This article provides a comprehensive comparison of GPT and BERT, two major Transformer variants, explaining their architectural differences, training methodologies (masked language modeling vs. autoregressive prediction), and distinct applications in natural language understanding and generation.
原文翻译:
本文全面比较了Transformer的两大主要变种GPT和BERT,解析了它们在架构、训练方法(掩码语言建模与自回归预测)以及自然语言理解与生成应用上的核心差异。