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Transformers are a groundbreaking architecture in the field of natural language processing (NLP) that have revolutionized how machines understand and generate human language. This introduction will explore the fundamental concepts of transformer models, such as their unique structure and mechanisms, such as self-attention and positional encodings. These models have enabled remarkable performance in tasks like language translation, text generation, and sentiment analysis, and have had a profound impact on the landscape of artificial intelligence.