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--- |
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license: apache-2.0 |
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pipeline_tag: image-text-to-text |
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library_name: transformers |
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paper: https://arxiv.org/abs/2409.03277 |
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--- |
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<p align="center"> |
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<b><font size="6">ChartMoE</font></b> |
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<p> |
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<p align="center"> |
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<b><font size="4">ICLR2025 Oral </font></b> |
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<p> |
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<div align="center"> |
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<div style="display: inline-block; margin-right: 30px;"> |
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[](https://arxiv.org/abs/2409.03277) |
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</div> |
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<div style="display: inline-block; margin-right: 30px;"> |
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[](https://chartmoe.github.io/) |
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</div> |
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<div style="display: inline-block; margin-right: 30px;"> |
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[](https://github.com/IDEA-FinAI/ChartMoE) |
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</div> |
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<div style="display: inline-block; margin-right: 30px;"> |
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[](https://huggingface.co/IDEA-FinAI/chartmoe) |
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</div> |
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</div> |
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**ChartMoE** is a multimodal large language model with Mixture-of-Expert connector, based on [InternLM-XComposer2](https://github.com/InternLM/InternLM-XComposer/tree/main/InternLM-XComposer-2.0) for advanced chart 1)understanding, 2)replot, 3)editing, 4)highlighting and 5)transformation. |
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**This is a reproduction of diversely-aligner moe-connector, please feel free to use it for continue sft training!** |
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## Open Source License |
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The data is licensed under Apache-2.0. |