
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### Inference for visual tokenization and de-tokenization |
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To discretize an image to 1D visual codes with causal dependency, and reconstruct the image from the visual codes using the off-the-shelf unCLIP SD-UNet: |
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```bash |
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python scripts/seed_tokenizer_inference.py |
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``` |
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### Launching Demo of SEED-LLaMA Locally |
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```bash |
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sh start_backend.sh |
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sh start_frontend.sh |
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``` |
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## Citation |
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If you find the work helpful, please consider citing: |
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```bash |
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@article{ge2023making, |
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title={Making LLaMA SEE and Draw with SEED Tokenizer}, |
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author={Ge, Yuying and Zhao, Sijie and Zeng, Ziyun and Ge, Yixiao and Li, Chen and Wang, Xintao and Shan, Ying}, |
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journal={arXiv preprint arXiv:2310.01218}, |
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year={2023} |
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} |
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@article{ge2023planting, |
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title={Planting a seed of vision in large language model}, |
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author={Ge, Yuying and Ge, Yixiao and Zeng, Ziyun and Wang, Xintao and Shan, Ying}, |
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journal={arXiv preprint arXiv:2307.08041}, |
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year={2023} |
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} |
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``` |
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The project is still in progress. Stay tuned for more updates! |
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## License |
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`SEED` is released under [Apache License Version 2.0](License.txt). |
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`SEED-LLaMA` is released under the original [License](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) of [LLaMA2](https://huggingface.co/meta-llama/Llama-2-13b-chat-hf). |
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## Acknowledgement |
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We thank the great work from [unCLIP SD](https://huggingface.co/stabilityai/stable-diffusion-2-1-unclip) and [BLIP2](https://github.com/salesforce/LAVIS). |
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