1.6 KiB
1.6 KiB
| title |
|---|
| 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 happily supports MacOS Metal GPU as of version 0.1.62
(you needed xcode installed in order pip to build/compile the C++ code)
pip uninstall llama-cpp-python -y
CMAKE_ARGS="-DLLAMA_METAL=on" 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 or higher installed
llama-cpp-python 0.1.68
(5) 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