Opus-mt-de-ar Open-Source Translation Model - Freely Supports Translation from German to Multiple Arabic Dialects

Opus Mt De Ar

Developed by Helsinki-NLP

This is a German-to-Arabic translation model based on the transformer-align architecture, supporting multiple Arabic dialect variants.

Machine Translation

Transformers

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

Downloads 292

Release Time : 3/2/2022

Model Overview

This model specializes in German-to-Arabic machine translation tasks, utilizing standardized preprocessing and SentencePiece tokenization techniques, supporting target languages including Standard Arabic and various dialects.

Model Features

Multi-dialect support

Supports translation into multiple Arabic dialect variants, including Gulf Arabic, Egyptian Arabic, etc.

Standardized preprocessing

Employs standardized and SentencePiece tokenization techniques for text preprocessing

Language identifiers

Supports specifying target language variants through specially formatted identifiers

Model Capabilities

German-to-Arabic text translation

Multi-dialect Arabic translation

Cross-language text conversion

Use Cases

Language services

Document translation

Translate German documents into Standard Arabic or specific dialects

Translation quality of BLEU 19.7/chr-F 0.486

Cross-cultural communication

Facilitate basic communication between German and Arabic speakers

🚀 deu-ara Translation Model

This project focuses on German to Arabic translation, offering a high - quality translation solution with specific model and evaluation metrics.

✨ Features

Language Pair: Translates from German (deu) to multiple Arabic variants including afb, apc, ara, ara_Latn, arq, arz.
Model Type: Utilizes the transformer - align model.
Pre - processing: Applies normalization and SentencePiece (spm32k, spm32k) techniques.
Language Token Requirement: A sentence initial language token in the form of >>id<< (where id is a valid target language ID) is required.

📦 Installation

The README does not provide specific installation steps, so this section is skipped.

💻 Usage Examples

The README does not contain code examples, so this section is skipped.

📚 Documentation

Model Information

Source Group: German
Target Group: Arabic
OPUS Readme: deu - ara
Model: transformer - align
Pre - processing: normalization + SentencePiece (spm32k,spm32k)

Download Links

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.deu.ara	19.7	0.486

System Info

Property	Details
hf_name	deu - ara
source_languages	deu
target_languages	ara
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-ara/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['de', 'ar']
src_constituents	{'deu'}
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/deu-ara/opus-2020-07-03.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ara/opus-2020-07-03.test.txt
src_alpha3	deu
tgt_alpha3	ara
short_pair	de - ar
chrF2_score	0.486
bleu	19.7
brevity_penalty	0.993
ref_len	6324.0
src_name	German
tgt_name	Arabic
train_date	2020 - 07 - 03
src_alpha2	de
tgt_alpha2	ar
prefer_old	False
long_pair	deu - ara
helsinki_git_sha	480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha	2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine	brutasse
port_time	2020 - 08 - 21 - 14:41

🔧 Technical Details

The README does not provide in - depth technical implementation details, so this section is skipped.

📄 License

This project is licensed under the Apache 2.0 license.

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご