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Opus Mt Fr Ru
A French-to-Russian neural machine translation model based on Transformer architecture, developed by Helsinki-NLP team and trained on the OPUS dataset.
Downloads 2,057
Release Time : 3/2/2022
Model Overview
This model is a French-to-Russian neural machine translation model that adopts the transformer-align architecture, supporting normalization and SentencePiece preprocessing.
Model Features
Trained on OPUS dataset
Trained on the large-scale multilingual OPUS dataset, covering a wide range of domains and contexts.
Normalization preprocessing
Utilizes normalization and SentencePiece preprocessing techniques to enhance translation quality and consistency.
Alignment mechanism
Employs transformer-align architecture to improve alignment capabilities between source and target languages.
Model Capabilities
French-to-Russian text translation
Supports normalized text processing
Supports SentencePiece tokenization
Use Cases
Text translation
Document translation
Translates French documents into Russian, suitable for cross-language document processing.
Achieved a BLEU score of 37.9 on the Tatoeba test set.
Real-time translation
Integrated into applications to provide real-time French-to-Russian translation services.
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