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README.md
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**SFR-Embedding by Salesforce Research.**
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The model is trained on top of [E5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) and [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). The model has 32 layers and the embedding size is 4096.
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More technical details will be updated later.
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scores = (embeddings[:2] @ embeddings[2:].T) * 100
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print(scores.tolist())
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```
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SFR-Embedding Team
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* Semih Yavuz
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* Yingbo Zhou
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* Caiming Xiong
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**SFR-Embedding by Salesforce Research.**
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The model is trained on top of [E5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) and [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). The model has 32 layers and the embedding size is 4096.
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More technical details will be updated later.
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scores = (embeddings[:2] @ embeddings[2:].T) * 100
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print(scores.tolist())
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```
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Full MTEB evaluation will be added soon.
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SFR-Embedding Team
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* Semih Yavuz
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* Yingbo Zhou
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* Caiming Xiong
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This project is for research purposes only. Third-party datasets may be subject to additional terms and conditions under their associated licenses. Please refer to specific papers for more details:
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- [E5 Dataset](https://arxiv.org/abs/2212.03533)
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- [MTEB Dataset](https://arxiv.org/abs/2210.07316)
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- [Mistral Dataset](https://arxiv.org/abs/2310.06825)
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