This repo consists of an implementation of Book Script Generation code.

The dataset used was from one of the popular Packt book Mastering PostgreSQL by Hans-Jürgen Schönig. We used almost 100 pages from the book and removed any figures, tables and SQL code.

• This code is checked on using native Python 3 with anaconda
• Create a conda virtual environment and install relevant packages using requirements.txt file

pip install requirements.txt

To run the code just execute

python main.py

As the dataset is not large, code can be executed on CPU itself.

Code is pretty self explanatory. There are mainly four files in implementation:

• main.py -- It contains three parts:
  • main function: To call the relevant functions
  • train: trains the model
• parameters.py -- Contains all the parameter declarations
• Model.py -- Contains the Model Class.
• utils.py -- Helper functions.

Note that the model was not tuned for best hyperparameters. Feel free to play around.