Opus-MT Tr-AR Open-Source Machine Translation Model - Free Turkish to Arabic and Variants Translation

Opus Mt Tr Ar

Developed by Helsinki-NLP

This is a machine translation model based on Transformer architecture, specifically designed for translating Turkish into Arabic and its variants.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Multidialectal Arabic support #SentencePiece tokenization #Low-resource language translation

Downloads 273

Release Time : 3/2/2022

Model Overview

This model supports translation tasks from Turkish to Arabic and its multiple variants, using SentencePiece tokenization for preprocessing.

Model Features

Multi-Arabic variant support

Supports translation for multiple Arabic variants, including Standard Arabic and dialectal variants.

Standardized preprocessing

Uses standardization and SentencePiece tokenization for text preprocessing.

Target language identifier

Requires adding target language identifiers at the beginning of sentences to specify translation target variants.

Model Capabilities

Turkish to Arabic text translation

Supports translation for multiple Arabic variants

Use Cases

Cross-language communication

Turkish-Arabic text translation

Translate Turkish text into Arabic or its variants

BLEU 14.9, chr-F 0.455 (on Tatoeba test set)

Language learning

Language learning aid

Assists students learning Turkish or Arabic in understanding the correspondence between the two languages

🚀 tur-ara Translation Model

This is a translation model that translates from Turkish to Arabic, offering high - quality translation services.

🚀 Quick Start

This model is designed for Turkish - Arabic translation. You can download the original weights and test set translations from the provided links to start using it.

✨ Features

Model Type: Transformer
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.

📦 Installation

There is no specific installation command provided in the original document, so this section is skipped.

💻 Usage Examples

There is no code example provided in the original document, so this section is skipped.

📚 Documentation

Model Information

Source Group: Turkish
Target Group: Arabic
OPUS Readme: tur - ara
Model: transformer
Source Language(s): tur
Target Language(s): apc_Latn, ara, ara_Latn, arq_Latn
Pre - processing: normalization + SentencePiece (spm32k,spm32k)
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.tur.ara	14.9	0.455

System Info

Property	Details
hf_name	tur - ara
source_languages	tur
target_languages	ara
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/tur-ara/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['tr', 'ar']
src_constituents	{'tur'}
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/tur-ara/opus-2020-07-03.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/tur-ara/opus-2020-07-03.test.txt
src_alpha3	tur
tgt_alpha3	ara
short_pair	tr - ar
chrF2_score	0.455
bleu	14.9
brevity_penalty	0.988
ref_len	6944.0
src_name	Turkish
tgt_name	Arabic
train_date	2020 - 07 - 03
src_alpha2	tr
tgt_alpha2	ar
prefer_old	False
long_pair	tur - ara
helsinki_git_sha	480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha	2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine	brutasse
port_time	2020 - 08 - 21 - 14:41

🔧 Technical Details

There is no specific technical implementation details (more than 50 words) provided in the original document, so this section is skipped.

📄 License

This project is licensed under the Apache - 2.0 license.

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