Update README.md

README.md

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-# 🔐 Encrypted Text Classifier – 20 Newsgroups Cipher Challenge
-
-This project is built for the [Kaggle Ciphertext Challenge](https://www.kaggle.com/competitions/20-newsgroups-ciphertext-challenge), where the goal is to classify encrypted text documents into 20 different newsgroup categories.
-
-🎯 Even without decrypting the text, we trained a character-level machine learning model that achieves over **63% accuracy**.
-
----
-
-## 📂 Project Structure
-cipher-classifier/
-├── app.py # Streamlit app
-├── cipher_classifier.pkl # Pickled model + vectorizer
-├── train.csv # Kaggle training data
-├── requirements.txt # Libraries for deployment
-└── README.md
-
-
----
-
-## 🧠 Model Overview
-
-- **Input:** Ciphertext strings (unreadable encrypted text)
-- **Vectorization:** `CountVectorizer` with char-level n-grams (1 to 3)
-- **Model:** Logistic Regression (sklearn)
-- **Accuracy:** ~63% (without decryption)
-
----
-
-
-Example Output
-Input (Ciphertext)	Predicted Label
-['W')(7x1zay7Hb3...	15
-Tx4a8M\HNsyp;HM...	8
-
-
-
-📦 Deployment
-This app is designed to run on:
-
-🟢 Hugging Face Spaces
-
-🟢 Streamlit Cloud
-
-🔵 GitHub
-
-
-📌 Kaggle Link
-You can download the dataset from the official competition:
-👉 Kaggle – 20 Newsgroups Ciphertext Challenge
-
+
+---
+title: Encrypted Text Classifier
+emoji: 🔐
+colorFrom: gray
+colorTo: blue
+sdk: streamlit
+sdk_version: "1.32.2"
+app_file: app.py
+pinned: false
+---
+
+
+# 🔐 Encrypted Text Classifier – 20 Newsgroups Cipher Challenge
+
+This project is built for the [Kaggle Ciphertext Challenge](https://www.kaggle.com/competitions/20-newsgroups-ciphertext-challenge), where the goal is to classify encrypted text documents into 20 different newsgroup categories.
+
+🎯 Even without decrypting the text, we trained a character-level machine learning model that achieves over **63% accuracy**.
+
+---
+
+## 📂 Project Structure
+cipher-classifier/
+├── app.py # Streamlit app
+├── cipher_classifier.pkl # Pickled model + vectorizer
+├── train.csv # Kaggle training data
+├── requirements.txt # Libraries for deployment
+└── README.md
+
+
+---
+
+## 🧠 Model Overview
+
+- **Input:** Ciphertext strings (unreadable encrypted text)
+- **Vectorization:** `CountVectorizer` with char-level n-grams (1 to 3)
+- **Model:** Logistic Regression (sklearn)
+- **Accuracy:** ~63% (without decryption)
+
+---
+
+
+Example Output
+Input (Ciphertext)	Predicted Label
+['W')(7x1zay7Hb3...	15
+Tx4a8M\HNsyp;HM...	8
+
+
+
+📦 Deployment
+This app is designed to run on:
+
+🟢 Hugging Face Spaces
+
+🟢 Streamlit Cloud
+
+🔵 GitHub
+
+
+📌 Kaggle Link
+You can download the dataset from the official competition:
+👉 Kaggle – 20 Newsgroups Ciphertext Challenge
+