This paper mainly introduces the basic situation of Lan-Bridge’s participation in the CCMT 2024 machine translation evaluation project. In this evaluation, we participate in the bilingual translation projects for three minority languages: Mongolian to Chinese, Tibetan to Chinese, and Uygur to Chinese. We adopt the Transformer model based on the self-attention network as our foundation and train three machine translation models for these three language pairs. The paper primarily discusses the specific methods and experimental details employed by the model, providing an in-depth analysis and discussion of the model performance in the bilingual translation tasks for the three minority languages.