---
license: apache-2.0
datasets:
- blizet/Phishing_Email
language:
- en
base_model:
- NousResearch/Llama-2-7b-chat-hf
pipeline_tag: text-generation
library_name: adapter-transformers
---
# Phishing Detection Model - Fine-Tuned LLaMA-2

This repository contains a fine-tuned version of the **LLaMA-2-7B** model for phishing email detection. The model analyzes emails for phishing attempts, urgency, grammatical errors, and suspicious elements, providing detailed insights.

## Model Details

- **Base Model**: [NousResearch/Llama-2-7b-chat-hf](https://huggingface.co/NousResearch/Llama-2-7b-chat-hf)
- **Fine-Tuned Dataset**: Custom phishing dataset (25,000 samples)
- **Framework**: [Transformers](https://huggingface.co/docs/transformers), [PEFT](https://huggingface.co/docs/peft), [TRL](https://github.com/huggingface/trl)
- **Quantization**: 4-bit (QLoRA)

## Features

1. **Phishing Detection**: Identifies suspicious elements in emails.
2. **Context Analysis**: Evaluates urgency, grammar, sender details, and more.
3. **Detailed Responses**: Outputs structured feedback for 15 parameters.

## Example Usage

```python
from transformers import pipeline

# Load the pipeline
pipe = pipeline("text-generation", model="blizet/Llama-Phishing-Finetune")

# Analyze an email
email_content = "Dear Customer, your account has been flagged. Click here to verify: http://example.com"
result = pipe(f"<s>[INST] Analyze this email for phishing: {email_content} [/INST]")
print(result[0]["generated_text"])