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  # BGE-M3
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  In this project, we introduce BGE-M3, which is distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.
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  - MCLS: A simple method to improve the performance on long text without fine-tuning.
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  If you have no enough resource to fine-tuning model with long text, the method is useful.
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- Refer to our [report]() for more details.
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  **The fine-tuning codes and datasets will be open-sourced in the near future.**
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+ For more details please refer to our github repo: https://github.com/FlagOpen/FlagEmbedding
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  # BGE-M3
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  In this project, we introduce BGE-M3, which is distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.
 
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  - MCLS: A simple method to improve the performance on long text without fine-tuning.
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  If you have no enough resource to fine-tuning model with long text, the method is useful.
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+ Refer to our [report](https://github.com/FlagOpen/FlagEmbedding/blob/master/FlagEmbedding/BGE_M3/BGE_M3.pdf) for more details.
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  **The fine-tuning codes and datasets will be open-sourced in the near future.**
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