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In Machine Translation, our goal is to convert a sentence from the source language (e.g. Spanish) to the target language (e.g. English). In this assignment, we will implement a sequence-to-sequence (Seq2Seq) network with attention, to build a Neural Machine Translation (NMT) system.

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felipevillaarenas/Neural-Machine-Translation-LSTMs-Attention

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Neural Machine Translation (NMT) System based on LSTMs+Attention

Stanford Certification Note: Heavily inspired by the https://github.com/pcyin/pytorch_nmt repository

Create virtual environment

conda env create --file local_env.yml

Activate and deactivate environment

conda activate local_nmt
conda deactivate

Install necessary packages (On your VM)

pip install -r gpu_requirements.txt

Generate the required vocab files

sh run.sh vocab

Train model on your local machine

sh run.sh train_local

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In Machine Translation, our goal is to convert a sentence from the source language (e.g. Spanish) to the target language (e.g. English). In this assignment, we will implement a sequence-to-sequence (Seq2Seq) network with attention, to build a Neural Machine Translation (NMT) system.

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