This project provides an implementation of an Encoder layers and Decoder layers of a Transformer. It includes detailed implementations of both the encoder and decoder components, utilizing multi-head ...

We will use PyTorch + Lightning to create and optimize an encoder-decoder transformer, like the one shown in the picture below. Code a Position Encoder Class From Scratch!!! The position encoder class ...

Transformers contain several blocks of attention and feed-forward layers to gradually capture more complicated relationships. The task of the decoder module is to translate the encoder’s ...

We propose a method for anomaly localization in industrial images using Transformer Encoder-Decoder Mask Reconstruction. The self-attention mechanism of the Transformer enables better attention to ...

To this end, we propose a Transformer-based Sparse Encoder and Answer Decoder (SEAD) model for visual question answering, in which a two-stream sparse Transformer module based on co-attention is built ...

The ability of transformers to handle data sequences without the need for sequential processing makes them extremely effective for various NLP tasks, including translation, text summarization, and ...