Eric Alonas ejalonas

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4 Steps in Running LLaMA-7B on a M1 MacBook

The large language models usability

The problem with large language models is that you can’t run these locally on your laptop. Thanks to Georgi Gerganov and his llama.cpp project, it is now possible to run Meta’s LLaMA on a single computer without a dedicated GPU.

Running LLaMA

There are multiple steps involved in running LLaMA locally on a M1 Mac after downloading the model weights.

	# Reference: https://svds.com/jupyter-notebook-best-practices-for-data-science/
	import os
	from subprocess import check_call

	def post_save(model, os_path, contents_manager):
	"""post-save hook for converting notebooks to .py scripts"""
	if model['type'] != 'notebook':
	return # only do this for notebooks
	d, fname = os.path.split(os_path)
	check_call(['jupyter', 'nbconvert', '--to', 'script', fname], cwd=d)