# English Semantic Matching

A cross-encoder model trained on the msmarco dataset using the sentence-transformers library, designed for text re-ranking and semantic search

A lightweight sentence embedding model based on BERT for efficient calculation of sentence similarity

A cross-encoder model trained on the MS Marco passage ranking task for query-passage relevance scoring in information retrieval.

BERT is a pre-trained language model based on the Transformer architecture, developed by Google. It understands text through bidirectional context and is suitable for various natural language processing tasks.

A cross-encoder trained on the ELECTRA-base architecture, specifically optimized for the MS Marco passage ranking task, used for query-passage relevance scoring in information retrieval.

A cross-encoder model trained on the MS Marco passage ranking task for scoring query-passage relevance in information retrieval

A cross-encoder model trained on the MS Marco passage ranking task for relevance ranking in information retrieval.