README.md

---
title: Instant Sentiment Analysis
emoji: 🤗
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.29.0
app_file: app.py
pinned: false
license: apache-2.0
---

# Instant Sentiment Analysis with `bertweet-base`

This Hugging Face Space hosts an interactive demo for a sentiment analysis pipeline. It uses the pre-trained [`finiteautomata/bertweet-base-sentiment-analysis`](https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis) model, which is fine-tuned on tweets, making it highly effective at understanding informal language, slang, and social media content.

This project serves as a foundational example of how to wrap a powerful, pre-trained model from the Hugging Face Hub into an interactive web application using **Gradio**.

## 🚀 How to Use the Demo

1.  **Enter Text:** Type or paste any text into the input box.
2.  **See the Results:** The model will instantly analyze the text and display the sentiment scores for "Positive" (POS), "Negative" (NEG), and "Neutral" (NEU).
3.  **Try the Examples:** Click on one of the provided examples to see how the model performs on different types of sentences.

## 🤖 Model Details

The underlying model, `bertweet-base-sentiment-analysis`, is a RoBERTa-base model trained on a massive corpus of English tweets. This specific training makes it robust for analyzing sentiment in noisy, real-world text commonly found on the internet.

-   **Labels:**
    -   `POS`: Positive sentiment
    -   `NEU`: Neutral sentiment
    -   `NEG`: Negative sentiment

## 🛠️ Project Purpose & Portfolio Value

This project was developed to showcase several key skills in the modern AI landscape:

-   **Leveraging Pre-trained Models:** Demonstrates the ability to identify and utilize state-of-the-art models from the Hugging Face Hub for a specific task.
-   **GPU-Accelerated Inference:** The backend automatically uses a GPU if available, showcasing an understanding of hardware acceleration for ML models.
-   **Interactive Application Development:** Uses Gradio to build a clean, user-friendly interface, a critical skill for making AI models accessible.
-   **Reproducibility:** The project is fully reproducible thanks to the `requirements.txt` file, a best practice for collaborative and professional development.

This Space is a tangible demonstration of applying advanced NLP tools to create a practical, real-world application.