LLamaSharp.Cpu
0.2.1
dotnet add package LLamaSharp.Cpu --version 0.2.1
NuGet\Install-Package LLamaSharp.Cpu -Version 0.2.1
<PackageReference Include="LLamaSharp.Cpu" Version="0.2.1" />
paket add LLamaSharp.Cpu --version 0.2.1
#r "nuget: LLamaSharp.Cpu, 0.2.1"
// Install LLamaSharp.Cpu as a Cake Addin #addin nuget:?package=LLamaSharp.Cpu&version=0.2.1 // Install LLamaSharp.Cpu as a Cake Tool #tool nuget:?package=LLamaSharp.Cpu&version=0.2.1
LLamaSharp - .NET Bindings for llama.cpp
The C#/.NET binding of llama.cpp. It provides APIs to inference the LLaMa Models and deploy it on native environment or Web. It works on both Windows and Linux and does NOT require compiling the library yourself.
- Load and inference LLaMa models
- Simple APIs for chat session
- Quantize the model in C#/.NET
- ASP.NET core integration
- Native UI integration
Installation
Just search LLamaSharp
in nuget package manager and install it!
PM> Install-Package LLamaSharp
Simple Benchmark
Currently it's only a simple benchmark to indicate that the performance of LLamaSharp
is close to llama.cpp
. Experiments run on a computer
with Intel i7-12700, 3060Ti with 7B model. Note that the benchmark uses LLamaModel
instead of LLamaModelV1
.
Windows
llama.cpp: 2.98 words / second
LLamaSharp: 2.94 words / second
Usages
Currently, LLamaSharp
provides two kinds of model, LLamaModelV1
and LLamaModel
. Both of them works but LLamaModel
is more recommended
because it provides better alignment with the master branch of llama.cpp.
Besides, ChatSession
makes it easier to wrap your own chat bot. The code below is a simple example. For all examples, please refer to
Examples.
var model = new LLamaModel(new LLamaParams(model: "<Your path>", n_ctx: 512, repeat_penalty: 1.0f));
var session = new ChatSession<LLamaModel>(model).WithPromptFile("<Your prompt file path>")
.WithAntiprompt(new string[] { "User:" );
Console.Write("\nUser:");
while (true)
{
Console.ForegroundColor = ConsoleColor.Green;
var question = Console.ReadLine();
Console.ForegroundColor = ConsoleColor.White;
var outputs = session.Chat(question); // It's simple to use the chat API.
foreach (var output in outputs)
{
Console.Write(output);
}
}
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!");
}
Demo
Roadmap
✅ LLaMa model inference.
✅ Embeddings generation.
✅ Chat session.
✅ Quantization
🔳 ASP.NET core Integration
🔳 WPF UI Integration
Assets
The model weights is too large to include in the project. However some resources could be found below:
- eachadea/ggml-vicuna-13b-1.1
- TheBloke/wizardLM-7B-GGML
- Magnet: magnet:?xt=urn:btih:b8287ebfa04f879b048d4d4404108cf3e8014352&dn=LLaMA
The weights included in the magnet is exactly the weights from Facebook LLaMa.
The prompts could be found below:
License
This project is licensed under the terms of the MIT license.
Product | Versions 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 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. |
.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. |
-
.NETStandard 2.0
- Microsoft.Extensions.Logging (>= 7.0.0)
- Serilog (>= 3.0.0-dev-01998)
- Serilog.Extensions.Logging.File (>= 3.0.1-dev-00077)
- Serilog.Sinks.Console (>= 4.1.0)
-
net6.0
- Microsoft.Extensions.Logging (>= 7.0.0)
- Serilog (>= 3.0.0-dev-01998)
- Serilog.Extensions.Logging.File (>= 3.0.1-dev-00077)
- Serilog.Sinks.Console (>= 4.1.0)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.
Version | Downloads | Last updated |
---|---|---|
0.2.1 | 916 | 5/12/2023 |
LLamaSharp 0.2.1 provides basic APIs to load, run and quantize models. It also support chat session and Web API.