LLama.cpp golang bindings.
The go-llama.cpp bindings are high level, as such most of the work is kept into the C/C++ code to avoid any extra computational cost, be more performant and lastly ease out maintenance, while keeping the usage as simple as possible.
Check out this and this write-ups which summarize the impact of a low-level interface which calls C functions from Go.
If you are looking for an high-level OpenAI compatible API, check out here.
Note: This repository uses git submodules to keep track of LLama.cpp.
Clone the repository locally:
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cppTo build the bindings locally, run:
cd go-llama.cpp
make libbinding.a
Now you can run the example with:
LIBRARY_PATH=$PWD C_INCLUDE_PATH=$PWD go run ./examples -m "/model/path/here" -t 14
To build and run with OpenBLAS, for example:
BUILD_TYPE=openblas make libbinding.a
CGO_LDFLAGS="-lopenblas" LIBRARY_PATH=$PWD C_INCLUDE_PATH=$PWD go run -tags openblas ./examples -m "/model/path/here" -t 14
To build with CuBLAS:
BUILD_TYPE=cublas make libbinding.a
CGO_LDFLAGS="-lcublas -lcudart -L/usr/local/cuda/lib64/" LIBRARY_PATH=$PWD C_INCLUDE_PATH=$PWD go run ./examples -m "/model/path/here" -t 14
BUILD_TYPE=clblas CLBLAS_DIR=... make libbinding.a
CGO_LDFLAGS="-lOpenCL -lclblast -L/usr/local/lib64/" LIBRARY_PATH=$PWD C_INCLUDE_PATH=$PWD go run ./examples -m "/model/path/here" -t 14
You should see something like this from the output when using the GPU:
ggml_opencl: selecting platform: 'Intel(R) OpenCL HD Graphics'
ggml_opencl: selecting device: 'Intel(R) Graphics [0x46a6]'
ggml_opencl: device FP16 support: true
Enjoy!
The documentation is available here and the full example code is here.
MIT