DocGemma3-4B-GGUF Open-Source Medical Text Model - Free Deployment to Realize English-Romanian Bilingual Q&A Generation

Docgemma3 4B GGUF

Developed by mradermacher

Quantized version based on drwlf/Medra foundation model, specialized for text generation and Q&A tasks in the medical field, supporting English and Romanian.

Large Language Model Supports Multiple LanguagesOpen Source License:Apache-2.0 #Medical Q&A System #Dermatology AI #Multilingual Medical Summarization

Downloads 455

Release Time : 4/23/2025

Model Overview

This is a quantized large language model for the medical domain, specifically optimized for dermatology-related Q&A capabilities while also supporting tasks like summarization.

Model Features

Medical Domain Optimization

Fine-tuned specifically on PubMedQA and dermatology datasets, excelling in medical Q&A tasks

Multilingual Support

Supports English and Romanian language processing

Efficient Quantization

Offers 12 quantization versions from Q2_K to f16 to meet deployment needs across different hardware conditions

Fast Inference

Q4_K_S and Q4_K_M versions provide fast inference speeds while maintaining quality

Model Capabilities

Medical text generation

Medical Q&A

Dermatology diagnosis assistance

Medical literature summarization

Multilingual medical information processing

Use Cases

Medical Q&A Systems

Dermatology Symptom Consultation

Provides potential dermatological diagnostic suggestions based on patient-described symptoms

Medical Literature Interpretation

Helps medical students and researchers understand complex medical literature content

Medical Document Processing

Medical Report Summarization

Automatically generates concise summaries of lengthy medical reports

🚀 DocGemma3-4B-GGUF

A fine - tuned medical AI model for text generation, question - answering, and summarization, based on the drwlf/Medra base model.

🚀 Quick Start

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi - part files.

✨ Features

Multilingual Support: Supports English (en) and Romanian (ro).
Diverse Datasets: Fine - tuned on multiple medical datasets such as qiaojin/PubMedQA, Mreeb/Dermatology - Question - Answer - Dataset - For - Fine - Tuning, and lavita/MedQuAD.
Multiple Tasks: Capable of text generation, question - answering, summarization, and more in the medical domain.

📦 Installation

No specific installation steps are provided in the original document.

📚 Documentation

About

Static quants of https://huggingface.co/drwlf/Medra. Weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Provided Quants

(sorted by size, not necessarily quality. IQ - quants are often preferable over similar sized non - IQ quants)

Link	Type	Size/GB	Notes
GGUF	Q2_K	1.8
GGUF	Q3_K_S	2.0
GGUF	Q3_K_M	2.2	lower quality
GGUF	Q3_K_L	2.3
GGUF	IQ4_XS	2.4
GGUF	Q4_K_S	2.5	fast, recommended
GGUF	Q4_K_M	2.6	fast, recommended
GGUF	Q5_K_S	2.9
GGUF	Q5_K_M	2.9
GGUF	Q6_K	3.3	very good quality
GGUF	Q8_0	4.2	fast, best quality
GGUF	f16	7.9	16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower - quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

📄 License

This project is licensed under the apache - 2.0 license.

📦 Model Information

Property	Details
Base Model	drwlf/Medra
Datasets	qiaojin/PubMedQA, Mreeb/Dermatology - Question - Answer - Dataset - For - Fine - Tuning, lavita/MedQuAD
Language	en, ro
Library Name	transformers
Quantized By	mradermacher
Tags	text - generation, medical - ai, question - answering, summarization, dermatology, gemma - 3, qlora, unsloth, fine - tuned
License	apache - 2.0

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