Microsoft.ML.Tokenizers 1.0.0

Prefix Reserved
dotnet add package Microsoft.ML.Tokenizers --version 1.0.0                
NuGet\Install-Package Microsoft.ML.Tokenizers -Version 1.0.0                
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="Microsoft.ML.Tokenizers" Version="1.0.0" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Microsoft.ML.Tokenizers --version 1.0.0                
#r "nuget: Microsoft.ML.Tokenizers, 1.0.0"                
#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 Microsoft.ML.Tokenizers as a Cake Addin
#addin nuget:?package=Microsoft.ML.Tokenizers&version=1.0.0

// Install Microsoft.ML.Tokenizers as a Cake Tool
#tool nuget:?package=Microsoft.ML.Tokenizers&version=1.0.0                

About

Microsoft.ML.Tokenizers supports various the implementation of the tokenization used in the NLP transforms.

Key Features

  • Extensible tokenizer architecture that allows for specialization of Normalizer, PreTokenizer, Model/Encoder, Decoder
  • BPE - Byte pair encoding model
  • English Roberta model
  • Tiktoken model
  • Llama model
  • Phi2 model

How to Use

using Microsoft.ML.Tokenizers;
using System.Net.Http;
using System.IO;

//
// Using Tiktoken Tokenizer
//

// initialize the tokenizer for `gpt-4` model
Tokenizer tokenizer = TiktokenTokenizer.CreateForModel("gpt-4");

string source = "Text tokenization is the process of splitting a string into a list of tokens.";

Console.WriteLine($"Tokens: {tokenizer.CountTokens(source)}");
// print: Tokens: 16

var trimIndex = tokenizer.GetIndexByTokenCountFromEnd(source, 5, out string processedText, out _);
Console.WriteLine($"5 tokens from end: {processedText.Substring(trimIndex)}");
// 5 tokens from end:  a list of tokens.

trimIndex = tokenizer.GetIndexByTokenCount(source, 5, out processedText, out _);
Console.WriteLine($"5 tokens from start: {processedText.Substring(0, trimIndex)}");
// 5 tokens from start: Text tokenization is the

IReadOnlyList<int> ids = tokenizer.EncodeToIds(source);
Console.WriteLine(string.Join(", ", ids));
// prints: 1199, 4037, 2065, 374, 279, 1920, 315, 45473, 264, 925, 1139, 264, 1160, 315, 11460, 13

//
// Using Llama Tokenizer
//

// Open stream of remote Llama tokenizer model data file
using HttpClient httpClient = new();
const string modelUrl = @"https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer.model";
using Stream remoteStream = await httpClient.GetStreamAsync(modelUrl);

// Create the Llama tokenizer using the remote stream
Tokenizer llamaTokenizer = LlamaTokenizer.Create(remoteStream);
string input = "Hello, world!";
ids = llamaTokenizer.EncodeToIds(input);
Console.WriteLine(string.Join(", ", ids));
// prints: 1, 15043, 29892, 3186, 29991

Console.WriteLine($"Tokens: {llamaTokenizer.CountTokens(input)}");
// print: Tokens: 5

Main Types

The main types provided by this library are:

  • Microsoft.ML.Tokenizers.Tokenizer
  • Microsoft.ML.Tokenizers.BpeTokenizer
  • Microsoft.ML.Tokenizers.EnglishRobertaTokenizer
  • Microsoft.ML.Tokenizers.TiktokenTokenizer
  • Microsoft.ML.Tokenizers.Normalizer
  • Microsoft.ML.Tokenizers.PreTokenizer

Additional Documentation

Feedback & Contributing

Microsoft.ML.Tokenizers is released as open source under the MIT license. Bug reports and contributions are welcome at the GitHub repository.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  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 is compatible.  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. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (18)

Showing the top 5 NuGet packages that depend on Microsoft.ML.Tokenizers:

Package Downloads
Microsoft.KernelMemory.Core

The package contains the the core logic and abstractions of Kernel Memory, not including extensions.

Microsoft.KernelMemory.AI.OpenAI

Provide access to OpenAI LLM models in Kernel Memory to generate embeddings and text

Microsoft.ML.TorchSharp

Microsoft.ML.TorchSharp contains ML.NET integration of TorchSharp.

Microsoft.KernelMemory.AI.TikToken

Provide TikToken tokenizers in Kernel Memory

Microsoft.Teams.AI

SDK focused on building AI based applications for Microsoft Teams.

GitHub repositories (10)

Showing the top 5 popular GitHub repositories that depend on Microsoft.ML.Tokenizers:

Repository Stars
microsoft/semantic-kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
microsoft/kernel-memory
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
microsoft/teams-ai
SDK focused on building AI based applications and extensions for Microsoft Teams and other Bot Framework channels
dotnet/ai-samples
axzxs2001/Asp.NetCoreExperiment
原来所有项目都移动到**OleVersion**目录下进行保留。新的案例装以.net 5.0为主,一部分对以前案例进行升级,一部分将以前的工作经验总结出来,以供大家参考!
Version Downloads Last updated
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