ziaulkarim245/Deepseek-R1-Phishing-Detector
The ziaulkarim245/Deepseek-R1-Phishing-Detector is an 8 billion parameter Llama model, fine-tuned from unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit. Developed by ziaulkarim245, this model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is specifically designed and optimized for phishing detection tasks, leveraging its fine-tuned capabilities to identify and classify phishing attempts.
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Model Overview
The ziaulkarim245/Deepseek-R1-Phishing-Detector is an 8 billion parameter Llama model, fine-tuned by ziaulkarim245. It is based on the unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit architecture and was trained with a focus on efficiency, utilizing Unsloth and Huggingface's TRL library to achieve a 2x speedup in the fine-tuning process.
Key Capabilities
- Phishing Detection: The model is specifically fine-tuned for identifying and classifying phishing attempts.
- Efficient Training: Leverages Unsloth for accelerated fine-tuning, making it a practical choice for specialized tasks.
- Llama Architecture: Built upon the robust Llama model family, providing a strong foundation for language understanding.
Good For
- Cybersecurity Applications: Ideal for integrating into systems requiring automated detection of phishing content.
- Specialized NLP Tasks: Suitable for use cases that benefit from a model fine-tuned for a very specific domain like security threat analysis.
- Developers seeking efficient fine-tuning: Demonstrates the effectiveness of Unsloth for faster model adaptation.