LLamaSharp 0.4.1-preview

This is a prerelease version of LLamaSharp.
There is a newer version of this package available.
See the version list below for details.
dotnet add package LLamaSharp --version 0.4.1-preview                
NuGet\Install-Package LLamaSharp -Version 0.4.1-preview                
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="LLamaSharp" Version="0.4.1-preview" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add LLamaSharp --version 0.4.1-preview                
#r "nuget: LLamaSharp, 0.4.1-preview"                
#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 LLamaSharp as a Cake Addin
#addin nuget:?package=LLamaSharp&version=0.4.1-preview&prerelease

// Install LLamaSharp as a Cake Tool
#tool nuget:?package=LLamaSharp&version=0.4.1-preview&prerelease                

LLamaSharp - .NET Binding for llama.cpp

logo

Discord QQ Group LLamaSharp Badge LLamaSharp Badge LLamaSharp Badge LLamaSharp Badge

The C#/.NET binding of llama.cpp. It provides APIs to inference the LLaMa Models and deploy it on local environment. It works on both Windows, Linux and MAC without requirment for compiling llama.cpp yourself. Its performance is close to llama.cpp.

Furthermore, it provides integrations with other projects such as BotSharp to provide higher-level applications and UI.

Documentation

Installation

Firstly, search LLamaSharp in nuget package manager and install it.

PM> Install-Package LLamaSharp

Then, search and install one of the following backends:

LLamaSharp.Backend.Cpu
LLamaSharp.Backend.Cuda11
LLamaSharp.Backend.Cuda12

Here's the mapping of them and corresponding model samples provided by LLamaSharp. If you're not sure which model is available for a version, please try our sample model.

LLamaSharp.Backend LLamaSharp Verified Model Resources llama.cpp commit id
- v0.2.0 This version is not recommended to use. -
- v0.2.1 WizardLM, Vicuna (filenames with "old") -
v0.2.2 v0.2.2, v0.2.3 WizardLM, Vicuna (filenames without "old") 63d2046
v0.3.0, v0.3.1 v0.3.0, v0.4.0 LLamaSharpSamples v0.3.0, WizardLM 7e4ea5b

We publish the backend with cpu, cuda11 and cuda12 because they are the most popular ones. If none of them matches, please compile the llama.cpp from source and put the libllama under your project's output path. When building from source, please add -DBUILD_SHARED_LIBS=ON to enable the library generation.

FAQ

  1. GPU out of memory: Please try setting n_gpu_layers to a smaller number.
  2. Unsupported model: llama.cpp is under quick development and often has break changes. Please check the release date of the model and find a suitable version of LLamaSharp to install, or use the model we provide on huggingface.

Usages

Model Inference and Chat Session

LLamaSharp provides two ways to run inference: LLamaExecutor and ChatSession. The chat session is a higher-level wrapping of the executor and the model. Here's a simple example to use chat session.

using LLama.Common;
using LLama;

string modelPath = "<Your model path>" // change it to your own model path
var prompt = "Transcript of a dialog, where the User interacts with an Assistant named Bob. Bob is helpful, kind, honest, good at writing, and never fails to answer the User's requests immediately and with precision.\r\n\r\nUser: Hello, Bob.\r\nBob: Hello. How may I help you today?\r\nUser: Please tell me the largest city in Europe.\r\nBob: Sure. The largest city in Europe is Moscow, the capital of Russia.\r\nUser:"; // use the "chat-with-bob" prompt here.

// Initialize a chat session
var ex = new InteractiveExecutor(new LLamaModel(new ModelParams(modelPath, contextSize: 1024, seed: 1337, gpuLayerCount: 5)));
ChatSession session = new ChatSession(ex);

// show the prompt
Console.WriteLine();
Console.Write(prompt);

// run the inference in a loop to chat with LLM
while (prompt != "stop")
{
    foreach (var text in session.Chat(prompt, new InferenceParams() { Temperature = 0.6f, AntiPrompts = new List<string> { "User:" } }))
    {
        Console.Write(text);
    }
    prompt = Console.ReadLine();
}

// save the session
session.SaveSession("SavedSessionPath");
Quantization

The following example shows how to quantize the model. With LLamaSharp you needn't to compile c++ project and run scripts to quantize the model, instead, just run it in C#.

string srcFilename = "<Your source path>";
string dstFilename = "<Your destination path>";
string ftype = "q4_0";
if(Quantizer.Quantize(srcFileName, dstFilename, ftype))
{
    Console.WriteLine("Quantization succeed!");
}
else
{
    Console.WriteLine("Quantization failed!");
}

For more usages, please refer to Examples.

Web API

We provide the integration of ASP.NET core here. Since currently the API is not stable, please clone the repo and use it. In the future we'll publish it on NuGet.

Since we are in short of hands, if you're familiar with ASP.NET core, we'll appreciate it if you would like to help upgrading the Web API integration.

Demo

demo-console

Roadmap


✅: completed. ⚠️: outdated for latest release but will be updated. 🔳: not completed


✅ LLaMa model inference

✅ Embeddings generation, tokenization and detokenization

✅ Chat session

✅ Quantization

✅ State saving and loading

⚠️ BotSharp Integration

⚠️ ASP.NET core Integration

⚠️ Semantic-kernel Integration

🔳 MAUI Integration

🔳 Follow up llama.cpp and improve performance

Assets

Some extra model resources could be found below:

The weights included in the magnet is exactly the weights from Facebook LLaMa.

The prompts could be found below:

Contributing

Any contribution is welcomed! Please read the contributing guide. You can do one of the followings to help us make LLamaSharp better:

  • Append a model link that is available for a version. (This is very important!)
  • Star and share LLamaSharp to let others know it.
  • Add a feature or fix a BUG.
  • Help to develop Web API and UI integration.
  • Just start an issue about the problem you met!

Contact us

Join our chat on Discord.

Join QQ group

License

This project is licensed under the terms of the MIT license.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  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 is compatible.  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. 
.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 (10)

Showing the top 5 NuGet packages that depend on LLamaSharp:

Package Downloads
Microsoft.KernelMemory.AI.LlamaSharp

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

LLamaSharp.semantic-kernel

The integration of LLamaSharp and Microsoft semantic-kernel.

LLamaSharp.kernel-memory

The integration of LLamaSharp and Microsoft kernel-memory. It could make it easy to support document search for LLamaSharp model inference.

LangChain.Providers.LLamaSharp

LLamaSharp Chat model provider.

LangChain.Providers.Automatic1111

Automatic1111 Stable DIffusion model provider.

GitHub repositories (4)

Showing the top 4 popular GitHub repositories that depend on LLamaSharp:

Repository Stars
SciSharp/BotSharp
AI Multi-Agent Framework in .NET
microsoft/kernel-memory
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
CodeMazeBlog/CodeMazeGuides
The main repository for all the Code Maze guides
jxq1997216/AITranslator
使用大语言模型来翻译MTool导出的待翻译文件的图像化UI软件
Version Downloads Last updated
0.19.0 7,081 11/8/2024
0.18.0 11,589 10/19/2024
0.17.0 1,119 10/13/2024
0.16.0 52,404 9/1/2024
0.15.0 19,947 8/3/2024
0.14.0 3,345 7/16/2024
0.13.0 54,540 6/4/2024
0.12.0 86,515 5/12/2024
0.11.2 15,577 4/6/2024
0.11.1 853 3/31/2024
0.10.0 6,462 2/15/2024
0.9.1 10,331 1/6/2024
0.9.0 554 1/6/2024
0.8.1 23,221 11/28/2023
0.8.0 23,909 11/12/2023
0.7.0 1,863 10/31/2023
0.6.0 2,380 10/24/2023
0.5.1 7,156 9/5/2023
0.4.2-preview 1,952 8/6/2023
0.4.1-preview 1,258 6/21/2023
0.4.0 11,455 6/19/2023
0.3.0 10,733 5/22/2023
0.2.3 720 5/17/2023
0.2.2 645 5/17/2023
0.2.1 683 5/12/2023
0.2.0 884 5/12/2023

LLamaSharp 0.4.1 followed up the master branch of llama.cpp. (commit id: aacdbd4)