| 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. | |