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macOS Internals

Understand your Mac and iPhone more deeply by tracing the evolution of Mac OS X from prelease to Swift. John Siracusa delivers the details.

Starting Points

How to use this gist

You've got two main options:

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This worked on 14/May/23. The instructions will probably require updating in the future.

It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

• Get llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.
• Use the link at the bottom of the page to apply for research access to the llama model: https://ai.facebook.com/blog/large-language-model-llama-meta-ai/
• Set up a micromamba environment to install cuda/python pytorch stuff in order to run the conversion scripts. Install some packages:
  • micromamba install -c conda-forge -n mymamba pytorch transformers sentencepiece
• Perform the conversion process: (This will produce a file called `ggml-model

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#include <assert.h>
#include <ctype.h>
#include <math.h>
#include <ncurses.h>
#include <stdlib.h>
#include <string.h>

#define NCOL 26                       // max number of columns (A..Z)
#define NROW 50                       // max number of rows
#define CW 9                          // column display width