Irannas/Masked_Email_Classification

1---2title: Email Classifier Project3emoji: 📉4colorFrom: blue5colorTo: purple6sdk: docker7pinned: false8---9 10Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference11# 📧 Email Classifier with PII Masking12 13An intelligent tool that classifies emails into categories like Work, Personal, Spam, etc., while protecting sensitive information through PII (Personally Identifiable Information) masking.14 15**🔗 Live Demo:** [🌐 Try it on Hugging Face Spaces](https://huggingface.co/spaces/Irannas/Masked_Email_Classification)  16**📁 GitHub Repo:** [GitHub Repository](https://github.com/IrannaSS/Masked_Email_Classification)17 18---19 20## 🚀 Features21 22- 🔐 **PII Masking**: Automatically detects and masks sensitive information such as names, phone numbers, email addresses, and more.23- 🧠 **Email Classification**: Uses a fine-tuned transformer model to classify email content into predefined categories.24- ⚡ **Real-Time Inference**: Deployed with Streamlit for fast and user-friendly web interaction.25- 📂 **Batch Upload Support**: Upload multiple email files (TXT format) and process them in one go.26 27---28 29## 🧰 Tech Stack30 31- **Language:** Python 3.10+32- **NLP Libraries:** Transformers (Hugging Face), spaCy, scikit-learn33- **Model:** DistilBERT / Custom Transformer34- **Deployment:** Streamlit, Hugging Face Spaces35- **PII Detection:** Regex + spaCy NER36 37---38 39## 📁 Project Structure40 41Email_Classifier_Project/42├── app/                      # Streamlit App43│   └── app.py44├── model/                    # Trained model and tokenizer45│   └── classifier_model/46├── data/                     # Sample email data47│   └── sample_emails/48├── utils/                    # Helper functions (PII masking, preprocessing, etc.)49│   └── preprocess.py50├── requirements.txt51├── Dockerfile               52└── README.md53 54 55 56---57 58## ⚙️ Installation59 60Clone the repository and install the requirements:61 62```bash63git clone https://github.com/IrannaSS/Masked_Email_Classification64cd your-repo-name65pip install -r requirements.txt66 67 68Run the Streamlit app locally:69 70        streamlit run app/app.py71 72 73