b76724cddc
Co-authored-by: john.shen <john.shen@bioclinica.com>
59 lines
1.6 KiB
Markdown
59 lines
1.6 KiB
Markdown
---
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title: MacOS Install with Metal GPU
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---
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**(1) Make sure you have xcode installed... at least the command line parts**
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```
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# check the path of your xcode install
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xcode-select -p
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# xcode installed returns
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# /Applications/Xcode-beta.app/Contents/Developer
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# if xcode is missing then install it... it takes ages;
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xcode-select --install
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```
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**(2) Install the conda version for MacOS that supports Metal GPU**
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```
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wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
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bash Miniforge3-MacOSX-arm64.sh
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```
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**(3) Make a conda environment**
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```
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conda create -n llama python=3.9.16
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conda activate llama
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```
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**(4) Install the LATEST llama-cpp-python...which happily supports MacOS Metal GPU as of version 0.1.62**
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*(you needed xcode installed in order pip to build/compile the C++ code)*
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```
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pip uninstall llama-cpp-python -y
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CMAKE_ARGS="-DLLAMA_METAL=on" pip install -U llama-cpp-python --no-cache-dir
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pip install 'llama-cpp-python[server]'
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# you should now have llama-cpp-python v0.1.62 or higher installed
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llama-cpp-python 0.1.68
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```
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**(5) Download a v3 gguf v2 model**
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- **ggufv2**
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- file name ends with **Q4_0.gguf** - indicating it is 4bit quantized, with quantisation method 0
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https://huggingface.co/TheBloke/CodeLlama-7B-GGUF
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**(6) run the llama-cpp-python API server with MacOS Metal GPU support**
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```
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# config your ggml model path
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# make sure it is gguf v2
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# make sure it is q4_0
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export MODEL=[path to your llama.cpp ggml models]]/[ggml-model-name]]Q4_0.gguf
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python3 -m llama_cpp.server --model $MODEL --n_gpu_layers 1
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```
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***Note:** If you omit the `--n_gpu_layers 1` then CPU will be used*
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