Machine learning
Transformer (NLP)
Transformer是一种基于注意力机制的深度学习模型，由Vaswani及其同事于2017年提出，通过让序列中的每个词元（token）直接关注序列中的其他所有词元，执行文本分类、命名实体识别和语言建模任务。它用自注意力机制取代了早期的循环设计，能够并行处理整个序列。
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来源
- Vaswani, A. et al. (2017). Attention Is All You Need. NeurIPS. link ↗
如何引用本页
ScholarGate. (2026, June 1). Transformer Model for Natural Language Processing. ScholarGate. https://scholargate.app/zh/deep-learning/transformer-nlp
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