https://huggingface.co/m42-health

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This is an automated message from the Librarian Bot. I found the following papers similar to this paper.

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These\nmodels are built on Llama3 architecture and fine-tuned using specialized\nclinical data. They underwent multi-stage preference alignment to effectively\nrespond to natural prompts. While generic models are often preference-aligned\nto avoid answering clinical queries as a precaution, Med42-v2 is specifically\ntrained to overcome this limitation, enabling its use in clinical settings.\nMed42-v2 models demonstrate superior performance compared to the original\nLlama3 models in both 8B and 70B parameter configurations and GPT-4 across\nvarious medical benchmarks. These LLMs are developed to understand clinical\nqueries, perform reasoning tasks, and provide valuable assistance in clinical\nenvironments. 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Papers

arxiv:2408.06142

Med42-v2: A Suite of Clinical LLMs

Published on Aug 12, 2024

· Submitted by

AK on Aug 13, 2024

Upvote

Authors:

Clément Christophe ,

Praveen K Kanithi ,

Tathagata Raha ,

Marco AF Pimentel

Abstract

Med42-v2 enhances Llama3 with clinical data to improve performance in healthcare settings, outperforming generic models across medical benchmarks.

AI-generated summary

Med42-v2 introduces a suite of clinical large language models (LLMs) designed to address the limitations of generic models in healthcare settings. These models are built on Llama3 architecture and fine-tuned using specialized clinical data. They underwent multi-stage preference alignment to effectively respond to natural prompts. While generic models are often preference-aligned to avoid answering clinical queries as a precaution, Med42-v2 is specifically trained to overcome this limitation, enabling its use in clinical settings. Med42-v2 models demonstrate superior performance compared to the original Llama3 models in both 8B and 70B parameter configurations and GPT-4 across various medical benchmarks. These LLMs are developed to understand clinical queries, perform reasoning tasks, and provide valuable assistance in clinical environments. The models are now publicly available at https://huggingface.co/m42-health{https://huggingface.co/m42-health}.