So sánh hiệu quả của Transformer với các mô hình ngôn ngữ truyền thống
The advent of Transformers has marked a paradigm shift in the field of natural language processing. This essay delves into a comparative analysis of Transformers and traditional language models, exploring their strengths, weaknesses, and the impact they have had on various NLP tasks.
In conclusion, Transformers have emerged as a superior alternative to traditional language models, exhibiting remarkable capabilities in capturing long-range dependencies, processing information in parallel, and achieving state-of-the-art results in various NLP tasks. While challenges remain in terms of computational requirements and interpretability, the transformative impact of Transformers on natural language processing is undeniable, paving the way for continued advancements in the field.