文件列表:

code (0, 2021-09-06)
code\bert_model.py (15251, 2021-09-06)
code\data_iterator.py (7122, 2021-09-06)
code\extractor.py (8526, 2021-09-06)
code\gensim_preprocess.py (13185, 2021-09-06)
code\run.py (2904, 2021-09-06)
code\tokenizer.py (10366, 2021-09-06)
code\utils.py (2970, 2021-09-06)
requirements.txt (105, 2021-09-06)

# PacSum This code is for paper [Sentence Centrality Revisited for Unsupervised Summarization](https://arxiv.org/pdf/1906.03508.pdf) ACL 2019 Some codes are borrowed from [pytorch_pretrained_bert](https://github.com/huggingface/pytorch-transformers) and [gensim](https://github.com/RaRe-Technologies/gensim) ------- ### Dependencies Python3.6, pytorch >= 1.0, numpy, gensim, pyrouge ------- ### Data used in the paper: Download https://drive.google.com/open?id=1gNKWkZG4dVr5XrOeQBVicy1fdnpH2d5l ### Bert models fine-tuned using the approach in the paper: Download https://drive.google.com/file/d/1wbMlLmnbD_0j7Qs8YY8cSCh935WKKdsP/view?usp=sharing ### Tuning the hyperparamters and test the performance using TfIdf or BERT representation ``` python run.py --rep tfidf --mode tune --tune_data_file path/to/validation/data --test_data_file path/to/test/data ``` ``` python run.py --rep bert --mode tune --tune_data_file path/to/validation/data --test_data_file path/to/test/data --bert_model_file path/to/model --bert_config_file path/to/config --bert_vocab_file path/to/vocab ```

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