https://github.com/gusgitmath/llama3_macsilicon

Repository for running LLMs efficiently on Mac silicon (M1, M2, M3). Features Jupyter notebook for Meta-Llama-3 setup using MLX framework, with install guide & perf tips. Aims to optimize LLM performance on Mac silicon for devs & researchers.
https://github.com/gusgitmath/llama3_macsilicon

llama3 llm macos

Last synced: about 9 hours ago
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Repository for running LLMs efficiently on Mac silicon (M1, M2, M3). Features Jupyter notebook for Meta-Llama-3 setup using MLX framework, with install guide & perf tips. Aims to optimize LLM performance on Mac silicon for devs & researchers.

• Host: GitHub
• URL: https://github.com/gusgitmath/llama3_macsilicon
• Owner: GusGitMath
• Created: 2024-08-29T16:13:51.000Z (29 days ago)
• Default Branch: main
• Last Pushed: 2024-08-29T16:14:05.000Z (29 days ago)
• Last Synced: 2024-09-27T04:02:36.748Z (about 9 hours ago)
• Topics: llama3, llm, macos
• Language: Jupyter Notebook
• Homepage: https://medium.com/@guslovesmath/efficiently-running-meta-llama-3-on-mac-silicon-m1-m2-m3-61585c9bc741
• Size: 5.86 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Meta-Llama-3 on Mac Silicon

## Overview

This Jupyter notebook demonstrates how to run the Meta-Llama-3 model on Apple's Mac silicon devices from [**My Medium Post**](https://medium.com/@guslovesmath/efficiently-running-meta-llama-3-on-mac-silicon-m1-m2-m3-61585c9bc741). It includes examples of generating responses from simple prompts and delves into more complex scenarios like solving mathematical problems.

## Requirements

- Apple Mac with M1, M2, or M3 chip

- macOS Monterey or later

- Python 3.x

- Required Python packages: `ipywidgets`, `torch`, `mlx-lm`

## Setup

Clone this repository and install the necessary packages:

```bash

pip install ipywidgets torch mlx-lm

```

[MLX Cummunity on Hugging Face](https://huggingface.co/mlx-community)