Understanding Sentences at Once with the Transformer Model
The Transformer is a neural network model that processes entire sentences simultaneously, rather than sequentially.
It's widely used in the field of Natural Language Processing (NLP) and is the core architecture of large language models like GPT and BERT.
Why Did the Transformer Emerge?
Traditional RNNs and LSTMs process words one at a time, in order.
While this approach is advantageous for understanding the flow of a sentence, it is slow and struggles with retaining earlier information in longer sentences.
The Transformer was developed to resolve this issue.
The Transformer model processes all words at once and directly computes the relationships between words, allowing for a more accurate understanding of the overall meaning of the sentence.
In the next lesson, we will explore in detail one of the key components of the Transformer: the Self-Attention Mechanism.
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