Title: Smiley-Based Sentiment Analysis

Description: This is a sentiment analysis model that classifies text input into different emotional categories (positive, negative, neutral, happy, sad, angry, racist, annoying, boring) and returns a corresponding smiley expression. The model is built using the Natural Language Toolkit (NLTK) library in Python and deployed on Gradio for a user-friendly interface.

Instructions: To use the model, simply input any text you wish to analyze into the interface and click the "Analyze" button. The model will classify the text into the appropriate emotional category and display the corresponding smiley expression.

Installation: To install and run the model on your local machine, make sure you have Python 3 installed along with the required libraries listed in the requirements.txt file. You can then run the app.py file and access the interface on your web browser.

Contributing: Contributions to this project are welcome! Feel free to open an issue or submit a pull request.