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#

seq2seq-attn

Here are 30 public repositories matching this topic...

pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"

  • UpdatedJan 23, 2023
  • Python

Image to LaTeX (Seq2seq + Attention with Beam Search) - Tensorflow

  • UpdatedAug 19, 2020
  • Python

CRNN with attention to do OCR,add Chinese recognition

  • UpdatedJun 16, 2024
  • Python

This is a pytorch implementation for the BST model from Alibabahttps://arxiv.org/pdf/1905.06874.pdf

  • UpdatedJul 11, 2022
  • Jupyter Notebook

Korean English NMT(Neural Machine Translation) with Gluon

  • UpdatedFeb 28, 2018
  • Jupyter Notebook

Key value memory network implemented using keras

  • UpdatedApr 16, 2018
  • Jupyter Notebook

C# Sequence to Sequence Learning with Attention using LSTM neural Networks

  • UpdatedFeb 18, 2025
  • C#

Chatbot using Tensorflow (Model is seq2seq) Extend V2.0 ko

  • UpdatedNov 22, 2018
  • Python

use an AI model to write couplet with TensorFlow 2 / 用AI对对联

  • UpdatedJul 20, 2020
  • Python

Sequence-to-sequence model implementations including RNN, CNN, Attention, and Transformers using PyTorch

  • UpdatedAug 28, 2023
  • Python

Neural Machine Translation using LSTMs and Attention mechanism. Two approaches were implemented, models, one without out attention using repeat vector, and the other using encoder decoder architecture and attention mechanism.

  • UpdatedJun 21, 2022
  • Python

Generates summary of a given news article. Used attention seq2seq encoder decoder model.

  • UpdatedDec 20, 2024
  • Jupyter Notebook

Seq2Seq Neural Machine Translation Task, Completed as a part of CS462-NLP Coursework

  • UpdatedOct 23, 2023
  • Jupyter Notebook

基于Seq2Seq+Attention模型的Textsum文本自动摘要

  • UpdatedOct 31, 2017
  • Python

This repository contains the code for a speech to speech translation system created from scratch for digits translation from English to Tamil

  • UpdatedJun 10, 2023
  • Python

Neural Machine Translation by Seq2Seq Model with Attention layer

  • UpdatedApr 17, 2019
  • Jupyter Notebook

A few approaches using sequence to sequence (seq2seq) architecture to solve semantice parsing problem

  • UpdatedMar 22, 2024
  • Python

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