readme: Check our SIGIR2021 short paper: https://dl.acm.org/doi/10.1145/3404835.3463048
  
  This checkpoint is a variant of monot5 (T5 pointwise re-ranking model). 
  Specifically, we fuse the "P2Q (i.e. doc2query)" and "Rank (i.e. passage ranking)" to learn the **discriminative** view (Rank) and **geneartive** view (P2Q). 
  
  We found that under the specific **mixing ratio** of these two task, the effectiveness of passage re-ranking improves on par with monot5-3B models.
  Hence, you can try to do both the task with this checkpoint by the following input format:
  - P2Q: Document: *\<here is a document or a passage\>* Translate Document to Query:
  - Rank: Query: *\<here is a query\>* Document: *\<here is a document or a passage\>* Relevant: 
  
  which the outputs will be like:
  - P2Q: *\<relevant query of the given text\>*
  - Rank: *true* or *false*
  
  ```
  Note that we usually use the logit values of *true*/ *false* token from T5 reranker as our query-passage relevant scores
  Note the above tokens are all case-sensitive.
  ```