In Dense Passage Retrieval  for Open-Domain Question Answering  Karpukhin et al. trained models based on Google's Natural Questions dataset:
- facebook-dpr-ctx_encoder-single-nq-base 
- facebook-dpr-question_encoder-single-nq-base
They also trained models on the combination of Natural Questions, TriviaQA, WebQuestions, and CuratedTREC.
- facebook-dpr-ctx_encoder-multiset-base 
- facebook-dpr-question_encoder-multiset-base
There is one model to encode passages and one model to encode question / queries.
Usage
To encode paragraphs, you need to provide a title (e.g. the Wikipedia article title) and the text passage. These must be seperated with a [SEP] token.  For encoding paragraphs, we use the ctx_encoder.
Queries are encoded with question_encoder:
```python
from sentence_transformers import SentenceTransformer, util
