# Medical Q&A

This project provides the GGUF quantized file for the Echelon-AI/Med-Qwen2-7B model, supported by Featherless AI, aiming to enhance model performance and reduce operating costs.

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.

MedGemma is a medical multimodal model built on Gemma 3, with two versions of 4B and 27B, focusing on medical text and image understanding tasks.

QwenMedic-v1 is a medical-specific language model developed based on Qwen3-1.7B, fine-tuned for clinical reasoning and instruction-following tasks to enhance diagnostic Q&A and clinical summarization capabilities.

Medra is a quantized language model fine-tuned on medical datasets, specializing in medical Q&A and summarization tasks.

A fine-tuned version based on the Qwen2.5-3B-Instruct model on medical and health datasets, designed to generate medical-related responses and provide health guidance to users.

HealthGPT is a large language model specifically developed for unified multimodal healthcare tasks.

medllama3-v20 is a text generation model specialized in the medical field, developed based on the Llama3 architecture, aiming to provide high-quality medical text generation capabilities.

HealthGPT is a model specifically developed for unified multimodal healthcare tasks, supporting both English and Chinese.

This is a medical domain Q&A model fine-tuned on DeepSeek-R1, specializing in medical-related text generation tasks.

Llama-Krikri-8B-Base is a large Greek foundational language model built upon Llama-3.1-8B, extending Greek language capabilities through continued pretraining while maintaining English proficiency.

A medical dialogue model fine-tuned based on Llama-2-7b, designed to answer medical-related questions and provide detailed knowledge.

Qwen2.5-Aloe-Beta-7B is an open-source large medical language model that achieves state-of-the-art performance in multiple medical tasks. It is fine-tuned based on the Qwen2.5-7B architecture, and the training data covers 1.8 billion tokens of diverse medical tasks.

Aloe is a brand-new family of large medical language models. Through model fusion and advanced prompting strategies, it is highly competitive among open-source models of the same type.

This is a GGUF format model converted from Chuxin-Embedding, primarily used for Chinese text retrieval tasks.

Med42-v2 is a clinically aligned large language model suite developed by M42, based on the LLaMA-3 architecture, available in 8B or 70B parameter versions, designed to provide high-quality medical Q&A capabilities.

This is a Llama3 model fine-tuned on the PubMedQA dataset, specializing in medical Q&A tasks.

An improved medical dialogue model based on Llama3-8B, specifically optimized for medical Q&A and clinical text processing

MMedLM is a multilingual language model focusing on the medical field. Based on the Llama 3 architecture, it performs excellently in tasks such as medical Q&A.

A Chinese medical domain model based on Llama-3-8B, merged via slerp method combining WiNGPT2 and JSL-MedLlama-3-8B models

A large language model for the medical domain developed by John Snow Labs, optimized based on Microsoft Phi-2 architecture

A large language model for the medical domain developed by John Snow Labs, based on supervised fine-tuning (SFT) of Meta-Llama-3-8B

A Llama3 8B series medical chat model fine-tuned from epfl-llm/meditron-7b using SFT QLora technology

A large language model in the medical field developed by John Snow Labs, fine-tuned based on Meta-Llama-3-8B, suitable for medical-related tasks.

A medical-specific language model based on the LLaMa-3 architecture, fine-tuned on extensive health information datasets to provide professional medical advice

A large-scale medical domain language model trained by physicians, the first 7b model to surpass the 60% passing score on the MedQA (USMLE) exam

A biomedical domain large language model fine-tuned based on Meta-Llama-3-8B, specializing in healthcare and biomedical Q&A

A 7-billion parameter medical large language model developed by John Snow Labs, optimized for the biomedical field

The first large-scale Greek foundational language model, based on the Mistral-7B architecture, enhanced with 40 billion tokens of Greek and English corpus to improve Greek language capabilities

Meltemi-7B-Instruct-v1 is a Greek instruction fine-tuned large language model based on the Mistral-7B architecture, supporting 8192 context length and optimized for Greek tasks

An open-source large language model for the medical domain based on the Mistral architecture, further pre-trained on PubMed Central texts

BioMistral-7B-mistral7instruct-dare is a large language model for the medical domain, merged using the DARE method from Mistral-7B-Instruct-v0.1 and BioMistral-7B, specializing in biomedical text generation tasks.

BioMistral-7B-slerp is a medical domain language model merged using the SLERP method from BioMistral-7B and Mistral-7B-Instruct-v0.1, specializing in biomedical text processing

BioMistral is an open-source medical domain model suite based on the Mistral architecture, further pretrained using PubMed Central open-access text data.

Dr Samantha 7B is a large language model based on the Llama architecture, supporting English and Chinese, specializing in medical Q&A and health consultation tasks.

A medical domain chatbot based on the Llama-2-7B-Chat-GGML model, specializing in answering medical-related questions and providing medical text generation capabilities

WiNGPT2 is a large-scale medical vertical domain model based on the GPT architecture, dedicated to integrating professional medical knowledge, healthcare information, and data to provide intelligent medical Q&A, diagnostic support, and medical knowledge services for the industry.

A fine-tuned version based on epfl-llm/meditron-7b using the Alpaca dataset for SFT training, specializing in medical Q&A tasks

Meditron 7B is a large language model in the medical field developed by the EPFL LLM Team. It is further pre-trained based on Llama-2-7B and focuses on medical knowledge encoding and clinical decision support.

A GPT-2 based medical Q&A chatbot model focused on providing medical-related information responses