llama.cpp-dotnet

Description

C# bindings for llama.cpp including a .NET core library and sample projects (CLI & Web API).

Quick Start

Build (on Windows use the VS2022 x64 command prompt, on Linux make sure to install cmake and dotnet):

git clone --recursive https://github.com/dranger003/llama.cpp-dotnet.git
cd llama.cpp-dotnet
dotnet build -c Release /p:Platform="Any CPU"

If you don't need to compile the native libraries, you can also append /p:NativeLibraries=OFF to the dotnet build command above.

Windows:

cd Release
LlamaCppCli.exe 0 <model_path>

Linux:

cd Release
./LlamaCppCli 0 <model_path>

Samples

Usage: LlamaCppCli.dll <SampleIndex> <SampleArgs>

Local

Usage: LlamaCppCli.dll 0 model_path [gpu_layers] [ctx_length] [template]

Remote

Usage: LlamaCppCli.dll 1 base_url model_name [gpu_layers] [ctx_length] [template]

Models

You will need a model in GGML format, the 13B parameters appears to perform well if you have the memory (8-12GB depending on the quantized model). If you have a lot of RAM (i.e. 48GB+) you could try a 65B version though it is much slower on the predictions, especially without a GPU.

A lot of models can be found below.

TheBloke on Hugging Face

Sample Code (interactive CLI)

using LlamaCppLib;

// Configure some model options
var modelOptions = new LlamaCppModelOptions
{
    ContextSize = 2048,
    GpuLayers = 24,
    // ...
};

// Load model file
using var model = new LlamaCppModel();
model.Load(@"ggml-model-13b-Q8_0.bin", modelOptions);

// Configure some prediction options
var generateOptions = new LlamaCppGenerateOptions
{
    ThreadCount = 4,
    TopK = 40,
    TopP = 0.95f,
    Temperature = 0.1f,
    RepeatPenalty = 1.1f,
    Mirostat = Mirostat.Mirostat2,
    // ...
};

// Create conversation session
var session = model.CreateSession();

while (true)
{
    // Get a prompt
    Console.Write("> ");
    var prompt = Console.ReadLine();

    // Quit on blank prompt
    if (String.IsNullOrWhiteSpace(prompt))
        break;

    // Set-up prompt using template
    prompt = String.Format(template, prompt);

    // Generate tokens
    await foreach (var token in session.GenerateTokenStringAsync(prompt, generateOptions))
        Console.Write(token);
}

API Endpoints (Model)

GET /model/list
GET /model/load?modelName={modelName}&modelOptions={modelOptions}
GET /model/unload
GET /model/status
GET /model/tokenize?prompt={prompt}
GET /model/reset
GET /session/create
GET /session/list
GET /session/get
GET /session/reset
POST /model/generate [RequestBody]

TODO

Dynamic model loading
Expose minimal API
Support Windows/Linux
Support BERT

Acknowledgments

ggerganov/llama.cpp for the LLaMA implementation in C++
skeskinen/bert.cpp for BERT support

wang2650/llama.cpp-dotnet