readme: ---
  datasets:
  - squad
  tags:
  - question-answer-generation
  widget:
  - text: "generate question: <hl> 42 <hl> is the answer to life, the universe and everything. </s>"
  - text: "question: What is 42 context: 42 is the answer to life, the universe and everything. </s>"
  license: mit
  ---
  
  ## T5 for multi-task QA and QG
  This is multi-task [t5-base](https://arxiv.org/abs/1910.10683) model trained for question answering and answer aware question generation tasks. 
  
  For question generation the answer spans are highlighted within the text with special highlight tokens (`<hl>`) and prefixed with 'generate question: '. For QA the input is processed like this `question: question_text context: context_text </s>` 
  
  You can play with the model using the inference API. Here's how you can use it
  
  For QG
  
  `generate question: <hl> 42 <hl> is the answer to life, the universe and everything. </s>`
  
  For QA
  
  `question: What is 42 context: 42 is the answer to life, the universe and everything. </s>`
  
  For more deatils see [this](https://github.com/patil-suraj/question_generation) repo.
  