
2 min read
AI This article explores the core components of Transformer-based Encoder-Decoder models, their revolutionary use of self-attention, positional encodings, and applications in machine translation and other sequence-to-sequence tasks.
This article explores the core components of Transformer-based Encoder-Decoder models, their revolutionary use of self-attention, positional encodings, and applications in machine translation and other sequence-to-sequence tasks.