opus-mt-en-he Open-source Machine Translation Model - Achieve Accurate English to Hebrew Translation for Free

Opus Mt En He

Developed by tiedeman

This is an English-to-Hebrew machine translation model based on the Transformer architecture, developed by the Helsinki-NLP team as part of the Tatoeba Challenge project.

Machine Translation Supports Multiple LanguagesOpen Source License:Apache-2.0 #High-precision translation #Multilingual support #Standardized preprocessing

Downloads 19

Release Time : 3/2/2022

Model Overview

This model is specifically designed for translating English text into Hebrew, utilizing standardized preprocessing and SentencePiece tokenization techniques.

Model Features

High-quality translation

Achieved 37.9 BLEU score and 0.602 chr-F score on the Tatoeba test set

Standardized preprocessing

Utilizes standardization and SentencePiece tokenization (spm32k) for text preprocessing

Open-source license

Uses Apache-2.0 license, allowing for both commercial and research use

Model Capabilities

English-to-Hebrew text translation

Processing standardized text input

Support for SentencePiece tokenization

Use Cases

Language learning

Language learning assistance

Helps English learners understand Hebrew text

Content localization

Website content translation

Translates English website content into Hebrew

🚀 English-Hebrew Translation Model

This project focuses on English-Hebrew translation, leveraging a Transformer model. It provides translation capabilities between English and Hebrew, with pre - processing steps and evaluation scores.

🚀 Quick Start

The model is designed for English-Hebrew translation. You can download the original weights and test set translations from the provided links to start using the model.

✨ Features

Language Pair: Supports translation from English (eng) to Hebrew (heb).
Model Type: Utilizes a Transformer model.
Pre - processing: Applies normalization and SentencePiece (spm32k, spm32k) for pre - processing.

📦 Installation

To use this model, you need to download the original weights: opus-2020-10-04.zip

📚 Documentation

Model Details

Source Group: English
Target Group: Hebrew
OPUS Readme: eng-heb

Benchmarks

testset	BLEU	chr-F
Tatoeba-test.eng.heb	37.9	0.602

System Info

Property	Details
hf_name	en-he
source_languages	eng
target_languages	heb
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-heb/README.md
original_repo	Tatoeba-Challenge
tags	['translation']
languages	['en', 'he']
src_constituents	('English', {'eng'})
tgt_constituents	('Hebrew', {'heb'})
src_multilingual	False
tgt_multilingual	False
long_pair	eng-heb
prepro	normalization + SentencePiece (spm32k,spm32k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/eng-heb/opus-2020-10-04.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/eng-heb/opus-2020-10-04.test.txt
src_alpha3	eng
tgt_alpha3	heb
chrF2_score	0.602
bleu	37.9
brevity_penalty	1.0
ref_len	60359.0
src_name	English
tgt_name	Hebrew
train_date	2020-10-04 00:00:00
src_alpha2	en
tgt_alpha2	he
prefer_old	False
short_pair	en-he
helsinki_git_sha	61fd6908b37d9a7b21cc3e27c1ae1fccedc97561
transformers_git_sha	d99ed7ad618037ae878f0758157ed0764bd7f935
port_machine	LM0-400-22516.local
port_time	2020-10-15-16:31

📄 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