The recent progress of large language models (LLMs), including ChatGPT and GPT-4, in comprehending and responding to human instructions has been remarkable. Nevertheless, these models typically perform better in English and have not been explicitly trained for the medical domain, resulting in suboptimal precision in diagnoses, drug recommendations, and other medical advice. Additionally, training and deploying a dialogue model is still believed to be impossible for hospitals, hindering the promotion of LLMs. To tackle these challenges, we have collected databases of medical dialogues in Chinese with ChatGPT's help and adopted several techniques to train an easy-deploy LLM. Remarkably, we were able to fine-tune the ChatGLM-6B on a single A100 80G in 13 hours, which means having a healthcare-purpose LLM can be very affordable. DoctorGLM is currently an early-stage engineering attempt and contain various mistakes. We are sharing it with the broader community to invite feedback and suggestions to improve its healthcare-focused capabilities: https://github.com/xionghonglin/DoctorGLM.
翻译:语言模型(LLMs)的最新进展,包括ChatGPT和GPT-4,在理解和回应人类指令方面取得了显著进展。然而,这些模型通常在英语方面表现更好,并且没有专门针对医疗领域进行训练,导致诊断、药品推荐和其他医疗建议的精度不佳。此外,训练和部署对话模型仍然被认为是不可能的,这阻碍了LLMs的推广。为了解决这些挑战,我们使用ChatGPT的帮助收集了中文医疗对话的数据库,并采用了几种技术来培训易于部署的LLM。令人惊讶的是,我们能够在一个单一的A100 80G上在13个小时内对ChatGLM-6B进行微调,这意味着拥有医疗目的的LLM可以非常实惠。DoctorGLM目前是一个早期的工程尝试,并且包含各种错误。我们与广大社区分享,以邀请反馈和建议来改善其医疗方面的能力:https://github.com/xionghonglin/DoctorGLM。