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umsuka-en-zu
MUNasir/umsuka-en-zu
umsuka-en-zu is a machine learning model from MUNasir. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
All-time downloads
648
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Repo size
605 MB
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At a glance
- Library
- transformers
- Model type
- marian
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Feb 12, 2024
- SHA
- 9ee1fcbb
Model card
From the Hugging Face model README
Languages:
-
Source language: English
-
Source language: isiZulu
Model Details:
-
model: transformer
-
Architecture: MarianMT
-
pre-processing: normalization + SentencePiece
Pre-trained Model:
Corpus:
- Umsuka English-isiZulu Parallel Corpus (https://zenodo.org/record/5035171#.Yh5NIOhBy3A)
Benchmark:
| Benchmark | Train | Test |
|---|---|---|
| Umsuka | 17.61 | 13.73 |
GitHub:
Citation:
@article{umair2022geographical,
title={Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine Translation},
author={Umair Nasir, Muhammad and Amos Mchechesi, Innocent},
journal={arXiv e-prints},
pages={arXiv--2205},
year={2022}
}
- Library
- transformers
- Type
- marian
- Created
- Mar 2, 2022
- Updated
- Feb 12, 2024