A PyTorch implementation of the Transformer model in "Attention is All You Need".
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Updated
Apr 16, 2024 - Python
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 PyTorch
Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN
A PyTorch implementation of Speech Transformer, an End-to-End ASR with Transformer network on Mandarin Chinese.
Attention is all you need implementation
Open-Source Toolkit for End-to-End Korean Automatic Speech Recognition leveraging PyTorch and Hydra.
A Keras+TensorFlow Implementation of the Transformer: Attention Is All You Need
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 Benchmark of Text Classification in PyTorch
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Neural Machine Translation with Keras
A Pytorch Implementation of "Attention is All You Need" and "Weighted Transformer Network for Machine Translation"
list of efficient attention modules
Implementation of plug in and play Attention from "LongNet: Scaling Transformers to 1,000,000,000 Tokens"
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.
Notes about "Attention is all you need" video (https://www.youtube.com/watch?v=bCz4OMemCcA)
Implementation of "PaLM-E: An Embodied Multimodal Language Model"
Multi heads attention for image classification
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