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  [Github](https://github.com/vec-ai/lychee-embed) | [Paper](https://openreview.net/pdf?id=NC6G1KCxlt)
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- `Lychee-embed` is the latest generalist text embedding model developed based on the `Qwen2.5` basic model. It is suitable for text retrieval (semantic correlation), text similarity and other downstream tasks, and supports multiple languages of `Qwen2.5`.
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  `Lychee-embed` is jointly developed by the NLP Team of Harbin Institute of Technology, Shenzhen and is built based on an innovative multi-stage training framework (warm-up, task-learning, model merging, annealing).
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  The first batch of open source is 1.5B parameter version.
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  [Github](https://github.com/vec-ai/lychee-embed) | [Paper](https://openreview.net/pdf?id=NC6G1KCxlt)
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+ `Lychee-embed` is the latest generalist text embedding model based on the `Qwen2.5` model. It is suitable for text retrieval (semantic correlation), text similarity and other downstream tasks, and supports multiple languages of `Qwen2.5`.
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  `Lychee-embed` is jointly developed by the NLP Team of Harbin Institute of Technology, Shenzhen and is built based on an innovative multi-stage training framework (warm-up, task-learning, model merging, annealing).
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  The first batch of open source is 1.5B parameter version.
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