Compendium

Introduction

Compendium is a seq2seq abstractive text symmetrization model based on GRU encoder decoder with attention mechanism.

Base Info

Files and there uses are listed below

Data -> Folder used for train and test data storage
helper -> Contains helper functions used in model.ipynb.
brain -> Contains trained RNN Model.
Data Clean.ipnb -> Ipython Notbook for cleaning and splitting data into train, val and test.
model.ipynb -> Ipython Notebook for training andd testing model.
requirement -> txt file containg required lib

Requirements

Python : 3.X

Pip

Installation

Steps for installation?

1. Download venv
   pip3 install virtualenv
2. Clone
   git clone https://github.com/soni-ratnesh/compendium.git
3. Change directory
   cd compendium
4. Create and activate virtual environment
   pip3 venv env
. env\bin\activate
5. Install required library
   pip3 install -r requirements.txt
6. Install spacy english model
   python3 -m spacy download en
   
7. Copy brain file
   cp <your barin file path> ./application/model/brain
   
8. Run Flask server
   bash start.sh

Result

The testing accuracy and loss are,

Test Loss     :  2.23
Test PPE      :  10.87

Need trained model?

We do provide trained model, just let us know. you can get trained model from here . Save the provideed file in brain dir to load and run.

Contribution

Pull requests are welcome. If have an idea please let me know through an issue. For contribution please raise pull requests by,

1. Clone Repo

   git clone https://github.com/soni-ratnesh/compendium.git

2. Install Dependencies

   pip3 install requirements.txt

3. Verify your changes

4. Submit Pull Request

Short for time??

Feel free to raise an issue to correct errors or contribute content without a pull request.