Med42-v2: A Suite of Clinical LLMs
Authors: name: Clément Christophe, name: Praveen K Kanithi, name: Tathagata Raha, name: Shadab Khan, name: Marco AF Pimentel

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}.