Dense passage retriever (DPR) is a dense retrieval method described in the following paper:

Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih. Dense Passage Retrieval for Open-Domain Question Answering. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769-6781, 2020.

We have trained our own DPR models with our Wikipedia corpus variants using the Tevatron library.

Our own efforts are described in the paper entitled:

Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.

This is the passage encoder portion of a 2nd iteration DPR model for the wiki-text-100w corpus variant trained on the amalgamation of the NQ, TriviaQA, WQ, and CuratedTREC datasets.