alpha-ai/Medical-Diagnosis-COT-Gemma3-270M

Medical-Diagnosis-COT-Gemma3-270M: Chain-of-Thought for Medical Reasoning

This model, developed by Alpha AI, is a fine-tuned version of Google's Gemma 3 (270M parameters) specifically designed for medical question answering. Its core differentiator is the explicit generation of a chain-of-thought (CoT), enclosed within <think>...</think> tags, before providing a final answer. This feature is particularly valuable for understanding the model's reasoning process.

Key Capabilities

• Explicit Chain-of-Thought: Generates detailed reasoning steps, enhancing transparency and interpretability in medical problem-solving.
• Medical Question Answering: Fine-tuned on a dataset of medical reasoning questions, including FreedomIntelligence/medical-o1-reasoning-SFT and human-annotated data.
• Gemma 3 Architecture: Leverages the Gemma 3 base model, supporting a context window of up to 128K tokens.
• Research-Oriented: Ideal for studying CoT interpretability, prompt engineering, and dataset curation in the medical domain.

Good For

• Research on Medical Reasoning: Investigating how LLMs arrive at medical conclusions.
• Internal Tooling: Developing assistants where human review of intermediate reasoning steps is crucial.
• Interpretability Studies: Analyzing the model's thought process for medical diagnoses and treatment planning.

Important Note: This model is a research system and not intended for clinical use or diagnosis/treatment decisions. It may hallucinate facts and does not guarantee adherence to medical guidelines. Users should be aware of potential biases from synthetic training data.