Tokenizers.DotNet 0.1.0

.NET 6.0 This package targets .NET 6.0. The package is compatible with this framework or higher.
Additional Details

There's breaking changes to the library. Check following issue:
https://github.com/sappho192/Tokenizers.DotNet/issues/2

There is a newer version of this package available.
See the version list below for details. 
dotnet add package Tokenizers.DotNet --version 0.1.0                

                    
                

            
NuGet\Install-Package Tokenizers.DotNet -Version 0.1.0
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="Tokenizers.DotNet" Version="0.1.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Tokenizers.DotNet --version 0.1.0                

                    
                

            
#r "nuget: Tokenizers.DotNet, 0.1.0"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
// Install Tokenizers.DotNet as a Cake Addin
#addin nuget:?package=Tokenizers.DotNet&version=0.1.0

// Install Tokenizers.DotNet as a Cake Tool
#tool nuget:?package=Tokenizers.DotNet&version=0.1.0

Tokenizers.DotNet

.NET wrapper of HuggingFace Tokenizers library

Nuget Package list

Package main Description
Tokenizers.DotNet Nuget Tokenizers.DotNet Core library
Tokenizers.DotNet.runtime.win Nuget Tokenizers.DotNet.runtime.win Native bindings for windows x64

Requirements

  • .NET 6 or above

Supported functionalities

  • Download tokenizer files from Hugginface Hub
  • Load tokenizer file(.json) from local
  • Decode embeddings to string

How to use

(1) Install the packages

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

(2) Write the code

Check following example code:

using Tokenizers.DotNet;

var hubName = "skt/kogpt2-base-v2";
var filePath = "tokenizer.json";
var fileFullPath = await HuggingFace.GetFileFromHub(hubName, filePath, "deps");
Console.WriteLine($"Downloaded {fileFullPath}");

// Write the path of tokenizer.json to tokenizer.path.txt
var tokenizerPath = "tokenizer.path.txt";
await File.WriteAllTextAsync(tokenizerPath, fileFullPath);
Console.WriteLine($"Wrote {fileFullPath} to {tokenizerPath}");

// Create a tokenizer instance
var tokenizer = new Tokenizer();
var tokens = new uint[] { 9330, 387, 12857, 9376, 18649, 9098, 7656, 6969, 8084, 1 };
var decoded = tokenizer.Decode(tokens);
Console.WriteLine($"Decoded: {decoded}");

How to build

  1. Prepare following stuff:
    1. Rust build system (cargo)
    2. .NET build system (dotnet 6.0)
    3. PowerShell (Recommend 7.4.2 or above)
  2. Run build_all_clean.ps1
    1. To build Tokenizers.DotNet.runtime.win only, run build_rust.ps1
    2. To build Tokenizers.DotNet only, run build_dotnet.ps1

Each build artifacts will be in nuget directory.

Product Compatible and additional computed target framework versions.
.NET net6.0 is compatible.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

This package has no dependencies.

NuGet packages (1)

Showing the top 1 NuGet packages that depend on Tokenizers.DotNet:

Package Downloads
EDMTranslator

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

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