Play-Generator

Overview

The Play Generator is a text generation model built using TensorFlow and Keras, trained on the works of William Shakespeare. This model utilizes a character-based approach to generate text that mimics the style of Shakespearean plays.

Features

• Downloads and preprocesses Shakespeare's text data.
• Encodes characters into integers for model training.
• Creates training examples and targets for the model.
• Builds a recurrent neural network (RNN) using LSTM layers.
• Implements a custom loss function for training.
• Saves model checkpoints during training.
• Generates text based on a user-provided starting string.

Requirements

• Python 3.x
• TensorFlow
• Keras
• NumPy
• Other dependencies as specified in the code

Training the Model

• The model is trained for 50 epochs on the Shakespeare dataset. You can adjust the number of epochs in the training section of the notebook.

Generating Text

• After training, you can generate text by providing a starting string. The model will produce a continuation of the text in the style of Shakespeare.

Working

inp = input("Type a starting string: ")
print(generate_text(model, inp))

Checkpoints

• The model saves checkpoints during training, allowing you to resume training or load a pre-trained model.

Contributing

• Contributions are welcome! Please feel free to submit a pull request or open an issue for any suggestions or improvements.

Acknowledgments

• Inspired by the works of William Shakespeare.
• Utilizes TensorFlow and Keras for deep learning.