AI正在发生 未来正在更新bge-reranker-v2.5-gemma2-lightweight
**More details please refer to our Github: FlagEmbedding.** - Model List - Usage - Fine-tuning - Evaluation - Citation Different from embedding model, reranker uses question and document as input and directly output similarity instead of embedding. You can get a relevance score by inputting query and passage to the reranker. And the score can be mapped to a float value in [0,1] by sigmoid function.
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**More details please refer to our Github: FlagEmbedding.** - Model List - Usage - Fine-tuning - Evaluation - Citation Different from embedding model, reranker uses question and document as input and directly output similarity instead of embedding. You can get a relevance score by inputting query and passage to the reranker. And the score can be mapped to a float value in [0,1] by sigmoid function.