A lightweight medical fine-tuned model based on Arcee's AFM-4.5B, optimized using a three-stage training method (SFT→DPO→GRPO-CoT), specifically designed for medical education and research scenarios.

Natural Language ProcessingTransformersMultiple Languages

MedScholar-1.5B is a compact medical Q&A model based on the Qwen2.5-1.5B-Instruct architecture, fine-tuned using 1 million samples from the MIRIAD-4.4M dataset. This model is specifically designed for clinical knowledge research and educational exploration, trained using the Unsloth framework and QLoRA, and strictly used for non-clinical academic purposes.

Natural Language ProcessingTransformersEnglish

This is a medical AI assistant model based on a hybrid architecture of LLaMA, GPT, and DeepSeek, specifically designed for medical diagnosis reasoning and treatment recommendation assistance. It was trained on 80 million medical records and has in - depth medical knowledge, but is currently only used for research and testing purposes.

Natural Language ProcessingSafetensorsMultiple Languages

A text generation model in the medical domain based on the transformers library, focusing on medical research and disease diagnosis assistance.

Natural Language ProcessingTransformers

Llama3-Preferred-MedSwallow-70B is a fine - tuned model that undergoes continuous pre - training based on the original corpus of medical - related texts and is specifically designed for the medical research field.

Natural Language ProcessingTransformersMultiple Languages

Panacea-7B-Chat is a foundational model specifically designed for clinical trial-related tasks. It has been trained on 793,279 global clinical trial design documents and 1,113,207 clinical research papers, possessing rich clinical knowledge. It outperforms various open-source large language models and medical large language models in clinical trial tasks.

Natural Language ProcessingTransformersEnglish

This is a pathological image analysis model based on the Vision Transformer architecture, specifically designed for the classification and feature extraction of medical pathological images. The model performs excellently on multiple pathological image datasets, providing an effective AI solution for pathological diagnosis and research.

Computer VisionTimm

TheProfessor is a hybrid model created by merging multiple pre-trained language models using the mergekit tool, specializing in conversational interaction, logical reasoning, scientific research, medical knowledge, and mathematical capabilities.

Natural Language ProcessingTransformers

A specialized variant based on the T5 Transformer architecture, fine-tuned specifically for medical text summarization tasks, capable of generating concise and coherent summaries for medical documents, research papers, clinical notes, and other healthcare-related texts.

Natural Language ProcessingTransformersEnglish

This model is based on the t5-small architecture, designed to automatically generate concise titles from lengthy medical research abstracts.

Natural Language ProcessingTransformersEnglish

Clinical Camel is an open-source large language model based on the LLaMA-2 70B architecture, fine-tuned with QLoRA, specifically tailored for the medical and clinical research fields.

Natural Language ProcessingTransformersEnglish

A deep learning model for generating synthetic ECG that creates realistic electrocardiogram data for medical research and development

Scientific ComputingTransformersEnglish

medBERT.de is a German medical natural language processing model based on the BERT architecture, specifically fine-tuned for medical texts, clinical records, and research papers, suitable for various NLP tasks in the medical field.

Natural Language ProcessingTransformersGerman