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Implementation of the paper Ranking Sentences for Extractive Summarisation using Reinforcement Learning

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Ranking Sentences for Extractive Summarisation using Reinforcement Learning

This is a re-implementation of the paper Ranking Sentences for Extractive Summarisation using Reinforcement Learning in PyTorch. Find the original code here.

Running the summarizer:

NOTE: to run on CPU, set --gpu_no argument to -1

  • Download model weights from here and save it.
  • Download Glove cache from here and save it.
  • Run:
    cd notebooks
    
    ipython run.py -- --input_folder=<path/to/document_folder> --output_folder=<path/to/summary_folder> --weights=<path/to/saved/weights/> --glove=<path/to/glove/cache> --gpu_no=0 --summary_len=3
    

Training

  • Download dataset (neuralsum.zip) from here.
  • Run preprocess.sh <path/to/neuralsum.zip> to process data.
    • Script for training

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Implementation of the paper Ranking Sentences for Extractive Summarisation using Reinforcement Learning

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