HouYi: An open-source large language model specially designed for
  renewable energy and carbon neutrality field
Mingliang Bai Zhihao Zhou Ruidong Wang Yusheng Yang Zizhen Qin Yunxiao Chen Chunjin Mu Jinfu Liu Daren Yu
Renewable energy is important for achieving carbon neutrality goal. With the
great success of Large Language Models (LLMs) like ChatGPT in automatic content
generation, LLMs are playing an increasingly important role. However, there has
not been a specially designed LLM for renewable energy. Meanwhile, there has
not been any dataset of renewable energy for training LLMs. Therefore, this
paper published the first open-source Renewable Energy Academic Paper (REAP)
dataset for non-commercial LLM research of renewable energy. REAP dataset is
collected through searching the title and abstract of 1,168,970 academic
literatures from Web of Science. Based on REAP dataset, HouYi model, the first
LLM for renewable energy, is developed through finetuning general LLMs. HouYi
demonstrated powerful academic paper paragraph generation ability in renewable
energy field. Experiments show that its ability to generate academic papers on
renewable energy is comparable to ChatGPT, slightly outperforms Claude, ERNIE
Bot and SparkDesk, and significantly outperforms open-source LLaMA-13B model.