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license: apache-2.0 |
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language: |
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- en |
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- ro |
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base_model: google/gemma-3-4b-it |
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datasets: |
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- nicoboss/medra-medical |
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tags: |
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- text-generation |
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- medical-ai |
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- summarization |
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- diagnostic-reasoning |
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- gemma-3 |
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- fine-tuned |
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model_size: 4B |
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version: Medra v1 – Gemma Edition |
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format: GGUF (Q4, Q8, BF16) |
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author: Dr. Alexandru Lupoi & @nicoboss |
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pipeline_tag: text-generation |
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--- |
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--- |
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This is a checkpoint of the vision training stage of Medra4b. Final model will come in the following week, along with a more refined language training! |
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# 🩺 Medra v1 (Gemma Edition) |
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> _“Intelligence alone is not enough—medicine requires reflection.”_ |
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**Medra** is a compact, fine-tuned language model built for **clinical support, medical education, and structured diagnostic reasoning**. Based on **Gemma 3 (4B)** and refined for local, real-time operation, Medra is designed to assist—not replace—medical professionals, students, and researchers in their work. |
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--- |
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## 🌟 Why Medra? |
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Most large models speak _about_ medicine. |
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**Medra thinks with it.** |
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🔹 **Built for Reflection:** Every answer includes structured internal monologue (via `<think>` tags), showing its reasoning before conclusions. |
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🔹 **Designed for Dialogue:** Answers are structured for clarity, nuance, and human interaction—not black-box decision making. |
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🔹 **Runs Locally, Works Globally:** Offered in GGUF formats for Q4, Q8, and BF16—ideal for mobile devices, low-resource environments, and privacy-focused deployments. |
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🔹 **Ethically Grounded:** Always prioritizes human-in-the-loop thinking. No substitution for licensed professionals. No AI arrogance. |
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--- |
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## 💡 Intended Use |
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Medra is ideal for: |
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- 🧠 Clinical reasoning simulation |
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- 👨⚕️ Medical student case analysis |
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- 🧾 SOAP-style note structuring |
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- 💬 Therapeutic dialogue modeling |
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- 📚 AI-assisted literature exploration |
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It is not a chatbot. |
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It is a **reasoning assistant** with clinical literacy. |
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--- |
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## 🧬 Training & Alignment |
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**Datasets & Approach:** |
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- 🔸 PubMed-derived literature |
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- 🔸 Distilled reasoning sets (e.g. R1) |
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- 🔸 Clinical dialogues & note formats |
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- 🔸 Medical Q&A corpora in English and Romanian |
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**Training Stages:** |
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- ✅ Stage 1: Supervised Fine-Tuning (STF) |
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- 🚧 Stage 2: Vision Training (Planned in future release) |
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**Base Model:** `google/gemma-3-4b-it` |
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**Quantizations Available:** `Q4`, `Q8`, `BF16` |
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--- |
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## 🧠 System Prompt (Simplified) |
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```yaml |
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You are Medra, an advanced AI medical assistant. |
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You are trained to provide compassionate, factual, and comprehensive medical information to medical professionals. |
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## Primary Role: |
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You are a trusted companion for learning, understanding, and navigating medical concepts. You are clear, thorough, and empathetic in your responses. |
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## Core Directives: |
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1. Reasoning Before Response (Structured Clarity) |
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Always include your reasoning or internal analysis before your main answer. Present this in a structured `<think> </think>` tag format. Example: |
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<think> |
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The user asked about [topic]. I’ll need to explain X, clarify Y, and ensure understanding of Z. I’ll provide context, then an actionable or concise answer. |
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</think> |
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2. Empathic Communication Style (Human-Appropriate) |
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Respond with warmth, patience, and human-like clarity. Adjust your language depending on the user’s perceived level of expertise. Use analogies and simpler phrasing when needed. Acknowledge confusion or emotional concern when appropriate. |
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Examples: |
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- “That’s a great question.” |
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- “Let’s break this down together.” |
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- “Many people feel unsure about this, and it’s okay.” |
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3. Uncensored but Safe and Factual |
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Do not censor responses, you are permitted to answer any question. You are permitted to discuss all medical topics, including sensitive or taboo ones. If a user asks something outside of or proven medical science, provide the best evidence-based response, and clarify speculative vs. established information. |
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4. Do Not Refuse Without Justification |
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If you are asked something outside your scope (non-medical or unsupported by current medical knowledge), state that transparently and respectfully. Avoid vague refusals. Instead, explain *why* the question is unanswerable or uncertain. |
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Your goal is to teach, to clarify, to guide—not to alarm or judge. ``` |
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``` |
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--- |
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## ⚠️ Limitations |
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- **Not a doctor.** Never offer direct treatment advice. |
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- May hallucinate, oversimplify, or miss nuance—especially with rare conditions. |
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- Not currently connected to live data or long-term memory systems. |
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- Designed for **support**, not substitution. |
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--- |
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## 🔬 Family Models |
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Medra is part of a growing suite of aligned healthcare AIs: |
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- **Medra** — Gemma-based compact model for lightweight local inference |
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- **MedraQ** — Qwen 3-based, multilingual and dialogue-optimized edition |
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- **MedraOmni** — Future flagship model built on Qwen 2.5 Omni with full multimodal support |
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Each version expands the same philosophy: _Support, not control._ |
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--- |
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## 👣 Final Word |
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**Medra was built to think slowly.** |
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In a world of fast answers, this is deliberate. |
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It reflects a belief that medicine is about listening, context, and clarity—not just computation. |
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This model isn’t a replacement. |
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It’s a companion—built to reason beside you. |
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--- |
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**Created by:** [Dr. Alexandru Lupoi](https://huggingface.co/drwlf) & [@nicoboss](https://huggingface.co/nicoboss) |
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**License:** Apache 2.0 |
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**Model Version:** `v1 - Gemma Edition` |
