Description

Sequence-to-Sequence (Seq2Seq) models are a class of neural network models designed to transform an input sequence into an output sequence. They typically consist of an encoder that processes the input sequence and a decoder that generates the output sequence. Seq2Seq models have been particularly successful in tasks where both input and output are sequences of variable length, such as machine translation or text summarization.

Examples

• 🌐 Machine translation
• 📝 Text summarization
• 🗣️ Speech-to-text conversion

Applications