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---
license: llama2
---
# v-MLLM Model Card
## Model details
**Model type:**
v-MLLM is an open-source MLLM trained on Visual-Modality Instruction (VIM) corpus, it can robustly follow the text-modality instructions and visual-modality instructions.
**Model date:**
v-MLLM-13B was trained in January 2024.
**Github for more information:**
https://github.com/VIM-Bench/VIM_TOOL
## License
v-MLLM is licensed under the LLAMA 2 Community License,
Copyright (c) Meta Platforms, Inc. All Rights Reserved.
## Intended use
**Primary intended uses:**
The primary use of v-MLLM is for research on multimodal large language models.
**Primary intended users:**
The primary intended users of the model are researchers in computer vision, natural language processing, machine learning, and artificial intelligence.
## Training dataset
- 846k VIM corpus based on LVIS-Instruct4V corpus.
# Citation
Please kindly cite our paper if you find our resources useful:
```
@misc{li2024text,
title={Text as Images: Can Multimodal Large Language Models Follow Printed Instructions in Pixels?},
author={Xiujun Li and Yujie Lu and Zhe Gan and Jianfeng Gao and William Yang Wang and Yejin Choi},
year={2024},
eprint={2311.17647},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{lu2023vim,
title={VIM: Probing Multimodal Large Language Models for Visual Embedded Instruction Following},
author={Yujie Lu and Xiujun Li and William Yang Wang and Yejin Choi},
year={2023},
eprint={2311.17647},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
``` |