To start this,
Happy to announce it here first, I’ve been working on Question Generation using  transformers for past two months, and today releasing the first set of experiments here.
Question generation is the task of automatically generating questions from a text paragraph. This project is aimed as an open source study on question generation with pre-trained transformers (specifically seq-2-seq models) using straight-forward end-to-end methods without much complicated pipelines. The goal is to provide simplified data processing and training scripts and easy to use pipelines for inference.
Specifically, I trained T5 model for

answer aware question generation
multitask qa and qq
end-to-end question generation (without answer supervision)

Here’s a sneak peek
qa-qg-ss2048×1780 319 KB
Everything is built using  HuggingFace libraries

Dataset:  nlp library
model and training:  transformers

models hosted on:  model hub

For more details here’s the repo 13
Do share your feedback, specifically regarding the quality of questions, the mistakes and any ethical biases that you observe. Happy to discuss more details here. Cheers !
All models 1 are available on hub with configured inference API. You can search using question-generation tag.
Here’s a colab 9 if anyone wants to play more with it.