HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge
This addresses the need for improved medical AI assistance in Chinese healthcare, but it is incremental as it adapts an existing model to a specific domain.
The paper tackles the problem of large language models underperforming in biomedical tasks due to lack of medical expertise, by proposing HuaTuo, a LLaMA-based model fine-tuned with generated QA instances, resulting in responses with more reliable medical knowledge.
Large Language Models (LLMs), such as the LLaMA model, have demonstrated their effectiveness in various general-domain natural language processing (NLP) tasks. Nevertheless, LLMs have not yet performed optimally in biomedical domain tasks due to the need for medical expertise in the responses. In response to this challenge, we propose HuaTuo, a LLaMA-based model that has been supervised-fine-tuned with generated QA (Question-Answer) instances. The experimental results demonstrate that HuaTuo generates responses that possess more reliable medical knowledge. Our proposed HuaTuo model is accessible at https://github.com/SCIR-HI/Huatuo-Llama-Med-Chinese.