Gemma-UA-Cardio consists of two professional large language models specifically designed for the Ukrainian cardiology field. They are based on Google's Gemma and MedGemma models and have undergone two-stage fine-tuning (language adaptation and domain specialization). They can accurately provide cardiovascular medical information and answer clinical questions in Ukrainian, serving as auxiliary tools for medical professionals.

Natural Language ProcessingTransformersOther

MedWhisper Large ITA is a domain-adapted variant based on OpenAI Whisper Large v3 Turbo, specifically optimized for Italian medical speech recognition. This model is fine-tuned using LoRA technology on a carefully selected dataset of Italian outpatient specialty consultation recordings, significantly improving the recognition accuracy of medical terms and clinical expressions.

Audio ProcessingTransformersOther

A large vision-language model designed specifically for the Indian healthcare environment, dedicated to handling tasks related to medical records, including test report parsing, electronic prescription parsing, document classification, and personal identity information extraction.

MultimodalTransformersEnglish

This is a large language model in the medical field fine-tuned using the Unsloth framework based on the MedGemma-4B-IT model. The training speed is doubled, and it focuses on text generation tasks and supports English language processing.

Natural Language ProcessingTransformersEnglish

MedVAL-4B is a fine-tuned language model that can evaluate the medical text output generated by artificial intelligence with reliability close to that of a doctor. It is a self-supervised framework that uses synthetic data to train a large language model for the evaluator, and can assess the factual consistency between the medical output generated by the large language model and the input without doctor labels or reference outputs.

Natural Language ProcessingTransformersMultiple Languages

BioMed-R1-8B is a large language model with 8B parameters specifically optimized for the medical field. It is trained based on Llama-3.1-8B-Instruct and focuses on solving medical reasoning and knowledge question-answering tasks. It performs excellently in biomedical question-answering benchmark tests.

Natural Language ProcessingSafetensorsEnglish

Apollo2-7B-GGUF is a quantized version of FreedomIntelligence/Apollo2-7B, supporting medical large language model applications in multiple languages.

Natural Language ProcessingGgufMultiple Languages

The Lingshu-32B GGUF model is a multimodal large language model suitable for the medical field. It supports multiple medical image modalities and performs excellently in medical Q&A and report generation tasks.

MultimodalTransformers

Lingshu is a SOTA multimodal large language model in the medical field, performing excellently in medical visual Q&A and report generation tasks.

MultimodalTransformers

Lingshu is a multimodal large language model that performs excellently in the medical field. It can effectively process medical image and text information and demonstrates top - notch performance in medical Q&A and report generation tasks.

MultimodalTransformers

MedGemma-27B-Text-IT is a medical-specific large language model based on the Gemma 3 architecture, optimized for medical text processing and offering multiple quantization versions to adapt to different hardware environments.

Natural Language ProcessingTransformers

MedGemma-27B-Text-IT-BF16 is a large language model converted based on the MLX format, focusing on text processing tasks in the medical and health field.

Natural Language ProcessingMlx

MedGemma is a large language model developed by Google for the medical field, focusing on clinical reasoning and medical text generation tasks.

Natural Language ProcessingMlx

MedGemma-27B-Text-IT is a large language model developed by Google, focusing on text generation tasks in the medical field.

Natural Language ProcessingGguf

II-Medical-8B is a next-generation medical large language model developed by Intelligent Internet, specifically designed to enhance AI medical reasoning capabilities, achieving significant breakthroughs in medical Q&A performance.

Natural Language ProcessingTransformers

This model is a large language model for medical Q&A fine-tuned using the GRPO method on the medmcqa-grpo dataset based on Qwen/Qwen3-4B. It is specifically optimized for the scenario of medical multiple-choice questions and has strong medical reasoning ability.

Natural Language ProcessingTransformers

Mol-LLaMA is a large language model for molecular understanding based on Llama-3.1-8B-Instruct, focusing on the comprehension and reasoning of molecular properties in biology, chemistry, and medical fields.

MultimodalTransformersEnglish

A large language model fine-tuned on medical datasets with preliminary reasoning capabilities, capable of performing basic consultation tasks, generating text with superior BLEU scores compared to the original model.

Natural Language ProcessingSafetensors

A family of medical image processing models consisting of six large-scale, generalizable 2D/3D variational autoencoders capable of encoding medical images into compressed latent representations and achieving high-fidelity image reconstruction.

FineMedLM-o1 is a specialized large language model designed for advanced medical reasoning, featuring a multi-step reasoning mechanism that refines and perfects its thought process before delivering a final response.

Natural Language ProcessingTransformersMultiple Languages