Researchers at the Gaoling School of Artificial Intelligence, Renmin University of China, have developed YuLan-Mini, a new open data-efficient language model featuring 2.42 billion parameters. This model is designed to enhance long-context capabilities and employs advanced training techniques, marking a notable advancement in the field of artificial intelligence. Additionally, the concept of Low-Rank Adaptation (LoRA) has emerged as a new approach to fine-tuning large language models, which allows for more efficient model training by significantly reducing the number of parameters that need to be updated during the fine-tuning process.