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Opus Mt En Cs
opus-mt-en-cs is a machine translation model based on the Transformer architecture, specifically designed for translating English to Czech. The model was developed by the University of Helsinki NLP team as part of the OPUS-MT project.
Downloads 2,546
Release Time : 3/2/2022
Model Overview
This model is a Transformer-based neural machine translation model primarily used for English-to-Czech text translation tasks. It employs SentencePiece for text preprocessing and is trained on the OPUS dataset.
Model Features
Transformer-based architecture
Utilizes the advanced Transformer architecture to effectively handle long-range dependencies and improve translation quality.
SentencePiece preprocessing
Employs SentencePiece for text normalization and tokenization, supporting more flexible vocabulary handling.
Multi-testset validation
Evaluated on multiple standard test sets, including newssyscomb2009 and newstest2008-2019, ensuring reliable translation quality.
Model Capabilities
English-to-Czech text translation
Supports translation across various text domains
Handles long-text translation
Use Cases
News translation
News article translation
Translates English news articles into Czech while preserving the original semantics and style.
Achieves BLEU scores of 22.7-26.7 on the newstest2015-2019 test sets
General text translation
Everyday text translation
Translates various everyday texts, such as emails and web content.
Achieves a BLEU score of 46.1 on the Tatoeba test set
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