EDMTranslator 0.9.0

• 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

Supported models

• FF14Translator(sappho192/ffxiv-ja-ko-translator): Japanese-to-Korean translator based on bert-base-japanese and skt-kogpt2-base-v2
• More to be added...

Quickstart

Following guide supposes that you are to use FF14Translator 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/ffxiv-ja-ko-translator/releases 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 Korean based on FF14Translator

using EDMTranslator.Tokenization;
using EDMTranslator.Translation;

// Prepare the tokenizer
var encoderVocabPath = await BertJapaneseTokenizer.HuggingFace.GetVocabFromHub("tohoku-nlp/bert-base-japanese-v2");
var hubName = "skt/kogpt2-base-v2";
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 BertJa2KoGPTTokenizer(
    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 "음, 이제 식사도 해볼까요"
    var tokens = new uint[] { 9330, 387, 12857, 9376, 18649, 9098, 7656, 6969, 8084, 1 };
    Console.WriteLine($"Input: {string.Join(", ", tokens)}");
    var decoded = tokenizer.Decode(tokens);
    Console.WriteLine($"Decoded: {decoded}");
}
TestTokenizer(tokenizer);

// Prepare the translator
string modelDir = @"D:\MODEL\ffxiv-ja-ko-translator\onnx"; // Contains encoder_model.onnx and decoder_model_merged.onnx
var translator = new FF14Translator(tokenizer, modelDir);
void TestTranslator(FF14Translator 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(FF14Translator 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)
   2. PowerShell (Recommend 7.4.2 or above)
2. Run cbuild.ps1

The build artifact will be saved in nuget directory.