PyMarian: Fast Neural Machine Translation and Evaluation in Python
<|reference_start|>PyMarian: Fast Neural Machine Translation and Evaluation in Python: The deep learning language of choice these days is Python; measured by factors such as available libraries and technical support, it is hard to beat. At the same time, software written in lower-level programming languages like C++ retain advantages in speed. We describe a Python interface to Marian NMT, a C++-based training and inference toolkit for sequence-to-sequence models, focusing on machine translation. This interface enables models trained with Marian to be connected to the rich, wide range of tools available in Python. A highlight of the interface is the ability to compute state-of-the-art COMET metrics from Python but using Marian's inference engine, with a speedup factor of up to 7.8$\times$ the existing implementations. We also briefly spotlight a number of other integrations, including Jupyter notebooks, connection with prebuilt models, and a web app interface provided with the package. PyMarian is available in PyPI via $\texttt{pip install pymarian}$.<|reference_end|>
@article{gowda2024pymarian:,
    title={PyMarian: Fast Neural Machine Translation and Evaluation in Python},
    author={Thamme Gowda, Roman Grundkiewicz, Elijah Rippeth, Matt Post, Marcin
  Junczys-Dowmunt},
    journal={arXiv preprint arXiv:2408.11853},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.11853},
    primaryClass={cs.CL}
}