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Madrimed1.2 2B GGUF Optimized GGUF Quantization Tiers for MadriMed 1.2 (2B Medical Mulitmodel)

A 2B-parameter multimodal medical vision-language model, trained for medical image understanding, radiology report assistance, clinical visual question answering, and medical text reasoning.

🩺 HuatuoGPT-3-27B 🏠 GitHub | 📄 Paper

🩺 HuatuoGPT-3-9B 🏠 GitHub | 📄 Paper

Native OpenMed and OpenMedKit vision-language inference for Apple Silicon, including local clinical-document and chart workflows on Mac, iPhone, and iPad.

A clinical reasoning assistant for early-stage Alzheimer's assessment. It joins a 3D MRI + biomarker classifier (Vbai-2.6AD) to a reasoning LLM (Gemma 4 12B) inside a single forward pass — the diagnosis is passed as vectors, not text.

The commands below use the glyph package. Install it from the code repository:

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This repository contains LoRA finetunes of DiffusionGemma (image-conditioned discrete-diffusion LLM) for radiology visual question answering, each paired with an autoregressive Gemma-4 finetune as a controlled baseline. It corresponds to the paper Discrete Diffusion Language Models for Interactive…

A Chinese medical reasoning model fine-tuned from Qwen3.5-4B using a two-stage training pipeline: Supervised Fine-Tuning (SFT) for format alignment, followed by Group Sequence Policy Optimization (GSPO) with an LLM-as-Judge reward function.

Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding

Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding

Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding

📝 arXiv • 📖 IEEE TNNLS • 🤗 Model • 🧩 Codes

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A generalist foundation model for healthcare capable of handling diverse medical data modalities.

![Language: Multilingual]()

![Language: Multilingual]()

Sahal Shaji Mullappilly\, Mohammed Irfan K\, Omair Mohamed, Mohamed Zidan, Fahad Khan, Salman Khan, Rao Muhammad Anwer, and Hisham Cholakkal

Fine-tuned version of Google's MedGemma-4B-it model on the ECGInstruct dataset for automated ECG interpretation.

This model is a fine-tuned version of google/medgemma-1.5-4b-it specialized for mammogram analysis and breast imaging interpretation.

Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding

Large Language and Vision Assistant for bioMedicine (i.e., “LLaVA-Med”) is a large language and vision model trained using a curriculum learning method for adapting LLaVA to the biomedical domain. It is an open-source release intended for research use only to facilitate reproducibility of the…

# MedicalLlama3.2-11B-IT ## Model Description This is a fine-tuned version of meta-llama/Llama-3.2-11B-Vision-Instruct on a multimodal dataset consisting of radiological images and associated medical concepts and captions extracted from the PMC Open Access Subset.

This model is a fine-tuned version of google/medgemma-4b-it adapted for binary mammogram classification on the OMAMA 256×256 dataset. The dataset consists of ~154k mammogram image slices (.npz) with metadata JSONs providing labels (NonCancer, Cancer).

Website    🤖 7B Model    🤖 32B Model    MedEvalKit    Technical Report    Lingshu MCP

Website    🤖 7B Model    🤖 32B Model    MedEvalKit    Technical Report    Lingshu MCP

This repos contains the biomedicine MLLM developed from Qwen2.5-VL-3B-Instruct in our paper: On Domain-Adaptive Post-Training for Multimodal Large Language Models. The correspoding training dataset is in biomed-visual-instructions.

Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

Using llama.cpp release b5868 for quantization.

Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

RaDialog

Model documentation: MedGemma

# fernandoruiz/medgemma-4b-it-Q4_0-GGUF This model was converted to GGUF format from google/medgemma-4b-it using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

The Gradio Web UI allows you to use our examples or upload your images for inference.

Dataset for paper "Teach Multimodal LLMs to Comprehend Electrocardiographic Images".