opus-mt-ru-ar Open-source Machine Translation Model - Free Russian to Multi-dialect Arabic Translation

Opus Mt Ru Ar

Developed by Helsinki-NLP

This is a Transformer-based machine translation model from Russian to Arabic, supporting multiple Arabic dialects.

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Multi-dialect Arabic support #SentencePiece tokenization #Tatoeba benchmark testing

Downloads 584

Release Time : 3/2/2022

Model Overview

This model is specifically designed for Russian-to-Arabic translation tasks, supporting various dialects including Standard Arabic, North Levantine Arabic, and Egyptian Arabic.

Model Features

Multi-dialect Support

Supports translation into multiple Arabic dialects including Standard Arabic, North Levantine Arabic, and Egyptian Arabic.

Preprocessing Optimization

Utilizes standardized preprocessing and SentencePiece tokenization (spm32k) to improve translation quality.

Target Language Identification

Requires adding target language identifiers (e.g., >>ara<<) at the beginning of sentences to specify the target dialect.

Model Capabilities

Russian-to-Arabic text translation

Multi-Arabic dialect translation

Cross-language text conversion

Use Cases

Language Services

Document Translation

Translate Russian documents into Arabic

BLEU 16.6, chr-F 0.486

Multilingual Content Creation

Create translated versions of Russian content for Arabic readers

Education

Language Learning Assistance

Help Russian or Arabic learners understand the other language

🚀 rus-ara Translation Model

This project focuses on Russian to Arabic translation, leveraging a transformer model. It provides detailed information about the model, including pre - processing steps, download links, and benchmark scores.

🚀 Quick Start

This model is designed for Russian to Arabic translation. You can download the original weights and test set translations from the provided links.

✨ Features

Language Pair: Translates from Russian to Arabic.
Model Type: Utilizes a transformer model.
Pre - processing: Applies normalization and SentencePiece (spm32k,spm32k).
Language Token Requirement: A sentence initial language token in the form of >>id<< (id = valid target language ID) is required.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

No code examples are provided in the original document.

📚 Documentation

Model Information

Property	Details
Source Group	Russian
Target Group	Arabic
OPUS Readme	rus-ara
Model Type	Transformer
Source Language(s)	rus
Target Language(s)	apc, ara, arz
Pre - processing	normalization + SentencePiece (spm32k,spm32k)
Language Token Requirement	A sentence initial language token in the form of `>>id<<` (id = valid target language ID) is required
Download Original Weights	opus-2020-07-03.zip
Test Set Translations	opus-2020-07-03.test.txt
Test Set Scores	opus-2020-07-03.eval.txt

Benchmarks

testset	BLEU	chr-F
Tatoeba-test.rus.ara	16.6	0.486

System Info

Property	Details
hf_name	rus-ara
source_languages	rus
target_languages	ara
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/rus-ara/README.md
original_repo	Tatoeba-Challenge
tags	['translation']
languages	['ru', 'ar']
src_constituents	{'rus'}
tgt_constituents	{'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'}
src_multilingual	False
tgt_multilingual	False
prepro	normalization + SentencePiece (spm32k,spm32k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/rus-ara/opus-2020-07-03.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/rus-ara/opus-2020-07-03.test.txt
src_alpha3	rus
tgt_alpha3	ara
short_pair	ru-ar
chrF2_score	0.486
bleu	16.6
brevity_penalty	0.9690000000000001
ref_len	18878.0
src_name	Russian
tgt_name	Arabic
train_date	2020 - 07 - 03
src_alpha2	ru
tgt_alpha2	ar
prefer_old	False
long_pair	rus-ara
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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