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

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.

Question 7Which transformer-based model architecture is well-suited to the task of text translation?1 pointSequence-to-sequenceAutoencoderAutoregressive

Which model architecture introduced the concept of transformers in NLP?*1 pointConvolutional Neural Networks (CNN)B) Recurrent Neural Networks (RNN)Long Short-Term Memory (LSTM)Attention Is All You Need

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

What are the encoder and decoder components of a transformer model?The encoder ingests an input sequence and produces a sequence of tokens. The decoder takes in the tokens from the encoder and produces an output sequence.The encoder ingests an input sequence and produces a single hidden state. The decoder takes in the hidden state from the encoder and produces an output sequence.The encoder ingests an input sequence and produces a sequence of hidden states. The decoder takes in the hidden states from the encoder and produces an output sequence.The encoder ingests an input sequence and produces a sequence of images. The decoder takes in the images from the encoder and produces an output sequence.