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resources for the paper 'Get To The Point: Summarization with Pointer-Generator Networks' with python3.x. overview on the posthttp://www.abigailsee.com/2017/04/16/taming-rnns-for-better-summarization.html or
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Organized resources forGet To The Point: Summarization with Pointer-Generator Networks with python3.x
参考https://github.com/abisee/cnn-dailymail
raw corpus
command for data preprocessing
python data/make_datafiles.py /path/to/unzipped/cnn_stories.tgz /path/to/unzipped/dailymail_stories.tgzgenerate data for model
参考https://github.com/abisee/pointer-generator
python run_summarization.py --mode=train --data_path=/path/to/chunked/train_* --vocab_path=/path/to/vocab --log_root=/path/to/a/log/directory --exp_name=myexperimentpython run_summarization.py --mode=eval --data_path=/path/to/chunked/val_* --vocab_path=/path/to/vocab --log_root=/path/to/a/log/directory --exp_name=myexperimentpython run_summarization.py --mode=decode --data_path=/path/to/chunked/val_* --vocab_path=/path/to/vocab --log_root=/path/to/a/log/directory --exp_name=myexperimentAbout
resources for the paper 'Get To The Point: Summarization with Pointer-Generator Networks' with python3.x. overview on the posthttp://www.abigailsee.com/2017/04/16/taming-rnns-for-better-summarization.html or
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