OmarioVICC/email-classifier: A Specialized Email Classification Model

This model, developed by OmarioVICC, is a 1 billion parameter language model fine-tuned from the unsloth/gemma-3-1b-it-unsloth-bnb-4bit base. It is specifically designed and optimized for email classification tasks.

Key Capabilities

• Efficient Email Categorization: Specialized in understanding and classifying email content.
• Accelerated Training: Utilizes Unsloth and Huggingface's TRL library, enabling 2x faster training compared to standard methods.
• Gemma 3-1B-IT Base: Built upon a robust instruction-tuned Gemma architecture, providing a strong foundation for language understanding.

Good For

• Automated Email Sorting: Ideal for systems that need to automatically sort incoming emails into predefined categories.
• Spam Detection: Can be adapted for identifying and filtering unwanted emails.
• Customer Support Triage: Useful for routing customer inquiries to the appropriate department based on email content.

This model is released under the Apache-2.0 license, offering flexibility for various applications.