Question Generation using hugstransformers
An open-source study on neural question generation using transformers, providing simplified training and inference pipelines.
What is Question Generation using hugstransformers?
Question Generation is an open-source project that uses transformer models to automatically generate questions from text passages. It implements various approaches like answer-aware question generation, multi-task QA-QG, and end-to-end question generation to simplify the creation of questions from given content. The project provides easy-to-use pipelines and training scripts to make neural question generation more accessible and practical.
NLP researchers, machine learning engineers, and developers working on educational technology, content automation, or quiz generation who need to automatically create questions from textual data.
It offers a simplified, end-to-end approach to question generation using state-of-the-art transformers, with pre-trained models and reproducible scripts that reduce the complexity typically associated with QG systems. The multi-task model consolidates answer extraction, QG, and QA into a single pipeline, streamlining deployment.
Overview
Neural question generation using transformers
Use Cases
Best For
- Automatically generating quiz questions from educational content
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