readme: ---
  datasets:
  - BeIR/msmarco
  language:
  - en
  ---
  
  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.