Release of Pre-Trained Models for the Japanese Language
This work addresses AI democratization for Japanese-speaking communities by providing specialized models, though it is incremental as it applies existing methods to new data.
The authors tackled the lack of large pre-trained models for non-English languages by releasing GPT, CLIP, Stable Diffusion, and HuBERT models pre-trained in Japanese, enabling users to access AI aligned with Japanese cultural values and achieving high performance in Japanese tasks.
AI democratization aims to create a world in which the average person can utilize AI techniques. To achieve this goal, numerous research institutes have attempted to make their results accessible to the public. In particular, large pre-trained models trained on large-scale data have shown unprecedented potential, and their release has had a significant impact. However, most of the released models specialize in the English language, and thus, AI democratization in non-English-speaking communities is lagging significantly. To reduce this gap in AI access, we released Generative Pre-trained Transformer (GPT), Contrastive Language and Image Pre-training (CLIP), Stable Diffusion, and Hidden-unit Bidirectional Encoder Representations from Transformers (HuBERT) pre-trained in Japanese. By providing these models, users can freely interface with AI that aligns with Japanese cultural values and ensures the identity of Japanese culture, thus enhancing the democratization of AI. Additionally, experiments showed that pre-trained models specialized for Japanese can efficiently achieve high performance in Japanese tasks.