A neural network based on the encoder-decoder architecture the modeling power of modern sequence models, Transformers with a set of promising experimental features from various papers. - ...

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 ...

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 ...

Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder–Decoder Network With Invertible Modeling ... this work is the first of its kind in combining encoder–decoder network ...

Accurate traffic flow forecasting is crucial for managing and planning urban transportation systems. Despite the widespread use of sequence modelling models like Long Short-Term Memory (LSTM) for this ...

The proposed model explores the effectiveness of encoder-decoder transformer models for six software engineering tasks, including thirteen sub-tasks. CodeTrans. CodeTrans adapts the encoder-decoder ...