AWS Certified Cloud Practitioner
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Why do Transformers use positional encodings?
Real Exam
Community
RRitesh
A
To increase randomness in generation
B
To provide sequence order information to the model
C
To reduce model size
D
To avoid gradient vanishing
Explanation:
Transformers use positional encodings to provide sequence order information to the model. Unlike RNNs and LSTMs which process sequences sequentially and inherently capture order, Transformers process all tokens in parallel through self-attention mechanisms. This parallel processing means they don't have built-in awareness of token positions. Positional encodings add information about the position of each token in the sequence, allowing the model to understand the order of words or tokens, which is crucial for understanding language structure and meaning.
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