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Install packages

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 v0.3.0 LLamaSharpSamples v0.3.0, WizardLM 7e4ea5b

Download a model

One of the following models could be okay:

Note that because llama.cpp is under fast development now and often introduce break changes, some model weights on huggingface which works under a version may be invalid with another version. If it's your first time to configure LLamaSharp, we'd like to suggest for using verified model weights in the table above.

Run the program

Please create a console program with dotnet runtime >= netstandard 2.0 (>= net6.0 is more recommended). Then, paste the following code to program.cs;

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.

// Load model
var parameters = new ModelParams(modelPath)
{
    ContextSize = 1024
};
using var model = LLamaWeights.LoadFromFile(parameters);

// Initialize a chat session
using var context = model.CreateContext(parameters);
var ex = new InteractiveExecutor(context);
ChatSession session = new ChatSession(ex);

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

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

    Console.ForegroundColor = ConsoleColor.Green;
    prompt = Console.ReadLine();
    Console.ForegroundColor = ConsoleColor.White;
}

After starting it, you'll see the following outputs.

Please input your model path: D:\development\llama\weights\wizard-vicuna-13B.ggmlv3.q4_1.bin
llama.cpp: loading model from D:\development\llama\weights\wizard-vicuna-13B.ggmlv3.q4_1.bin
llama_model_load_internal: format     = ggjt v3 (latest)
llama_model_load_internal: n_vocab    = 32000
llama_model_load_internal: n_ctx      = 1024
llama_model_load_internal: n_embd     = 5120
llama_model_load_internal: n_mult     = 256
llama_model_load_internal: n_head     = 40
llama_model_load_internal: n_layer    = 40
llama_model_load_internal: n_rot      = 128
llama_model_load_internal: ftype      = 3 (mostly Q4_1)
llama_model_load_internal: n_ff       = 13824
llama_model_load_internal: n_parts    = 1
llama_model_load_internal: model size = 13B
llama_model_load_internal: ggml ctx size = 7759.48 MB
llama_model_load_internal: mem required  = 9807.48 MB (+ 1608.00 MB per state)
....................................................................................................
llama_init_from_file: kv self size  =  800.00 MB

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.

User: Hello, Bob.
Bob: Hello. How may I help you today?
User: Please tell me the largest city in Europe.
Bob: Sure. The largest city in Europe is Moscow, the capital of Russia.
User:

Now, enjoy chatting with LLM!