  This paper presents the development of a specialized chatbot for materials
science, leveraging the Llama-2 language model, and continuing pre-training on
the expansive research articles in the materials science domain from the S2ORC
dataset. The methodology involves an initial pretraining phase on over one
million domain-specific papers, followed by an instruction-tuning process to
refine the chatbot's capabilities. The chatbot is designed to assist
researchers, educators, and students by providing instant, context-aware
responses to queries in the field of materials science. We make the four
trained checkpoints (7B, 13B, with or without chat ability) freely available to
the research community at https://github.com/Xianjun-Yang/Quokka.
