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

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

Multilingual Automatic Speech Recognition with word-level timestamps and confidence

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

list of efficient attention modules

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

My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT pretrained models.

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

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

Implementation of plug in and play Attention from "LongNet: Scaling Transformers to 1,000,000,000 Tokens"

A Benchmark of Text Classification in PyTorch

Open-Source Toolkit for End-to-End Korean Automatic Speech Recognition leveraging PyTorch and Hydra.

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

Neural Machine Translation with Keras

Attention is all you need implementation

An open source implementation of "Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning", an all-new multi modal AI that uses just a decoder to generate both text and images

pytorch implementation of Attention is all you need

Original transformer paper: Implementation of Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.

Implementation of "PaLM-E: An Embodied Multimodal Language Model"

Implementation of the ScreenAI model from the paper: "A Vision-Language Model for UI and Infographics Understanding"