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请问目前评测中文数据时,使用的chunk是多少?使用gpt4构造出来的Q和reference_context是强相关关系嘛?因为在我们私有评测数据集下效果没有这么出众呢?
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感谢对bce模型的关注~ 1、数据构造方式是:https://github.com/netease-youdao/BCEmbedding/tree/master?tab=readme-ov-file#3-broad-domain-adaptability 参考llamaIndex博客的评测方式(目前rag一般都这么做,试一下就知道是否科学) 2、bce reranker社区反馈很不错的。如果您的场景效果无法满足需求,可以尝试别的模型试试,真实效果以自己场景实测为准。
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请问目前评测中文数据时,使用的chunk是多少?使用gpt4构造出来的Q和reference_context是强相关关系嘛?因为在我们私有评测数据集下效果没有这么出众呢?
The text was updated successfully, but these errors were encountered: