Medra4b LORA

🚀 Medra: Your Compact Medical Reasoning Partner

Medra is a purpose - built, lightweight medical language model. It serves as a cognitive tool for students, clinicians, and researchers, helping to explore the complexity of medical care with AI without oversimplification.

🚀 Quick Start

Medra is a compact model that can run on consumer hardware. You can use it via local inference engines like Ollama, LM Studio, KoboldCpp, etc., to support various medical - related tasks.

✨ Features

Lightweight Clinical Reasoning Core

Medra is fine - tuned to handle structured medical queries, diagnostic steps, SOAP formatting, and clinical questioning strategies.

Local and Mobile Friendly

Available in GGUF (Q4, Q8, BF16) formats, Medra can run on local devices without the need for an API.

Data & Alignment

It is trained on medical content such as PubMed - derived literature, reasoning datasets, clinical notes, and prompt structures based on real - world physician interactions.

High Interpretability

Designed for transparency and reflection, Medra works best when treated as a partner rather than a prophet.

Designed for Ethical Integration

Built with the goal of remaining aligned, cautious, and useful in human - in - the - loop medical settings.

📦 Installation

There is no specific installation content provided in the original README. So, this section is skipped.

💻 Usage Examples

There is no code example provided in the original README. So, this section is skipped.

📚 Documentation

Overview

Medra, built on top of Gemma 3, is the first step in a long - term project to create deployable, interpretable, and ethically aligned AI support systems for medicine. It is not a chatbot but a cognitive tool.

Purpose & Philosophy

Medra fills a gap in the current AI landscape by providing structured, medically relevant reasoning. It can run locally, offline, and in real - time. It aims to offer interpretable outputs, support differential diagnosis, assist medical students, and refine reasoning in clinical contexts.

Intended Use

• Medical education and exam - style reasoning
• Case - based learning simulation
• AI health assistant prototyping
• Dialogue modeling in therapeutic or diagnostic contexts
• As a tool for thinking alongside human judgment

Limitations

• Medra is not a licensed medical professional and should not be used for real - world diagnosis, treatment planning, or patient interaction without human oversight.
• The model may hallucinate, oversimplify, or present outdated medical knowledge in edge cases.
• It lacks long - term memory, real - world clinical data access, and the authority to guide care.
• It is a prototype, not a finished replacement for expertise.

The Medra Family

• Medra: Gemma - based compact model for lightweight local inference
• MedraQ: Qwen 3 - based, multilingual and adaptive version
• MedraOmni: Future flagship model built on Qwen 2.5 Omni with full multimodal support

Final Note

Medra is built with the purpose of making intelligent care more accessible, transparent, and aligned with human needs.

🔧 Technical Details

• Base model: Gemma 3
• Fine - tuning stages: Instructional tuning (STF); RLHF planned in upcoming release
• Data domains: Medical Q&A, differential diagnosis formats, clinical conversation datasets, PubMed - derived material
• Supported inference engines: Ollama, LM Studio, KoboldCpp, GGML - compatible platforms
• Quantization formats: Q4, Q8, BF16

📄 License

The model is released under the Apache 2.0 license.

Model Information

This gemma3 model was trained 2x faster with Unsloth and Huggingface's TRL library.