AI Poetic Text Generator Using RNNs

This repository contains a Python implementation of an AI Poetic Text Generator using Recurrent Neural Networks (RNNs). The generator utilizes Long Short-Term Memory (LSTM) networks, a type of RNN suitable for sequential data like text, to produce expressive and poetic text reminiscent of human creativity.

Dataset

The model is trained on a subset of Shakespearean text obtained from the TensorFlow dataset. The dataset has been preprocessed to extract a portion of the text suitable for training the generator.

Dependencies

• TensorFlow 2.x
• NumPy

Installation

1. Clone the repository:

   gh repo clone chmuhammadasim/AI-Poetic-Text-Generator-Using-RNNs

Usage

1. Run the Model.py script to train the model and generate poetic text.

   python Model.py

2. Adjust the hyperparameters in the script to customize the training process and the generated text:
   • SEQ_LENGTH: Length of input sequences for the LSTM model.
   • STEP_SIZE: Step size for extracting sequences from the text data.
   • epochs: Number of training epochs for the model.
   • temperature: Temperature parameter for controlling the creativity of the generated text.

Generated Text

The generated poetic text will be displayed in the console, with variations based on the temperature parameter.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• This project is inspired by the work of creative text generation using neural networks.
• The TensorFlow team for providing the Shakespeare dataset and valuable resources for deep learning.

Disclaimer

This project is for educational and research purposes only. The generated text may not always be grammatically correct or coherent. Use discretion when interpreting the output.