Skip to content
This repository has been archived by the owner on Apr 25, 2023. It is now read-only.
/ seq2seq Public archive

Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch

License

Notifications You must be signed in to change notification settings

keon/seq2seq

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

37 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

mini seq2seq

Minimal Seq2Seq model with attention for neural machine translation in PyTorch.

This implementation focuses on the following features:

  • Modular structure to be used in other projects
  • Minimal code for readability
  • Full utilization of batches and GPU.

This implementation relies on torchtext to minimize dataset management and preprocessing parts.

Model description

Requirements

  • GPU & CUDA
  • Python3
  • PyTorch
  • torchtext
  • Spacy
  • numpy
  • Visdom (optional)

download tokenizers by doing so:

python -m spacy download de
python -m spacy download en

References

Based on the following implementations