Transformer是在2017年由谷歌提出的，当时应用在机器翻译场景。从结构上来看，它分为Encoder 和Decoder两个...
[论文1]:Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio: “Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation”, 2014; [http://arxiv.org/abs/1406.1078 arXiv:1406.1078]. 图2:输入序列...
The goal of the blog post is to give anin-detailexplanation ofhowthe transformer-based encoder-decoder architecture modelssequence-to-sequenceproblems. We will focus on the mathematical model defined by the architecture and how the model can be used in inference. Along the way, we will give so...
Rank-One Editing of Encoder-Decoder Models Vikas Raunak, Arul Menezes NeurIPS 2022 Workshop on Interactive Learning for Natural Language Processing|November 2022 Large sequence to sequence models for tasks such as Neural Machine Translation (NMT) are usually trained over hundreds of millions of...
In this work, we present a preliminary study investigating rank-one editing as a direct intervention method for behavior deletion requests in encoderdecoder transformer models. We propose four editing tasks for NMT and show that the proposed editing algorithm achieves high efficacy, while requiring ...
Autoencoders vs. encoder-decoders Though all autoencoder models include both an encoder and a decoder, not allencoder-decodermodels areautoencoders. Encoder-decoderframeworks, in which an encoder network extracts key features of the input data and a decoder network takes that extracted feature data...
(3) Encoder-Decoder Models Examples:T5 (Text-to-Text Transfer Transformer), Transformer (originally used for machine translation) What does it do? Main Function:First understand the input content, then generate output related to the input. ...
machine-learning deep-learning jupyter keras jupyter-notebook cnn lstm floydhub seq2seq cnn-keras encoder-decoder Updated Aug 16, 2024 HTML bentrevett / pytorch-seq2seq Star 5.5k Code Issues Pull requests Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch ...
{output\ stride}\)used during evaluation.Decoder:Employing the proposed decoder structure.MS:Multi-scale inputs during evaluation.Flip:Adding left-right flipped inputs.SC:Adopting depthwise separable convolution for both ASPP and decoder modules.COCO:Models pretrained on MS-COCO.JFT:Models pretrained ...
XSum: 0.27/0.20 vs 0.24/0.19 We also show that results continue as we scale the models up to 1B parameters. Usage Package Installation Start by creating a virtual conda environment using python==3.10, and install necessary packages. cd encoder-decoder-slm conda create -n slm_env python=3.10...