Sequence-to-sequence models take an input sequence, encode it into an internal representation, and then decode that into an output sequence. This makes them perfect for tasks like machine translation, text summarization, and question answering.
These models are like skilled translators. A translator takes a sentence in one language (source), understands its meaning, and then reproduces that meaning in another language (target).
Example:
T5, BART Family
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