llama.cpp.zig

llama.cpp bindings and utilities for zig. Currently targeting zig 0.11.x, there is high chance nightly works as well (0.12.0-dev.1856+94c63f31f when I checked) (using same branch, only few places have needed patching where @hasDecl was enough to support both versions).

• Implements llama.h for nicer interaction with zig.
  • Removes prefixes, changes naming for functions to camelCase. Group functions within most appropriete struct. etc.
  • Bindings still depend on translate-c as I tried to not rewrite struct definitions too much as those might change. But some were rewritten for ease of use. Has to be seen if others might benefit rewriting as well for nicer access / syntax.
• Re-Implements some of the C++ that is not acessable through c api due to use of c++ std stuff:
  • sampling.zig
• Implements some utilities such as:
  • buffered Tokenizer & Detokenizer
  • prompt utility to simplify interaction with llama. (still wip) will support easly modifying prompt & regenerating it. Handling of out of context behaviour, etc. Possibly optional pagination/indexing of messages.
  • basic templated prompt generator, to try to manage different prompt formatting styles (chatML, alpaca, etc).

Example usage

Clone: git clone --recursive https://github.com/Deins/llama.cpp.zig.git

1. Download llama.cpp supported model (usually *.gguf format). For example this one.
2. build and run with:

zig build run-simple -Doptimize=ReleaseFast -- --model_path path_to/model.gguf --prompt "Hello! I am AI, and here are the 10 things I like to think about:"

See examples/simple.zig

CPP samples

Subset of llama cpp samples have been included in build scripts. Use -Dcpp_samples option to install them.
Or run them directly, for example: zig build run-cpp-main -Dclblast -Doptimize=ReleaseFast -- -m path/to/model.gguf -p "hello my name is"

CLBlast acceleration

Clblast is supported by building it from source with zig. At moment only OpenCl backend has been tested. Cuda backend is not finished as I don't have nvidia hardware, pull requests are welcome.

Build:

Ideally just zig build -Dclblast .... It should work out of the box if you have installed GPUOpen/ocl. For other configurations you will need to find where OpenCL headers/libs are and pass them in using arguments zig build -Dclblast -Dopencl_includes="/my/path" -Dopencl_libs="/my/path/" Auto detection might be improved in future - let me know what opencl sdk you use.

Selecting GPU

With opencl backend main_gpu parameter is ignored. Insted you can set ids of GGML_OPENCL_PLATFORM GGML_OPENCL_DEVICE system enviroment variables. There is zig build -Dclblast run-opencl_devices utility available to print all opencl devices detected.