SparkJiao/SLQA
An Unofficial Pytorch Implementation of Multi-Granularity Hierarchical Attention Fusion Networks for Reading Comprehension and Question Answering
This project provides an unofficial implementation of a deep learning model designed for advanced reading comprehension and question answering. It takes a body of text (like a document or article) and a question about that text, then attempts to extract the most relevant answer from the text. This is primarily for researchers and developers working on natural language processing (NLP) models for question answering systems.
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Use this if you are an NLP researcher or developer experimenting with or benchmarking multi-granularity hierarchical attention fusion networks for extractive question answering.
Not ideal if you need a production-ready, highly accurate, out-of-the-box question answering system with top-tier performance on standard datasets like SQuAD.
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75
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12
Language
Python
License
Apache-2.0
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Last pushed
May 13, 2021
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