In recent years, with the rapid development of large model technology, the Transformer architecture has gained widespread attention as its core cornerstone. This article will delve into the principles ...

Seq2Seq is essentially an abstract deion of a class of problems, rather than a specific model architecture, just as the ...

We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design ...

Here, we analyze encoder and decoder Transformer models and show how memory bandwidth can become the dominant bottleneck for decoder models. We argue for a redesign in model architecture, training, ...

The key to addressing these challenges lies in separating the encoder and decoder components of multimodal machine learning models.