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---
base_model:
- Qwen/Qwen2.5-1.5B-Instruct
- google/siglip-so400m-patch14-384
datasets:
- weizhiwang/Open-Qwen2VL-Data
- MAmmoTH-VL/MAmmoTH-VL-Instruct-12M
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
license: cc
pipeline_tag: image-text-to-text
---
# Model Card for Open-Qwen2VL-base
Open-Qwen2VL-base is a pre-trained base multimodal model that takes images and text as input and produces text as output. This model is described in the paper [Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources](https://huggingface.co/papers/2504.00595). The code is available at [https://github.com/Victorwz/Open-Qwen2VL](https://github.com/Victorwz/Open-Qwen2VL).
## Updates
- [4/1/2025] The codebase, model, data, and paper are released.
<!-- ## Model Details -->
## How to Use
The base model is released for further fine-tuning on public SFT data or customized SFT data. It is not appropriate for normal task completions.
## Citation
```bibtex
@article{Open-Qwen2VL,
title={Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources},
author={Wang, Weizhi and Tian, Yu and Yang, Linjie and Wang, Heng and Yan, Xifeng},
journal={arXiv preprint arXiv:2504.00595},
year={2025}
}
... |