nhellyercreek/email-phishing-detector-v1

Email Phishing Detector V1

This model is fine-tuned for email phishing detection. It classifies emails as phishing (1) or safe (0).

Model Description

This model is based on distilbert and has been fine-tuned for phishing detection tasks.

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

# Load model and tokenizer
model_name = "nhellyercreek/email-phishing-detector-v1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Example inference
text = "Your email or URL text here"
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
outputs = model(**inputs)
predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)

# Get prediction
predicted_class = predictions.argmax().item()
confidence = predictions[0][predicted_class].item()

print(f"Predicted class: {predicted_class} (phishing=1, safe=0)")
print(f"Confidence: {confidence:.4f}")

Limitations

This model was trained on specific datasets and may not generalize to all types of phishing attempts. Always use additional security measures in production environments.

Citation

If you use this model, please cite:

@misc{nhellyercreek_email_phishing_detector_v1,
  title={Email Phishing Detector V1},
  author={Your Name},
  year={2024},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/nhellyercreek/email-phishing-detector-v1}}
}