Harmj0y/qwen3-4b-instruct-phishing-classifier
Harmj0y/qwen3-4b-instruct-phishing-classifier is a 4 billion parameter Qwen3-based instruction-tuned model developed by Harmj0y, fine-tuned for phishing classification tasks. This model leverages Unsloth and Huggingface's TRL library for accelerated training, making it efficient for specialized text classification. With a 40960 token context length, it is designed for effective analysis and identification of phishing attempts.
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Overview
Harmj0y/qwen3-4b-instruct-phishing-classifier is a 4 billion parameter Qwen3-based instruction-tuned model developed by Harmj0y. It was specifically fine-tuned for phishing classification, building upon the unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit base model. The training process utilized Unsloth and Huggingface's TRL library, enabling a 2x faster fine-tuning compared to standard methods.
Key Capabilities
- Phishing Classification: The primary capability of this model is to identify and classify phishing attempts within text data.
- Efficient Fine-tuning: Benefits from accelerated training via Unsloth, making it a resource-efficient option for specialized tasks.
- Qwen3 Architecture: Built on the Qwen3 model family, providing a robust foundation for language understanding.
Good For
- Security Applications: Ideal for integrating into systems that require automated detection of phishing content.
- Content Moderation: Can be used to filter out malicious or deceptive text in various platforms.
- Research and Development: Provides a specialized model for further experimentation and development in text-based threat detection.