A PyTorch implementation of the Transformer model in "Attention is All You Need".

A TensorFlow Implementation of the Transformer: Attention Is All You Need

Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet

Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN

A Keras+TensorFlow Implementation of the Transformer: Attention Is All You Need

A Benchmark of Text Classification in PyTorch

Neural Machine Translation with Keras

A PyTorch implementation of Speech Transformer, an End-to-End ASR with Transformer network on Mandarin Chinese.

A Pytorch Implementation of "Attention is All You Need" and "Weighted Transformer Network for Machine Translation"

pytorch implementation of Attention is all you need

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

list of efficient attention modules

Open Source Project for Korean End-to-End (E2E) Automatic Speech Recognition (ASR) in Pytorch for Deep Learning Researchers

Transformers without Tears: Improving the Normalization of Self-Attention

Multi heads attention for image classification

Neutron: A pytorch based implementation of Transformer and its variants.

Abstractive summarization using Transformers.

A PyTorch implementation of the Transformer model from "Attention Is All You Need".

Experiments on Multilingual NMT

Implementation of "Attention is All You Need" paper

Implementation of the Transformer architecture described by Vaswani et al. in "Attention Is All You Need"

Transformer Based SeqGAN for Language Generation

A simple TensorFlow implementation of the Transformer

Machine Translation using Transfromers

Witwicky: An implementation of Transformer in PyTorch.

Fake News Detection by Learning Convolution Filters through Contextualized Attention

Attention Is All You Need | a PyTorch Tutorial to Machine Translation