**The C#/.NET binding of [llama.cpp](https://github.com/ggerganov/llama.cpp). It provides higher-level APIs to inference the LLaMA Models and deploy it on local device with C#/.NET. It works on
both Windows, Linux and MAC without requirement for compiling llama.cpp yourself. Even without a GPU or not enough GPU memory, you can still apply LLaMA models well with this repo. 🤗**
**Furthermore, it provides integrations with other projects such as [semantic-kernel](https://github.com/microsoft/semantic-kernel), [kernel-memory](https://github.com/microsoft/kernel-memory) and [BotSharp](https://github.com/SciSharp/BotSharp) to provide higher-level applications.**
We publish these backends because they are the most popular ones. If none of them matches, please compile the [llama.cpp](https://github.com/ggerganov/llama.cpp) yourself. In this case, please **DO NOT** install the backend packages, instead, add your DLL to your project and ensure it will be copied to the output directory when compiling your project. For more informations please refer to ([this guide](https://scisharp.github.io/LLamaSharp/0.5/ContributingGuide/)).
For [microsoft semantic-kernel](https://github.com/microsoft/semantic-kernel) integration, please search and install the following package:
For [microsoft kernel-memory](https://github.com/microsoft/kernel-memory) integration, please search and install the following package (currently kernel-memory only supports net6.0):
In general, there may be some break changes between two minor releases, for example 0.5.1 and 0.6.0. On the contrary, we don't introduce API break changes in patch release. Therefore it's recommended to keep the highest patch version of a minor release. For example, keep 0.5.6 instead of 0.5.3.
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.
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.
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#.
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 generate `gguf` format weights from original weights yourself.
3. Cannot load native lirary: 1) ensure you installed one of the backend packages. 2) Run `NativeLibraryConfig.WithLogs()` at the very beginning of your code to print more informations. 3) check if your system supports avx2, which is the default settings of official runtimes now. If not, please compile llama.cpp yourself and specify it with `NativeLibraryConfig.WithLibrary`.
4. How to find a model: Models in format `gguf` are valid for LLamaSharp (and `ggml` before v0.5.1). If you're new to LLM/LLaMA, it's a good choice to search `LLama` and `gguf` on [huggingface](https://huggingface.co/) to find a model. Another choice is generate gguf format file yourself with a pytorch weight (or any other), pleae refer to [convert.py](https://github.com/ggerganov/llama.cpp/blob/master/convert.py) and [convert-llama-ggml-to-gguf.py](https://github.com/ggerganov/llama.cpp/blob/master/convert-llama-ggml-to-gguf.py) to get gguf file through a ggml transformation.
Any contribution is welcomed! There's a TODO list in [LLamaSharp Dev Project](https://github.com/orgs/SciSharp/projects/5) and you could pick an interested one to start. Please read the [contributing guide](https://scisharp.github.io/LLamaSharp/latest/ContributingGuide/) for more informations.
You can also do one of the followings to help us make LLamaSharp better:
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.
The llama.cpp commit id will help if you want to compile a DLL yourself.
| LLamaSharp | Verified Model Resources | llama.cpp commit id |
| - | -- | - |
| v0.2.0 | This version is not recommended to use. | - |
