Opus-mt-de-ZH Open-Source Machine Translation Model - Free Translation from German to Multiple Chinese Variants

Opus Mt De ZH

Developed by Helsinki-NLP

This is a Transformer-based German to Chinese multi-dialect machine translation model, supporting various Chinese variants including Mandarin, Simplified Chinese, Cantonese, and Traditional Chinese.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #German to Chinese Variants Translation #SentencePiece Tokenization #Target Language Identifier

Downloads 1,109

Release Time : 3/2/2022

Model Overview

Developed by the Helsinki-NLP team and trained using the OPUS dataset, this model can translate German text into multiple Chinese dialects. It employs SentencePiece for tokenization and requires the addition of target language identifiers before input.

Model Features

Multi-Dialect Support

Supports translation into various Chinese variants including Mandarin, Simplified Chinese, Cantonese, and Traditional Chinese.

Standardized Preprocessing

Uses standardized preprocessing and SentencePiece tokenization for input text.

Target Language Identification

Specifies the target language by adding a target language code (e.g., >>zh<<) at the beginning of the sentence.

Model Capabilities

German to Chinese Text Translation

Multi-Dialect Chinese Output

Cross-Language Conversion

Use Cases

Language Services

Document Translation

Translate German documents into various Chinese dialect versions.

Multilingual Content Generation

Generate content in different dialects for Chinese users.

Education

Language Learning Assistance

Help German learners understand Chinese content.

🚀 opus-mt-de-ZH

opus-mt-de-ZH is a translation model that supports translating German into multiple Chinese dialects and variants, offering a convenient solution for cross - language communication.

✨ Features

Multi - target Languages: Supports multiple Chinese target languages, including Mandarin (cmn), Cantonese (yue), and various regional variants.
OPUS Dataset: Trained on the OPUS dataset, which ensures high - quality and diverse training data.
Transformer - Align Model: Utilizes the transformer - align model architecture for efficient and accurate translations.
Pre - processing: Applies normalization and SentencePiece for pre - processing, improving the model's performance.
Language Token Requirement: Requires a sentence - initial language token in the form of >>id<< (id = valid target language ID).

📦 Installation

No specific installation steps are provided in the original document.

📚 Documentation

General Information

Source Languages: de
Target Languages: cmn, cn, yue, ze_zh, zh_cn, zh_CN, zh_HK, zh_tw, zh_TW, zh_yue, zhs, zht, zh
OPUS Readme: [de - cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh](https://github.com/Helsinki - NLP/OPUS - MT - train/blob/master/models/de - cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/README.md)
Dataset: opus
Model: transformer - align
Pre - processing: normalization + SentencePiece

Download Links

Original Weights: [opus - 2020 - 01 - 20.zip](https://object.pouta.csc.fi/OPUS - MT - models/de - cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus - 2020 - 01 - 20.zip)
Test Set Translations: [opus - 2020 - 01 - 20.test.txt](https://object.pouta.csc.fi/OPUS - MT - models/de - cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus - 2020 - 01 - 20.test.txt)
Test Set Scores: [opus - 2020 - 01 - 20.eval.txt](https://object.pouta.csc.fi/OPUS - MT - models/de - cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus - 2020 - 01 - 20.eval.txt)

📄 License

This project is licensed under the Apache - 2.0 license.

🔧 Technical Details

No detailed technical implementation details are provided in the original document.

📊 Benchmarks

Testset	BLEU	chr - F
bible - uedin.de.zh	24.4	0.335

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