the GPT family of large language models uses stacks of decoder modules to generate text. BERT, another variation of the transformer model developed by researchers at Google, only uses encoder ...

Standard transformer architecture consists of three main components - the encoder, the decoder and the attention mechanism. The encoder processes input data ...

The core innovation lies in replacing the traditional DETR backbone with ConvNeXt, a convolutional neural network inspired by ...

It was not until Google introduced the Transformer model in 2017 in the ground-breaking paper “Attention is all you need” that a full encoder-decoder model, using multiple layers of self ...

Specifically, the goal is to create a model that accepts a sequence of words such as "The man ran through the {blank} door" and then predicts most-likely words to fill in the blank. Transformer ...