In the context of Transformers, what is the role of positional encoding?Question 8Answera.Capture the order of words in a sequence.b.Represent the meaning of individual words.c.None of thesed.Improve the efficiency of the self-attention mechanism.

What is the main role of the decoder in a Transformer model?Question 14Answera.To generate output tokens based on the final encoder representation.b.To compute attention scores between input and output tokens.c.Learning positional encodings.d.To encode the input sequence.

The ______________ mechanism in transformers allows for capturing relationships between all words in a sequence simultaneously, rather than sequentially.

What is the primary function of the self-attention mechanism in transformers?Group of answer choicesTo perform backpropagationTo reduce the computational costTo reduce the computational cost of trainingTo allow the model to weigh the importance of different words in a sentence relative to each other

3.Question 3What is the self-attention that powers the transformer architecture?1 pointA mechanism that allows a model to focus on different parts of the input sequence during computation.A technique used to improve the generalization capabilities of a model by training it on diverse datasets.A measure of how well a model can understand and generate human-like language.The ability of the transformer to analyze its own performance and make adjustments accordingly.4.Question 4

Which mechanism in transformers addresses the quadratic complexity of self-attention?Group of answer choicesSparse attentionLayer normalizationMulti-head attentionPositional encoding