opus-mt-en-vi Open-source Machine Translation Model - Free English to Vietnamese (including Chinese character variants) Translation

Opus Mt En Vi

Developed by Helsinki-NLP

This is a Transformer-based machine translation model from English to Vietnamese (including Han character variants), developed by the Helsinki-NLP team.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Transformer architecture #SentencePiece tokenization #Tatoeba benchmark

Downloads 18.94k

Release Time : 3/2/2022

Model Overview

This model is specifically designed for English-to-Vietnamese text translation tasks, supporting standardized text input and using SentencePiece tokenization.

Model Features

Multilingual variant support

Supports both standard Vietnamese and Han variant outputs

Standardized preprocessing

Uses standardized text input and SentencePiece tokenization (spm32k)

Transformer architecture

Based on advanced Transformer alignment model architecture

Model Capabilities

English-to-Vietnamese text translation

Supports Han variant output

Batch text processing

Use Cases

Cross-language communication

Business document translation

Translate English business documents into Vietnamese

BLEU 37.2/chr-F 0.542

Website content localization

Translate English website content into Vietnamese versions

🚀 eng-vie Translation Model

This is a translation model for English to Vietnamese. It provides a reliable way to translate English content into Vietnamese, with specific model details and performance metrics.

🚀 Quick Start

The eng - vie model is designed for English - Vietnamese translation. You can download the original weights and test set translations from the provided links to start using the model.

✨ Features

Language Pair: Translates from English (eng) to Vietnamese (vie and vie_Hani).
Model Type: transformer - align
Pre - processing: Normalization + SentencePiece (spm32k, spm32k)
Initial Token Requirement: A sentence initial language token in the form of >>id<< (id = valid target language ID) is required.

📦 Installation

There is no specific installation steps provided in the original document.

💻 Usage Examples

There is no code example provided in the original document.

📚 Documentation

eng - vie Model Details

Source Group: English
Target Group: Vietnamese
OPUS Readme: eng - vie
Model: transformer - align
Source Language(s): eng
Target Language(s): vie, vie_Hani
Pre - processing: normalization + SentencePiece (spm32k, spm32k)
Initial Token Requirement: A sentence initial language token in the form of >>id<< (id = valid target language ID) is required.
Download Original Weights: opus - 2020 - 06 - 17.zip
Test Set Translations: opus - 2020 - 06 - 17.test.txt
Test Set Scores: opus - 2020 - 06 - 17.eval.txt

Benchmarks

testset	BLEU	chr - F
Tatoeba - test.eng.vie	37.2	0.542

System Info

Property	Details
hf_name	eng - vie
source_languages	eng
target_languages	vie
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-vie/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['en', 'vi']
src_constituents	{'eng'}
tgt_constituents	{'vie', 'vie_Hani'}
src_multilingual	False
tgt_multilingual	False
prepro	normalization + SentencePiece (spm32k, spm32k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/eng-vie/opus-2020-06-17.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/eng-vie/opus-2020-06-17.test.txt
src_alpha3	eng
tgt_alpha3	vie
short_pair	en - vi
chrF2_score	0.542
bleu	37.2
brevity_penalty	0.973
ref_len	24427.0
src_name	English
tgt_name	Vietnamese
train_date	2020 - 06 - 17
src_alpha2	en
tgt_alpha2	vi
prefer_old	False
long_pair	eng - vie
helsinki_git_sha	480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha	2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine	brutasse
port_time	2020 - 08 - 21 - 14:41

📄 License

This project is licensed under the Apache - 2.0 license.

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