OneLLM: One Framework to Align All Modalities with Language

[Project Page] [Paper] [HF Demo🤗] [Modelscope Demo🤖] [Model🤗]

News

• 2023.12.01 Release model weights and inference code.🎉

Contents

• Install
• Models
• Demo

TODO

• Data
• Evaluation
• Training

Install

1. Clone the repo into a local folder.

git clone https://github.com/csuhan/OneLLM

cd OneLLM

2. Install packages.

conda create -n onellm python=3.9 -y
conda activate onellm

pip install -r requirements.txt

# install pointnet
cd model/lib/pointnet2
python setup.py install

3. Install Apex. (Optional)

git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./

Models

We provide a preview model on the Hugging Face at: csuhan/OneLLM-7B.

Demo

Huggingface Demo: csuhan/OneLLM.

Local Demo: Assume you have downloaded the weights to ${WEIGHTS_DIR}. Then run the following command to start a gradio demo locally.

python demos/multi_turn_mm.py --gpu_ids 0 --tokenizer_path config/llama2/tokenizer.model --llama_config config/llama2/7B.json --pretrained_path ${WEIGHTS_DIR}/consolidated.00-of-01.pth

Citation

@article{han2023onellm,
  title={OneLLM: One Framework to Align All Modalities with Language},
  author={Han, Jiaming and Gong, Kaixiong and Zhang, Yiyuan and Wang, Jiaqi and Zhang, Kaipeng and Lin, Dahua and Qiao, Yu and Gao, Peng and Yue, Xiangyu},
  journal={arXiv preprint arXiv:2312.03700},
  year={2023}
}

Acknowledgement

LLaMA, LLaMA-Adapter, LLaMA2-Accessory, Meta-Transformer, ChatBridge

License

This project is developed based on Llama 2, please refer to the LLAMA 2 Community License.