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https://github.com/magic282/NeuSum
Code for the ACL 2018 paper "Neural Document Summarization by Jointly Learning to Score and Select Sentences"
https://github.com/magic282/NeuSum
natural-language-processing summarization
Last synced: 3 months ago
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Code for the ACL 2018 paper "Neural Document Summarization by Jointly Learning to Score and Select Sentences"
- Host: GitHub
- URL: https://github.com/magic282/NeuSum
- Owner: magic282
- Archived: true
- Created: 2018-05-10T02:08:35.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2018-10-05T03:24:57.000Z (about 6 years ago)
- Last Synced: 2024-06-14T01:46:40.920Z (5 months ago)
- Topics: natural-language-processing, summarization
- Language: Python
- Size: 32.2 KB
- Stars: 150
- Watchers: 7
- Forks: 32
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- StarryDivineSky - magic282/NeuSum
README
# NeuSum
This repository contains code for the ACL 2018 paper "Neural Document Summarization by Jointly Learning to Score and Select Sentences"
## About this code
**PyTorch version**: This code requires PyTorch v0.3.x.
**Python version**: This code requires Python3.
## How to run
### Prepare the dataset and code
Make a folder for the code and data:
```bash
NEUSUM_HOME=~/workspace/neusum
mkdir -p $NEUSUM_HOME/code
cd $NEUSUM_HOME/code
git clone --recursive https://github.com/magic282/NeuSum.git
```
After preparation, the workspace looks like:
```
neusum
├── code
│ └── NeuSum
│ └── neusum_pt
│ ├── neusum
│ └── PyRouge
└── data
└── cnndm
├── dev
├── glove
├── models
└── train
```
The paper used CNN / Daily Mail dataset.
[About the CNN Daily Mail Dataset](https://gist.github.com/magic282/e4b2ecc91f185939b2688863ae9e41c1)
[About the CNN Daily Mail Dataset 2](https://github.com/magic282/cnndm_acl18)
### Setup the environment
#### Package Requirements:
```
nltk numpy pytorch
```
**Warning**: Older versions of NLTK have a bug in the PorterStemmer. Therefore, a fresh installation or update of NLTK is recommended.
A Docker image is also provided.
#### Docker image
```bash
docker pull magic282/pytorch:0.3.0
```
### Run training
The file `run.sh` is an example. Modify it according to your configuration.
#### Without Docker
```bash
bash $NEUSUM_HOME/code/NeuSum/neusum_pt/run.sh $NEUSUM_HOME/data/cnndm $NEUSUM_HOME/code/NeuSum/neusum_pt
```
#### With Docker
```bash
nvidia-docker run --rm -ti -v $NEUSUM_HOME:/workspace magic282/pytorch:0.3.0
```
Then inside the docker:
```bash
bash code/NeuSum/neusum_pt/run.sh /workspace/data/cnndm /workspace/code/NeuSum/neusum_pt
```