cross-encoder/ms-marco-TinyBERT-L-6

The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch) Then sort the passages in a decreasing order . The training code is available here: SBERT.net Training MS Marco.net . Pre-trained Cross-Encoders have been used in the TREC Deep Learning 2019 and the MS Marco Passage Reranking dataset . The performance of these models has been significantly improved on a V100 GPU-powered Python tokenizer based on Rust . The model was trained on MS Marco Passage Ranking task. The model is based on General_TinyBERT_v2(6layer,