Implementation Guidelines for Training Artificial Intelligence Large Models with High-Quality Datasets is led by the Zhongguancun Digital Economic Industry Alliance and jointly formulated by a number of leading technology enterprises and financial institutions, with high industry authority and extensive influence. Based on the current practical pain points of the rapid development of artificial intelligence large models but uneven data quality and lack of unified specifications for the training process, the standard systematically constructs a technical specification system covering the whole life cycle of "data collection - cleaning - annotation - training - evaluation - decommissioning". The guidelines clarify the core requirements of high-quality datasets in terms of accuracy, integrity, consistency and compliance, set quantitative quality indicators, integrate safety and compliance management, and strengthen data desensitization, access control and privacy protection. Its content is both forward-looking and operable, and has been verified to be effective in practical projects such as multimodal large models, which can improve data utilization efficiency by about 30% and reduce the risk of model deviation by more than 40%. As the first group standard in China focusing on the whole-process governance of training data for large models, this achievement provides a standardized implementation path for the industry, and is of great strategic significance for promoting the healthy and orderly development of the AI industry and enhancing the competitiveness of China's large model technology.