Next word predictor using Long Short Term Memory(LSTM).

This Dataset is from Kaggle:-

Overview

The LSTM Next-Word Predictor is a deep learning-based application designed to predict the next word based on user input (a word or sentence). Trained on a predefined dataset, the model leverages LSTM (Long Short-Term Memory) networks for sequence learning, ensuring contextually accurate and relevant predictions.

Features

• Accepts user input (word or sentence) to generate the next word suggestion.
• Built with LSTM architecture optimized for text sequence modeling.
• Trained on a predefined dataset for reliable predictions.

How It Works

1. The user inputs a word or sentence.
2. The model processes the input and predicts the most likely next word.
3. The output is displayed as a word suggestion for the user.

Installation and Setup

1. Clone this repository:

   git clone https://github.com/Vruddhi18/LSTM_Next-word-predictor.git

2. Install dependencies

   pip install -r requirements.txt

3. Run the predictor

   streamlit run app.py

Output

1736254557348703.mov