Opus-mt-ar-he Open-source Machine Translation Model - Supports Multiple Dialects, Freely Achieve Arabic to Hebrew Translation

Opus Mt Ar He

Developed by Helsinki-NLP

This is a Transformer-based machine translation model for Arabic to Hebrew, supporting multiple Arabic dialect variants.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Multi-dialect Arabic support #High-precision translation #SentencePiece preprocessing

Downloads 94

Release Time : 3/2/2022

Model Overview

This model is specifically designed for Arabic (including various dialects) to Hebrew translation tasks, employing standardized preprocessing and SentencePiece tokenization techniques.

Model Features

Multi-dialect Support

Supports translation for multiple Arabic dialects including North Levantine Arabic, Algerian Arabic, and Egyptian Arabic.

Standardized Preprocessing

Utilizes standardized preprocessing and SentencePiece tokenization to enhance translation quality.

High-precision Translation

Achieves high scores of 40.4 BLEU and 0.605 chr-F on the Tatoeba test set.

Model Capabilities

Arabic to Hebrew text translation

Multi-dialect Arabic processing

Standardized text preprocessing

Use Cases

Cross-language Communication

Arabic-Hebrew Real-time Translation

Used for real-time communication translation between Arabic and Hebrew speakers.

Content Localization

Arabic Content Localization in Hebrew

Translates Arabic content into Hebrew for website, application, and other content localization purposes.

🚀 ara-heb

This project focuses on Arabic to Hebrew translation. It provides a transformer-based model with specific pre - processing steps and offers various evaluation metrics and related resources.

🚀 Quick Start

This project aims to perform translation tasks from Arabic to Hebrew. You can download the original weights and test set translations from the provided links for further exploration.

✨ Features

Language Pair: Translates from Arabic to Hebrew.
Model Type: Utilizes a transformer model.
Pre - processing: Applies normalization and SentencePiece (spm32k, spm32k).

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

No code examples are provided in the original document.

📚 Documentation

ara - heb Details

Source Group: Arabic
Target Group: Hebrew
OPUS Readme: ara - heb
Model: Transformer
Source Language(s): apc, apc_Latn, ara, arq, arz
Target Language(s): heb
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.ara.heb	40.4	0.605

System Info

Property	Details
hf_name	ara - heb
source_languages	ara
target_languages	heb
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-heb/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['ar', 'he']
src_constituents	{'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'}
tgt_constituents	{'heb'}
src_multilingual	False
tgt_multilingual	False
prepro	normalization + SentencePiece (spm32k, spm32k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/ara-heb/opus-2020-07-03.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/ara-heb/opus-2020-07-03.test.txt
src_alpha3	ara
tgt_alpha3	heb
short_pair	ar - he
chrF2_score	0.605
bleu	40.4
brevity_penalty	1.0
ref_len	6801.0
src_name	Arabic
tgt_name	Hebrew
train_date	2020 - 07 - 03
src_alpha2	ar
tgt_alpha2	he
prefer_old	False
long_pair	ara - heb
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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