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The main purpose of positional encoding in Transformers is to provide a way for the model to incorporate information about the position of each element in the input sequence. Since Transformers do not have any inherent notion of the order of elements in a sequence, positional encoding is used to explicitly encode the position of each element. This is important for tasks such as natural language processing, where the order of words in a sentence is critical to the meaning of the sentence. Positional encoding allows the Transformer to take into account the position of each word in the sentence and learn to generate more accurate representations and predictions. Without positional encoding, …

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bikhanal
Mar 23, 2023
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