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This model uses two BERT models fine-tuned on a contrastive learning objective. One is responsable for short queries, and the other for longer documents that contain the answer to the query. After encoding many documents, one may perform a nearest neighbor search with the query encoding, to fetch the most relevant document.

Take a look at inference.py to see how to perform inference.

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Dataset used to train irow/dual-bert-IR