A Seq2Seq (Sequence-to-Sequence) Model is designed for tasks that involve converting one sequence of data into another, such as translating sentences or summarizing text. The model typically consists of an Encoder that processes the input sequence and a Decoder that generates the output sequence. Seq2Seq models have been widely used in natural language processing for tasks like machine translation, text generation, and speech recognition, leveraging their ability to handle sequential data effectively.