sentence-transformers/ce-ms-marco-TinyBERT-L-2

The model uses BERT-Tiny, a tiny BERT model with only 2 layers, 2 attention heads and 128 dimension size . It was trained on MS Marco Passage Ranking task . 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 models can be . used like this: Pre- trained models can . be used to encode queries and sort them in order to sort the . passages . The pre-trained model was computed on a V,