This repository contains an implementation of the Transformer Encoder-Decoder model from scratch in C++. The objective is to build a sequence-to-sequence model that leverages pre-trained word ...

Transformer Architecture: Implemented various Transformer components, including multi-head attention, feed-forward layers, layer normalization, encoder, and decoder blocks, following the Attention is ...

To the best of our knowledge, we present the first exploration of combining Swin Transformer and convolution in both the encoder and decoder stages. Through comprehensive comparative analysis, we ...

But not all transformer applications require both the encoder and decoder module. For example, the GPT family of large language models uses stacks of decoder modules to generate text.

Decoder-only models. In the last few years, large neural networks have achieved impressive results across a wide range of tasks. Models like BERT and T5 are trained with an encoder only or ...

The transformer model has become a state-of-the-art model in Natural Language Processing. The initial transformer model, known as the vanilla transformer model, is designed to improve some prominent ...

Transformer Neural Networks Described Transformers are a type of machine learning model that specializes in processing and interpreting sequential data, making them optimal for natural language ...