A chatbot implemented in TensorFlow based on the seq2seq model, with certain rules integrated.

TURJUMAN, a neural toolkit for translating from 20 languages into Modern Standard Arabic (MSA).

A Chinese to English Neural Model Translation Project

PyTorch implementation of a 2D-LSTM Seq2Seq Model for NMT.

This is the sequential Encoder-Decoder implementation of Neural Machine Translation using Keras

😺 基于Keras实现seq2seq，进行英文到中文的翻译

Implemented transformer NN block for Machine translation, text classfication, Natural language inference as well as Machine reading comprehension model.

Neural Machine Translation for RDFS reasoning: code and datasets for "Deep learning for noise-tolerant RDFS reasoning" http://www.semantic-web-journal.net/content/deep-learning-noise-tolerant-rdfs-reasoning-4

Neural Machine Translator with Transformers. Implementation for "Attention Is All You Need" paper

A web application to display the retrosynthetic reaction pathway using FLASK

whole package for seq2seq nmt model, machine translation.

Neural Machine Translation using Attention Mechanism

Implementation of Character level NMT(Neural Machine Translation) using RNN and Attention Wrapper

Train a jp2zh NMT model with ACG parallel corpus.

Implement the Google NMT model with good explanation

Neural Machine Translation (NMT) from Spanish to English. Architecture is Seq2Seq + Multiplicative Attention + Character-level conditional English (target) language model.

BayaanX is a Transformer-based Neural Machine Translation (NMT) model for translating Arabic to English. Built with PyTorch, it features multi-head attention, positional encoding, and a Streamlit-based web interface. The project includes data preprocessing, vocabulary building, training, and inference scripts for seamless translation.

French to English neural machine translation trained on multi30k dataset.