H13-321_V2.5 Exam Dumps | In NLP tasks, transformer models perform well in multiple tasks due to their self-attention mechanism

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Question 19/27

In NLP tasks, transformer models perform well in multiple tasks due to their self-attention mechanism and parallel computing capability. Which of the following statements about transformer models are true?

A. Transformer models outperform RNN and CNN in processing long texts because they can effectively capture global dependencies.

B. Multi-head attention is the core component of a transformer model. It computes multiple attention heads in parallel to capture semantic information in different subspaces.

C. A transformer model directly captures the dependency between different positions in the input sequence through the self-attention mechanism, without using the recurrent neural network (RNN) or convolutional neural network (CNN).

D. Positional encoding is optional in a transformer model because the self-attention mechanism can naturally process the order information of sequences.

Question 19/27

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