What kind of transformer model is BERT?Recurrent Neural Network (RNN) encoder-decoder modelEncoder-only modelDecoder-only modelEncoder-decoder model

What is the name of the language modeling technique that is used in Bidirectional Encoder Representations from Transformers (BERT)?Recurrent Neural Network (RNN)TransformerLong Short-Term Memory (LSTM)Gated Recurrent Unit (GRU)

BERT is a transformer model that was developed by Google in 2018. What is BERT used for?It is used to diagnose and treat diseases.It is used to generate text, translate languages, and write different kinds of creative content.It is used to train other machine learning models, such as Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks.It is used to solve many natural language processing tasks, such as question answering, text classification, and natural language inference.

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 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.

Which of the following is NOT a commonly used pre-trained language model for NLP tasks?Question 14Answera.BERT (Bidirectional Encoder Representations from Transformers)b.ELMO (Embeddings from Language Models)c.GPT (Generative Pre-trained Transformer)d.SVM (Support Vector Machine)