A Tensorflow implementation of QANet for machine reading comprehension
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Updated
May 30, 2018 - Python
A Tensorflow implementation of QANet for machine reading comprehension
😎 A curated list of the Question Answering (QA)
Tensorflow Implementation of R-Net
multi_task_NLP is a utility toolkit enabling NLP developers to easily train and infer a single model for multiple tasks.
ALBERT model Pretraining and Fine Tuning using TF2.0
Mining individual characters in multiparty dialogue
Survey on Machine Reading Comprehension
An example for applying FusionNet to Natural Language Inference
A PyTorch implementation of Mnemonic Reader for the Machine Comprehension task
Code for Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension
A PyTorch implemention of Match-LSTM, R-NET and M-Reader for Machine Reading Comprehension
R-NET implementation in TensorFlow.
A question answering dataset for machine comprehension of spoken content
Bidirectional Attention Flow for Machine Comprehension implemented in Keras 2
ODSQA: OPEN-DOMAIN SPOKEN QUESTION ANSWERING DATASET
A spoken question answering dataset on SQUAD
FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension
Code & data accompanying the IJCAI 2020 paper "GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension"
Study for Natural Language Processing & Deep Learning Framework
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