Model type: LLaVA-Next Interleave is an open-source chatbot trained by fine-tuning LLM on multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture.
This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses, including but not limited to the OpenAI Terms of Use for the dataset and the specific licenses for base language models for checkpoints trained using the dataset (e.g. Llama-1/2 community license for LLaMA-2 and Vicuna-v1.5,
Tongyi Qianwen LICENSE AGREEMENT and
META LLAMA 3 COMMUNITY LICENSE AGREEMENT). This project does not impose any additional constraints beyond those stipulated in the original licenses. Furthermore, users are reminded to ensure that their use of the dataset and checkpoints is in compliance with all applicable laws and regulations.
Use the code below to get started with the model.
1git clone https://github.com/LLaVA-VL/LLaVA-NeXT
2# install llava-next
3...
4# download the ckpt
5...
6bash playground/demo/interleave_demo.py --model_path path/to/ckpt
Use the code below to evaluate the model.
Please first edit /path/to/ckpt to the path of checkpoint, /path/to/images to the path of "interleave_data" in scripts/interleave/eval_all.sh and then run
1@misc{li2024llavanextinterleavetacklingmultiimagevideo,
2 title={LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models},
3 author={Feng Li and Renrui Zhang and Hao Zhang and Yuanhan Zhang and Bo Li and Wei Li and Zejun Ma and Chunyuan Li},
4 year={2024},
5 eprint={2407.07895},
6 archivePrefix={arXiv},
7 primaryClass={cs.CV},
8 url={https://arxiv.org/abs/2407.07895},
9}
