Cross Encoder for multilingual MS Marco This model was trained on the MMARCO dataset. It is a machine translated version of MS MARCO using Google Translate. It was translated to 14 languages. In our experiments, we observed that it performs also well for other languages. As a base model, we used the multilingual MiniLMv2 model. 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. See SBERT.net Retrieve & Re rank for more details. The training code is available here: SBERT.net Training MS Marco Usage with SentenceTransformers The usage becomes easy when you have SentenceTransformers installed. Then, you can use the pre trained models like this: Usage with Transformers
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