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.
Question
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.
Solution
The Transformer model, used in machine learning, consists of two main components: the encoder and the decoder.
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Encoder: The encoder's role is to understand the input data and create a higher-level representation of this data. It does this by ingesting an input sequence (such as a sentence in a language translation task) and mapping it to a sequence of continuous representations known as hidden states. These hidden states capture the information from the input sequence. The encoder does not produce a single hidden state or a sequence of images.
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Decoder: The decoder's role is to generate an output sequence from the hidden states produced by the encoder. It takes in the sequence of hidden states and, step by step, produces an output sequence. The output sequence is generated one element at a time, with each element being influenced by the previous elements and the hidden states from the encoder.
In summary, the encoder processes the input data to a higher-level representation, and the decoder uses this representation to generate an output sequence.
Similar Questions
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