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  For more details please refer to our Github: [FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding).
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- **BGE-EN-Mistral** primarily demonstrates the following capabilities:
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  - In-context learning ability: By providing few-shot examples in the query, it can significantly enhance the model's ability to handle new tasks.
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  - Outstanding performance: The model has achieved state-of-the-art (SOTA) performance on both BEIR and AIR-Bench.
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  - [ ] Evaluation Pipeline
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  - [ ] Technical Report
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- We will release the technical report and training data for **BGE-EN-Mistral** in the future.
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  ## Usage
 
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  For more details please refer to our Github: [FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding).
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+ **BGE-EN-ICL** primarily demonstrates the following capabilities:
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  - In-context learning ability: By providing few-shot examples in the query, it can significantly enhance the model's ability to handle new tasks.
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  - Outstanding performance: The model has achieved state-of-the-art (SOTA) performance on both BEIR and AIR-Bench.
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  - [ ] Evaluation Pipeline
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  - [ ] Technical Report
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+ We will release the technical report and training data for **BGE-EN-ICL** in the future.
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  ## Usage