Rin29/MedVault-4

This model is a Phi-4 Large Language Model (LLM) that has been fine-tuned for medical reasoning tasks. It leverages the architecture of the Phi-4 model and has been specifically adapted to understand and process medical information, answer medical questions, and potentially assist in clinical decision-making support (for research purposes only).

The fine-tuning process was carried out using Unsloth AI, a library designed for efficient and accessible LLM fine-tuning. Unsloth AI simplifies the process of adapting powerful models like Phi-4 for specific downstream tasks, making it easier to create specialized LLMs like this medical reasoning model.

Key Features:

• Based on the Phi-4 architecture, known for its efficiency and performance.
• Fine-tuned on a medical reasoning dataset to enhance its capabilities in the medical domain.
• Trained using Unsloth AI for optimized fine-tuning.

Dataset

The model was fine-tuned on FreedomIntelligence/Medical-R1-Distill-Data dataset.

• Dataset Description: SFT dataset distilled from Deepseek-R1 (Full Power Version), based on medical verifiable problems from HuatuoGPT-o1.
• Source: FreedomIntelligence/Medical-R1-Distill-Data
• Dataset Size: 22k rows.

Important Note on Dataset Bias: It's important to acknowledge that medical datasets can contain biases that reflect real-world healthcare disparities. This model may inherit and amplify such biases. Users should be aware of this limitation and interpret the model's outputs with caution.

Intended Use

This model is intended for research purposes only. Potential use cases include:

• Medical Education: Assisting medical students and professionals in learning and reviewing medical concepts.
• Clinical Decision Support Research: Exploring the potential of LLMs in providing support for clinical decision-making (always under the supervision of qualified professionals and not for direct clinical use).
• Medical Information Retrieval: Improving the accuracy and relevance of medical information retrieval systems.
• Medical Question Answering: Developing systems that can answer complex medical questions.

Disclaimer: This model is not intended for clinical use and should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always consult with a qualified healthcare provider for any health concerns or before making any decisions related to your health or treatment.