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- [x] Checkpoint
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- [x] Training Data
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- [x] Training Code
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- [x] Technical Report
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- [ ] Evaluation Pipeline
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- [ ] Technical Report
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We will release the technical report for **BGE-EN-ICL** in the future.
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The technical report for **BGE-EN-ICL** can be found in [Making Text Embedders Few-Shot Learners](https://arxiv.org/abs/2409.15700)
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## Environment
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```bash
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| Data | Introduction |
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| ------------------------------------------------------------ | ------------------------------------------------------------ |
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| [e5-data](https://huggingface.co/datasets/cfli/bge-e5data) | Public data identical to [e5-mistral](https://huggingface.co/intfloat/e5-mistral-7b-instruct) |
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| [public-data](https://huggingface.co/datasets/cfli/bge-e5data) | Public data identical to [e5-mistral](https://huggingface.co/intfloat/e5-mistral-7b-instruct) |
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| [full-data](https://huggingface.co/datasets/cfli/bge-full-data) | The full dataset we used for training |
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## Usage
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To cite our work:
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```
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@misc{li2023makinglargelanguagemodels,
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title={Making Large Language Models A Better Foundation For Dense Retrieval},
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author={Chaofan Li and Zheng Liu and Shitao Xiao and Yingxia Shao},
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year={2023},
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eprint={2312.15503},
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@misc{li2024makingtextembeddersfewshot,
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title={Making Text Embedders Few-Shot Learners},
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author={Chaofan Li and MingHao Qin and Shitao Xiao and Jianlyu Chen and Kun Luo and Yingxia Shao and Defu Lian and Zheng Liu},
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year={2024},
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eprint={2409.15700},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2312.15503},
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primaryClass={cs.IR},
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url={https://arxiv.org/abs/2409.15700},
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}
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```

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