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This study constructed a Japanese chat dataset for tuning large languagemodels (LLMs), which consist of about 8.4 million records. Recently, LLMs havebeen developed and gaining popularity. However, high-performing LLMs areusually mainly for English. There are two ways to support languages other thanEnglish by those LLMs: constructing LLMs from scratch or tuning existingmodels. However, in both ways, datasets are necessary parts. In this study, wefocused on supporting Japanese in those LLMs and making a dataset for trainingor tuning LLMs in Japanese. The dataset we constructed consisted of varioustasks, such as translation and knowledge tasks. In our experiment, we tuned anexisting LLM using our dataset and evaluated the performance qualitatively. Theresults suggest that our dataset is possibly beneficial for LLMs. However, wealso revealed some difficulties in constructing LLMs in languages other thanEnglish.

llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and its Methodology