• EDMTranslator
• Nuget Package list
• Requirements
• Supported models
• Quickstart
  • Install the packages
  • Prepare the required data
    • Japanese dictionary
    • Fine-tuned translator model
  • Implement the driver code
• How to build

EDMTranslator

Text translator library based on LLM models, especially EncoderDecoderModel in HuggingFace

Nuget Package list

Package	repo	description
EDMTranslator		Main library

Requirements

• .NET 6 or above
• Free RAM spaces at least 3.5GB before running the translator

Supported models

• JESCJaEnTranslator(sappho192/jesc-ja-en-translator): Japanese-to-English translator based on tohoku-nlp/bert-base-japanese-v2 and openai-community/gpt2, fine-tuned with JESC dataset
• FF14JaKoTranslator(sappho192/ffxiv-ja-ko-translator): Japanese-to-Korean translator based on tohoku-nlp/bert-base-japanese-v2 and skt/kogpt2-base-v2, fine-tuned with FF14 dataset
• AihubJaKoTranslator(sappho192/aihub-ja-ko-translator): Japanese-to-Korean translator based on tohoku-nlp/bert-base-japanese-v2 and skt/kogpt2-base-v2, fine-tuned with AIHub dataset
• More to be added...

Quickstart

Following guide supposes that you are to use JESCJaEnTranslator mentioned above.

Install the packages

1. From the NuGet, install EDMTranslator package
2. And then, install Tokenizers.DotNet.runtime.win package too

Prepare the required data

Japanese dictionary

• Download unidic mecab dictionary unidic-mecab-2.1.2_bin.zip from https://clrd.ninjal.ac.jp/unidic_archive/cwj/2.1.2/ and unzip the archive into somewhere

Fine-tuned translator model

• Download the translator model from sappho192/jesc-ja-en-translator (especially onnx_jesc-ja-en.7z) and unzip the archive into somewhere

Implement the driver code

Write the code like below and you are good to go 🫡 Note that you need to fix the path of encoderDictDir and modelDir correctly.

// Console application which translates Japanese sentence to English with JESCJaEnTranslator using EDMTranslator.Tokenization; using EDMTranslator.Translation; // Prepare the tokenizer var encoderVocabPath = await BertJapaneseTokenizer.HuggingFace.GetVocabFromHub("tohoku-nlp/bert-base-japanese-v2"); var hubName = "openai-community/gpt2"; var decoderVocabFilename = "tokenizer.json"; var decoderVocabPath = await Tokenizers.DotNet.HuggingFace.GetFileFromHub(hubName, decoderVocabFilename, "deps"); string encoderDictDir = @"D:\DATASET\unidic-mecab-2.1.2_bin"; var tokenizer = new BertJa2GPTTokenizer( encoderDictDir: encoderDictDir, encoderVocabPath: encoderVocabPath, decoderVocabPath: decoderVocabPath); void TestTokenizer(ITokenizer tokenizer) { Console.WriteLine("--Tokenizer test--"); Console.WriteLine("[Encode]"); var sentenceJa = "打ち合わせが終わった後にご飯を食べましょう。"; Console.WriteLine($"Input: {sentenceJa}"); var (embeddingsJa, attentionMask) = tokenizer.Encode(sentenceJa); Console.WriteLine($"Encoded: {string.Join(", ", embeddingsJa)}"); Console.WriteLine("[Decode]"); // Tokens of "i was nervous before the exam, and i had a fever." var tokens = new uint[] { 72, 373, 10927, 878, 262, 2814, 11, 290, 1312, 550, 257, 17372, 13 }; Console.WriteLine($"Input: {string.Join(", ", tokens)}"); var decoded = tokenizer.Decode(tokens); Console.WriteLine($"Decoded: {decoded}"); } TestTokenizer(tokenizer); // Prepare the translator string modelDir = @"D:\MODEL\jesc-ja-en-translator\onnx"; // The folder should contains encoder_model.onnx and decoder_model_merged.onnx var translator = new JESCJaEnTranslator(tokenizer, modelDir); void TestTranslator(JESCJaEnTranslator translator) { Console.WriteLine("--Translator test--"); Translate(translator, "打ち合わせが終わった後にご飯を食べましょう。"); Translate(translator, "試験前に緊張したあまり、熱がでてしまった。"); Translate(translator, "山田は英語にかけてはクラスの誰にも負けない。"); Translate(translator, "この本によれば、最初の人工橋梁は新石器時代にさかのぼるという。"); } TestTranslator(translator); static void Translate(JESCJaEnTranslator translator, string sentence) { Console.WriteLine($"SourceText: {sentence}"); string translated = translator.Translate(sentence); Console.WriteLine($"Translated: {translated}"); }

How to build

1. Prepare following stuff:
   1. .NET build system (dotnet 6.0, 7.0, 8.0)
   2. PowerShell (Recommend 7.4.2 or above)
2. Run cbuild.ps1

The build artifact will be saved in nuget directory.