llama-cpp-python - MacOS Install with Metal GPU

(1) Make sure you have xcode installed... at least the command line parts

# check the path of your xcode install 
xcode-select -p

# xcode installed returns
# /Applications/Xcode-beta.app/Contents/Developer

# if xcode is missing then install it... it takes ages;
xcode-select --install

(2) Install the conda version for MacOS that supports Metal GPU

wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
bash Miniforge3-MacOSX-arm64.sh

(3) Make a conda environment

conda create -n llama python=3.9.16
conda activate llama

(4) Install the LATEST llama-cpp-python.. which, as of just today, happily supports MacOS Metal GPU
(you needed xcode installed in order pip to build/compile the C++ code)

pip uninstall llama-cpp-python -y
CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install -U llama-cpp-python --no-cache-dir
pip install 'llama-cpp-python[server]'

# you should now have llama-cpp-python v0.1.62 installed
llama-cpp-python         0.1.62

(4) Download a v3 ggml model

ggmlv3
file name ends with q4_0.bin - indicating it is 4bit quantized, with quantisation method 0

https://huggingface.co/TheBloke/open-llama-7b-open-instruct-GGML

(6) run the llama-cpp-python API server with MacOS Metal GPU support

# config your ggml model path
# make sure it is ggml v3
# make sure it is q4_0
export MODEL=[path to your llama.cpp ggml models]]/[ggml-model-name]]q4_0.bin
python3 -m llama_cpp.server --model $MODEL  --n_gpu_layers 1

Note: If you omit the --n_gpu_layers 1 then CPU will be used

1.7 KiB Raw Blame History

llama-cpp-python - MacOS Install with Metal GPU

1.7 KiB

Raw Blame History