Sentiment Analysis Project

Overview

This project demonstrates a sentiment analysis application using Generative AI. The application leverages state-of-the-art language models to classify the sentiment of text inputs.

Features

• Sentiment Classification: Classify text as positive or negative.
• User-Friendly Interface: Simple User interface for input and output.
• Customizable Model: Option to fine-tune or replace the pre-trained model for specific use cases.

User Interface

Here’s a screenshot of the user interface for the sentiment analysis application:

Getting Started

Prerequisites

• Python 3.7 or higher
• transformers and datasets libraries
• pip for package management

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/sentiment-analysis-project.git
   cd sentiment-analysis-project

Usage

1. Run the sentiment analysis script:

   ```bash
    main.py.
   

   
   ```bash
   streamlit run app.py
   

Example

Here are a few example sentences you can use to test the sentiment analysis model:

• Positive: "I absolutely love this new feature! It's fantastic and makes my work so much easier."

• Negative: "I am really disappointed with the latest update. It’s full of bugs and doesn’t work as expected."

Model Details

This project uses the Hugging Face Transformers library to leverage pre-trained models for sentiment analysis.

Contributing

Contributions are welcome! Please open an issue or submit a pull request if you have suggestions or improvements.

Acknowledgements

• Hugging Face Transformers
• Sentiment Analysis Dataset