usage_example.md

# How to use your trained SetFit model

## Load the model
```python
from setfit import SetFitModel

# Load your trained model
model = SetFitModel.from_pretrained('setfit_email_classifier_20250921_101223')
```

## Make predictions
```python
# Predict single email
email_text = "Thank you for your application. We will review it shortly."
prediction = model([email_text])
print(f"Classification: {prediction[0]}")

# Predict multiple emails
emails = [
    "We would like to schedule an interview with you.",
    "Unfortunately, we cannot move forward with your application.",
    "Please submit the following additional documents."
]
predictions = model(emails)
for email, pred in zip(emails, predictions):
    print(f"Email: {email[:50]}...")
    print(f"Classification: {pred}\n")
```

## Model Info
- Base Model: sentence-transformers/all-MiniLM-L6-v2
- Trained: 2025-09-21 10:12:24
- Type: SetFit Email Classifier