# 🧠 TabTransformer Multitask Model for Churn, Tenure, and LTV Prediction
This model is a multitask `TabTransformer` implemented in PyTorch, designed to perform:
- **Binary classification** for customer **churn**
- **Regression** for customer **tenure**
- **Regression** for customer **LTV (Lifetime Value)**
It is saved as a pickle file: `model.pkl` and includes all custom layers (e.g., positional encoding).
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## 🧩 Model Architecture
- Tabular input with:
- `x_num`: Numerical features (projected into latent space)
- `x_cat`: Categorical features (embedded + transformer)
- Transformer-based attention over categorical embeddings
- Multi-head output for multitask predictions:
- `Churn`: Sigmoid activation for binary classification
- `Tenure` and `LTV`: Linear regression heads
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## 🧪 How to Use
### 1. Install Dependencies
```bash
pip install torch pandas
