Microsoft.ML.OnnxRuntimeGenAI.Cuda 0.5.2

Prefix Reserved
.NET 8.0 This package targets .NET 8.0. The package is compatible with this framework or higher. .NET Standard 2.0 This package targets .NET Standard 2.0. The package is compatible with this framework or higher. 
dotnet add package Microsoft.ML.OnnxRuntimeGenAI.Cuda --version 0.5.2                

                    
                

            
NuGet\Install-Package Microsoft.ML.OnnxRuntimeGenAI.Cuda -Version 0.5.2
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.OnnxRuntimeGenAI.Cuda" Version="0.5.2" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Microsoft.ML.OnnxRuntimeGenAI.Cuda --version 0.5.2                

                    
                

            
#r "nuget: Microsoft.ML.OnnxRuntimeGenAI.Cuda, 0.5.2"
#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.OnnxRuntimeGenAI.Cuda as a Cake Addin
#addin nuget:?package=Microsoft.ML.OnnxRuntimeGenAI.Cuda&version=0.5.2

// Install Microsoft.ML.OnnxRuntimeGenAI.Cuda as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxRuntimeGenAI.Cuda&version=0.5.2

About

Run Llama, Phi (Language + Vision!), Gemma, Mistral with ONNX Runtime.

This API gives you an easy, flexible and performant way of running LLMs on device using .NET/C#.

It implements the generative AI loop for ONNX models, including pre and post processing, inference with ONNX Runtime, logits processing, search and sampling, and KV cache management.

You can call a high level generate() method to generate all of the output at once, or stream the output one token at a time.

Key Features

  • Language and vision pre and post processing
  • Inference using ONNX Runtime
  • Generation tuning with greedy, beam search and random sampling
  • KV cache management to optimize performance
  • Multi target execution (CPU, GPU, with NPU coming!)

Sample

// See https://aka.ms/new-console-template for more information
using Microsoft.ML.OnnxRuntimeGenAI;

using OgaHandle ogaHandle = new OgaHandle();

// Specify the location of your downloaded model.
// Many models are published on HuggingFace e.g. 
// https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-onnx
string modelPath = "..."
Console.WriteLine("Model path: " + modelPath);

using Model model = new Model(modelPath);
using Tokenizer tokenizer = new Tokenizer(model);

// Set your prompt here
string prompt = "public static bool IsPrime(int number)";
var sequences = tokenizer.Encode($"<|user|>{prompt}<|end|><|assistant|>");

using GeneratorParams generatorParams = new GeneratorParams(model);
generatorParams.SetSearchOption("max_length", 512);
generatorParams.SetInputSequences(sequences);

using var tokenizerStream = tokenizer.CreateStream();
using var generator = new Generator(model, generatorParams);
while (!generator.IsDone())
{
    generator.ComputeLogits();
    generator.GenerateNextToken();
    Console.Write(tokenizerStream.Decode(generator.GetSequence(0)[^1]));
}

Generates the following output:

Here's a complete implementation of the `IsPrime` function in C# that checks if a given number is prime. The function includes basic input validation and comments for clarity.

using System;

namespace PrimeChecker
{
    public class PrimeChecker
    {
        /// <summary>
        /// Checks if the given number is prime.
        /// </summary>
        /// <param name="number">The number to check.</param>
        /// <returns>true if the number is prime; otherwise, false.</returns>
        public static bool IsPrime(int number)
        {
            // Input validation
            if (number < 2)
            {
                return false;
            }

            // 2 is the only even prime number
            if (number == 2)
            {
                return true;
            }

            // Exclude even numbers greater than 2
            if (number % 2 == 0)
            {
                return false;
            }

            // Check for factors up to the square root of the number
            int limit = (int)Math.Floor(Math.Sqrt(number));
            for (int i = 3; i <= limit; i += 2)
            {
                if (number % i == 0)
                {
                    return false;
                }
            }

            return true;
        }

        static void Main(string[] args)
        {
            int number = 29;
            bool isPrime = PrimeChecker.IsPrime(number);

            Console.WriteLine($"Is {number} prime? {isPrime}");
        }
    }
}

This implementation checks if a number is prime by iterating only up to the square root of the number, which is an optimization over checking all numbers up to the number itself. It also excludes even numbers greater than 2, as they cannot be prime.

Source code repository

ONNX Runtime is an open source project. See:

  • (ONNX Runtime)[https://github.com/microsoft/onnxruntime]
  • (ONNX Runtime GenAI)[https://github.com/microsoft/onnxruntime-genai]

Documentation

See (ONNX Runtime GenAI Documentation)[https://onxxruntime.ai/docs/genai]

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-android31.0 is compatible.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-ios15.4 is compatible.  net8.0-maccatalyst was computed.  net8.0-maccatalyst14.0 is compatible.  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. 
native native is compatible. 
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 (1)

Showing the top 1 NuGet packages that depend on Microsoft.ML.OnnxRuntimeGenAI.Cuda:

Package Downloads
feiyun0112.SemanticKernel.Connectors.OnnxRuntimeGenAI.CUDA

Semantic Kernel connector for Microsoft.ML.OnnxRuntimeGenAI.

GitHub repositories (2)

Showing the top 2 popular GitHub repositories that depend on Microsoft.ML.OnnxRuntimeGenAI.Cuda:

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microsoft/semantic-kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
lindexi/lindexi_gd
博客用到的代码
Version Downloads Last updated
0.5.2 972 11/25/2024
0.5.1 870 11/15/2024
0.5.0 466 11/7/2024
0.4.0 3,304 8/21/2024
0.4.0-rc1 262 8/14/2024
0.3.0 5,894 6/21/2024
0.3.0-rc2 7,689 5/29/2024
0.3.0-rc1 834 5/22/2024
0.2.0 1,765 5/20/2024
0.2.0-rc7 1,376 5/14/2024
0.2.0-rc6 1,843 5/4/2024
0.2.0-rc4 2,316 4/25/2024
0.2.0-rc3 241 4/24/2024
0.1.0 384 4/8/2024
0.1.0-rc4 286 3/27/2024

Release Def:
Branch: refs/heads/rel-0.5.2
Commit: 27bcf6c5e94bff5d6b44e7feb8090b55521d7808