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Explain positional encodings in Transformer models.

Answer Posted / Andleeb Sayyed

Positional encodings in Transformer models are vector representations added to the input embeddings, enabling the model to understand the relative position of words within a sequence. They help the model capture the order and context of words even if they are not explicitly stated.

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