README.md

---
tags:
- text-generation-inference
- transformers
- llama
- trl
license: apache-2.0
language:
- en
base_model:
- meta-llama/Llama-3.2-3B-Instruct
---
# 🛡️ PII-Shield
> *Your Intelligent Guardian for Personal Data Protection*


[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Made with ❤️](https://img.shields.io/badge/Made%20with%20%E2%9D%A4%EF%B8%8F%20by-Data%20Privacy%20Team-red.svg)](https://huggingface.co/mlninad/PII-Shield)

---

## 🌟 What is PII-Shield?

PII-Shield is your cutting-edge solution for protecting sensitive information in text data. Powered by advanced transformer architecture, it's your first line of defense against unintended PII exposure.

---

## 🎯 Core Capabilities

### 🔍 Smart Detection
```bash
"Regular text with [email protected]" → "Regular text with [EMAIL_1]"
```

### 🎭 Intelligent Masking
```bash
"Call John at (555) 123-4567" → "Call [PERSON_1] at [PHONE_1]"
```

### 📊 Structured Mapping
```bash
Original → Masked → JSON Mapping
```

---

## 🚀 Model Architecture

### 🧠 Two-Stage Intelligence


![image/png](https://cdn-uploads.huggingface.co/production/uploads/6434f4fe7b8247480110bf44/vSSoxcNxuIoAN-mI3aJvt.png)

---

## ⚡ Supported PII Categories

| Category | Icon | Example |
|----------|------|---------|
| Names | 👤 | John Smith |
| Emails | 📧 | [email protected] |
| Phones | 📱 | (555) 123-4567 |
| Addresses | 🏠 | 123 Privacy St |
| SSN | 🔢 | XXX-XX-XXXX |
| Credit Cards | 💳 | XXXX-XXXX-XXXX |
| DOB | 📅 | MM/DD/YYYY |
| IPs | 🌐 | 192.168.1.1 |

---

## 💫 How It Works

### 🎯 Detection Phase
```python
def detect_pii(text: str) -> List[Entity]:
    """
    🔍 Intelligent PII detection
    Returns list of identified entities
    """
    pass
```

### 🎭 Masking Phase
```python
def mask_pii(text: str, entities: List[Entity]) -> Dict:
    """
    🛡️ Smart PII masking
    Returns masked text and mapping
    """
    pass
```

---

## 🎮 Input/Output

### 📥 Input Format
```json
{
    "text": "Your sensitive text here",
    "options": {
        "mask_format": "[TYPE_INDEX]",
        "return_mapping": true
    }
}
```

### 📤 Output Format
```json
{
    "masked_text": "Your [TYPE_1] text here",
    "pii_mapping": [
        {
            "label": "TYPE",
            "value": "sensitive",
            "index": 1
        }
    ]
}
```

---

## 🚦 Performance Stats

| Metric | Score | Trend |
|--------|-------|-------|
| Precision | 98.5% | ⬆️ |
| Recall | 97.8% | ⬆️ |
| Speed | 2ms/req | ⬇️ |
| Accuracy | 99.1% | ➡️ |

---

## 🛠️ Technical Requirements

- 🖥️ CUDA-capable GPU
- 💾 8GB+ VRAM
- 🐍 Python 3.8+
- 🔧 PyTorch 2.0+

---

## 🔒 Security First

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6434f4fe7b8247480110bf44/z0zmLQATLKRNHFoA4nOZK.png)

## 🎯 Best Practices

1. 🔐 Never store raw PII
2. 💾 Process in-memory only
3. 🧹 Clear cache regularly
4. 📝 Enable access logging
5. 🔄 Regular updates

---

## ⚠️ Known Limitations

- 📏 Max 2048 tokens
- 🗣️ English-primary
- 💡 Domain adaptation needed
- 💾 GPU memory bound

---

## 📜 License

Apache License 2.0 • Made with ❤️ for Privacy

---

## 🤝 Support & Community

- 💬 [LinkedIn](https://www.linkedin.com/in/workwithninad)
- 📧 [Email Support](mailto:[email protected])