T5 for question-generation

This is t5-small model trained for answer aware question generation task. The answer spans are highlighted within the text with special highlight tokens.

You can play with the model using the inference API, just highlight the answer spans with <hl> tokens and end the text with </s> . For example

<hl> 42 <hl> is the answer to life, the universe and everything. </s>

For more deatils see this repo.

Model in action ?

You'll need to clone the repo .

from pipelines import pipeline
nlp = pipeline("question-generation")
nlp("42 is the answer to life, universe and everything.")
=> [{'answer': '42', 'question': 'What is the answer to life, universe and everything?'}]