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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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- en |
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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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... |