Update README.md

README.md

@@ -2,29 +2,42 @@
 
 This project is a web-based application that classifies waste materials from user-uploaded images. It identifies the type of waste (e.g., cardboard, glass, metal) and provides information on how to properly dispose of it.
 
-## Features
+## 🚀 Live Demo
 
-*   **Image-based classification:** Upload an image of a waste item to have it automatically classified.
-*   **Multiple waste categories:** The application can identify a variety of waste materials.
-*   **Disposal information:** After classification, the app provides guidance on how to dispose of the identified waste material.
-*   **Web interface:** A user-friendly web interface built with Gradio makes the application easy to use.
+Try the application live on Hugging Face Spaces!
 
-## How it works
+**➡️ [Waste Classification Demo](https://huggingface.co/spaces/HMWCS/Gemma3n-challenge-demo)**
 
-The application uses a pre-trained Vision Transformer (ViT) model to perform the image classification. The model has been fine-tuned on a dataset of waste images to accurately identify different materials. The disposal information is retrieved from a knowledge base within the application.
+---
 
-## Getting Started
+## ✨ Features
+
+* **Image-based classification:** Upload an image of a waste item to have it automatically classified.
+* **Multiple waste categories:** The application can identify a variety of waste materials.
+* **Disposal information:** After classification, the app provides guidance on how to dispose of the identified waste material.
+* **Web interface:** A user-friendly web interface built with Gradio makes the application easy to use.
+
+---
+
+## 💡 How it works
+
+The application uses a pre-trained Gemma3n(E2B) model to perform the image classification. The model has been fine-tuned on a dataset of waste images to accurately identify different materials. The disposal information is retrieved from a knowledge base within the application.
+
+---
+
+## 🛠️ Getting Started
 
 ### Prerequisites
 
-*   Python 3.7+
-*   Pip
+* Python 3.9+
+* Pip
+* Cuda (optional)
 
 ### Installation
 
 1.  Clone the repository:
     ```bash
-    git clone https://github.com/yichuan-huang/gemma3n-challenge
+    git clone [https://github.com/yichuan-huang/gemma3n-challenge](https://github.com/yichuan-huang/gemma3n-challenge)
     ```
 2.  Navigate to the project directory:
     ```bash
@@ -40,16 +53,4 @@ The application uses a pre-trained Vision Transformer (ViT) model to perform the
 To start the application, run the following command:
 
 ```bash
-python app.py
-```
-
-This will launch a Gradio web server. You can access the application by opening the provided URL in your web browser.
-
-## Project Structure
-
-*   `app.py`: The main application file, containing the Gradio interface and the classification logic.
-*   `classifier.py`:  Handles the image classification using the pre-trained model.
-*   `config.py`: Contains configuration settings for the application, such as the model name and labels.
-*   `knowledge_base.py`:  A simple knowledge base containing disposal information for different waste materials.
-*   `requirements.txt`: A list of the Python dependencies required to run the application.
-*   `test_images/`: A directory containing sample images for testing the application.
+python app.py