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README.md
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The [ModernVBERT](https://arxiv.org/abs/2510.01149) suite is a suite of compact 250M-parameter vision-language encoders, achieving state-of-the-art performance in this size class, matching the performance of models up to 10x larger.
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For more information about ModernVBERT, please check
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### Models
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- `colmodernvbert` (*ColModernVBERT* in the paper) is the late-interaction version that is fine-tuned for visual document retrieval tasks, our most performant model on this task.
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```
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## Evaluation
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<div>
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<img src="../imgs/table.png" width="100%" alt="ModernVBERT Results" />
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</div>
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ColModernVBERT matches the performance of models nearly 10x larger on visual document benchmarks. Additionally, it provides an interesting inference speed on CPU compared to the models of similar performance.
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## License
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The [ModernVBERT](https://arxiv.org/abs/2510.01149) suite is a suite of compact 250M-parameter vision-language encoders, achieving state-of-the-art performance in this size class, matching the performance of models up to 10x larger.
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For more information about ModernVBERT, please check the [arXiv](https://arxiv.org/abs/2510.01149) preprint.
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### Models
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- `colmodernvbert` (*ColModernVBERT* in the paper) is the late-interaction version that is fine-tuned for visual document retrieval tasks, our most performant model on this task.
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```
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## Evaluation
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ColModernVBERT matches the performance of models nearly 10x larger on visual document benchmarks. Additionally, it provides an interesting inference speed on CPU compared to the models of similar performance.
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## License
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