2 Commits (6a1a0d977a994a743d5a297a2345cc9f760d0297)

Author	SHA1	Message	Date
Mohammad Mohtashim	d1b7a934aa	[Community]: HuggingFaceCrossEncoder `score` accounting for <not-relevant score,relevant score> pairs. (#22578) ... - **Description:** Some of the Cross-Encoder models provide scores in pairs, i.e., <not-relevant score (higher means the document is less relevant to the query), relevant score (higher means the document is more relevant to the query)>. However, the `HuggingFaceCrossEncoder` `score` method does not currently take into account the pair situation. This PR addresses this issue by modifying the method to consider only the relevant score if score is being provided in pair. The reason for focusing on the relevant score is that the compressors select the top-n documents based on relevance. - **Issue:** #22556 - Please also refer to this [comment](https://github.com/UKPLab/sentence-transformers/issues/568#issuecomment-729153075)	3 months ago
Kenneth Choe	f98d7f7494	langchain[minor], community[minor]: add CrossEncoderReranker with HuggingFaceCrossEncoder and SagemakerEndpointCrossEncoder (#13687) ... - **Description:** Support reranking based on cross encoder models available from HuggingFace. - Added `CrossEncoder` schema - Implemented `HuggingFaceCrossEncoder` and `SagemakerEndpointCrossEncoder` - Implemented `CrossEncoderReranker` that performs similar functionality to `CohereRerank` - Added `cross-encoder-reranker.ipynb` to demonstrate how to use it. Please let me know if anything else needs to be done to make it visible on the table-of-contents navigation bar on the left, or on the card list on [retrievers documentation page](https://python.langchain.com/docs/integrations/retrievers). - **Issue:** N/A - **Dependencies:** None other than the existing ones. --------- Co-authored-by: Kenny Choe <kchoe@amazon.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago