M3 Max is a Machine Learning BEAST. So I took it for a spin with some LLM's running locally.
I also show how to gguf quantizations with llama.cpp

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Timestamps
00:00 Intro
00:40 Build from scratch manual
09:44 Bonus script automated
11:21 LM Studio one handed

Repo
https://github.com/ggerganov/llama.cpp/'>https://github.com/ggerganov/llama.cpp/

Commands
//assuming you already have a conda environment set up, and dev tools installed (see videos above for instructions)
Part 1 manual
brew install gitlfs
git lfs install
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
pip install r requirements.txt
make
git clone https://huggingface.co/teknium/OpenHe... openhermes7bv2.5
mv openhermes7bv2.5 models/
python3 convert.py ./models/openhermes7bv2.5 outfile ./models/openhermes7bv2.5/ggmlmodelf16.gguf outtype f16
./quantize ./models/openhermes7bv2.5/ggmlmodelf16.gguf ./models/openhermes7bv2.5/ggmlmodelq8_0.gguf q8_0
./quantize ./models/openhermes7bv2.5/ggmlmodelf16.gguf ./models/openhermes7bv2.5/ggmlmodelq4_k.gguf q4_k
./batchedbench ./models/openhermes7bv2.5/ggmlmodelf16.gguf 4096 0 99 0 2048 128,512 1,2,3,4
./server m models/openhermes7bv2.5/ggmlmodelq4_k.gguf port 8888 host 0.0.0.0 ctxsize 10240 parallel 4 ngl 99 n 512

Part 2 auto
bash c "$(curl s https://ggml.ai/serverllm.sh)"

MacBooks in this video
M2 Max 16" MacBook Pro 64GB/2TB


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