This project presents a medical question–answering language model built by fine-tuning Google Gemma-2-2B-IT using LoRA (Low-Rank Adaptation) 🧠⚕️. The primary objective is to adapt a general-purpose large language model to the healthcare domain in a parameter-efficient, reproducible, and resource-aware manner.

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Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models.

Gemma-2b-it LLM has been finetuned on a dataset of Python codes, enabling it to proficiently learn Python syntax and assist in debugging tasks, offering valuable guidance to programmers.

Google の Gemma モデルのサンプル集