opus-mt-fr-ms Open-Source Machine Translation Model - Freely Translate from French to Multiple Malay Variants

Opus Mt Fr Ms

Developed by Helsinki-NLP

This is a Transformer-based machine translation model for French to Malay macrolanguage, supporting various Malay variants including Standard Malay and Indonesian.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Multidialect Malay Support #SentencePiece Tokenization #Tatoeba Benchmark Testing

Downloads 16

Release Time : 3/2/2022

Model Overview

This model is specifically designed for French to Malay macrolanguage translation tasks, utilizing SentencePiece tokenization technology and supporting multiple Malay dialects.

Model Features

Multidialect Support

Supports various dialect variants under the Malay macrolanguage, including Standard Malay and Indonesian.

Standardized Preprocessing

Uses standardized + SentencePiece tokenization technology (spm32k) for text preprocessing.

Language Identifier Support

Supports specifying target languages through language code identifiers.

Model Capabilities

French to Malay text translation

Supports multiple Malay dialect variants

Batch text translation

Use Cases

Multilingual Content Localization

French Content Malay Localization

Translate French website or application content into various dialects under the Malay macrolanguage.

BLEU score 35.3, chr-F score 0.617

Cross-language Communication

French-Malay Real-time Translation

Used for real-time communication translation between French and Malay speakers.

🚀 fra - msa Translation Model

This project focuses on French - Malay (macrolanguage) translation, offering a transformer - based model with detailed benchmarks and system information.

✨ Features

Language Pair: Translates from French to Malay (macrolanguage).
Model Type: Uses the transformer - align 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

Download Original Weights: You can download the original weights from opus - 2020 - 06 - 17.zip.
Test Set Translations: Access the test set translations at opus - 2020 - 06 - 17.test.txt.
Test Set Scores: Check the test set scores in opus - 2020 - 06 - 17.eval.txt.

📚 Documentation

Model Details

Source Group: French
Target Group: Malay (macrolanguage)
OPUS Readme: fra - msa

Benchmarks

Testset	BLEU	chr - F
Tatoeba - test.fra.msa	35.3	0.617

System Info

Property	Details
hf_name	fra - msa
source_languages	fra
target_languages	msa
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-msa/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['fr', 'ms']
src_constituents	{'fra'}
tgt_constituents	{'zsm_Latn', 'ind', 'max_Latn', 'zlm_Latn', 'min'}
src_multilingual	False
tgt_multilingual	False
prepro	normalization + SentencePiece (spm32k, spm32k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/fra-msa/opus-2020-06-17.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/fra-msa/opus-2020-06-17.test.txt
src_alpha3	fra
tgt_alpha3	msa
short_pair	fr - ms
chrF2_score	0.617
bleu	35.3
brevity_penalty	0.978
ref_len	6696.0
src_name	French
tgt_name	Malay (macrolanguage)
train_date	2020 - 06 - 17
src_alpha2	fr
tgt_alpha2	ms
prefer_old	False
long_pair	fra - msa
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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