This project implements a text generation model using a Recurrent Neural Network (RNN) with PyTorch. The model learns from a provided corpus of text and can generate sentences based on the patterns it has learned.
- Text Preprocessing: Cleans and tokenizes input text, creating a vocabulary for the model.
- RNN Model: A custom implementation of an RNN for generating text.
- Training and Evaluation: Trains the model using backpropagation and evaluates its performance.
- Visualization: Plots training loss over epochs.
- Python 3.x
- PyTorch
- NLTK
- Matplotlib
- NumPy
To install the necessary libraries, run:
pip install torch nltk matplotlib numpy