Transformer models are a type of neural network architecture that have revolutionized the field of Natural Language Processing (NLP). They utilize a mechanism called self-attention, which allows the model to weigh the importance of different words in a sentence, regardless of their position. This architecture enables the processing of data in parallel, leading to significant improvements in training efficiency and performance on various NLP tasks. Common use cases include language translation, text summarization, and sentiment analysis, making them essential for modern AI applications.
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AI Fundamentals