Update README.md

README.md

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----
-title: "📧 Spam Message Classifier"
-emoji: ✉️
-colorFrom: red
-colorTo: pink
-sdk: gradio
-sdk_version: "4.12.0"
-app_file: app.py
-pinned: true
----
-
-# ✉️ Spam Message Classifier
-
-Detect spam messages with 90%+ accuracy using machine learning. Built with Logistic Regression, TF-IDF, and deployed via Gradio.
-
-## 🚀 How It Works
-1. Paste any SMS/email message
-2. Get instant classification (Spam/Ham)
-3. See confidence score and detected keywords
-4. Try example messages below the input box
-
-## 🔍 Features
-- Keyword detection (free, win, urgent, etc.)
-- Confidence percentage
-- Mobile-friendly interface
-- Fast predictions (<1sec)
-
-## 🛠️ Technical Stack
-- Python 3.10
-- Scikit-learn
-- NLTK for text processing
-- Gradio for UI
-- Hugging Face Spaces for deployment
-
-## 🔗 Live Demo
-👉 [Try the live app](https://huggingface.co/spaces/Ahmedhassan54/Spam-Ham-Classification)
-
-## 📦 Local Setup
-```bash
-git clone https://huggingface.co/spaces/your-username/spam-classifier
-cd spam-classifier
-pip install -r requirements.txt
+---
+title: 📧 Spam Message Classifier
+emoji: ✉️
+colorFrom: red
+colorTo: pink
+sdk: gradio
+sdk_version: 5.34.2
+app_file: app.py
+pinned: true
+---
+
+# ✉️ Spam Message Classifier
+
+Detect spam messages with 90%+ accuracy using machine learning. Built with Logistic Regression, TF-IDF, and deployed via Gradio.
+
+## 🚀 How It Works
+1. Paste any SMS/email message
+2. Get instant classification (Spam/Ham)
+3. See confidence score and detected keywords
+4. Try example messages below the input box
+
+## 🔍 Features
+- Keyword detection (free, win, urgent, etc.)
+- Confidence percentage
+- Mobile-friendly interface
+- Fast predictions (<1sec)
+
+## 🛠️ Technical Stack
+- Python 3.10
+- Scikit-learn
+- NLTK for text processing
+- Gradio for UI
+- Hugging Face Spaces for deployment
+
+## 🔗 Live Demo
+👉 [Try the live app](https://huggingface.co/spaces/Ahmedhassan54/Spam-Ham-Classification)
+
+## 📦 Local Setup
+```bash
+git clone https://huggingface.co/spaces/your-username/spam-classifier
+cd spam-classifier
+pip install -r requirements.txt
 python app.py