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---
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base_model:
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- Qwen/Qwen2.5-1.5B-Instruct
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- google/siglip-so400m-patch14-384
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datasets:
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- weizhiwang/Open-Qwen2VL-Data
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- MAmmoTH-VL/MAmmoTH-VL-Instruct-12M
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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license: cc
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pipeline_tag: image-text-to-text
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---
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# Model Card for Open-Qwen2VL-base
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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).
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## Updates
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- [4/1/2025] The codebase, model, data, and paper are released.
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<!-- ## Model Details -->
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## How to Use
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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.
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## Citation
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```bibtex
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@article{Open-Qwen2VL,
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title={Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources},
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author={Wang, Weizhi and Tian, Yu and Yang, Linjie and Wang, Heng and Yan, Xifeng},
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journal={arXiv preprint arXiv:2504.00595},
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year={2025}
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}
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... |
