CookieĬloudflare sets this cookie to identify trusted web traffic. These cookies ensure basic functionalities and security features of the website, anonymously. A step-by-step instruction guide for running LLaMA on a Mac can be found here (Warning: it's fairly technical).Necessary cookies are absolutely essential for the website to function properly. The release of Alpaca today by Stanford proves that fine tuning (additional training with a specific goal in mind) can improve performance, and it's still early days after LLaMA's release. Also, optimizations and fine-tunings come quickly when everyone has their hands on the code and the weights - even though LLaMA is still saddled with some fairly restrictive terms of use. It's entirely possible that better prompting techniques might generate better results.

In our tests, LLaMA 7B trimmed down to 4-bit quantization was very impressive for running on a MacBook Air - but still not on par with what you might expect from ChatGPT. There's still the question of how much the quantization affects the quality of the output. You call it as a script on the command line with a prompt, and LLaMA does its best to complete it in a reasonable way.

After obtaining the LLaMA weights ourselves, we followed instructions and got the 7B parameter version running on an M1 Macbook Air, and it runs at a reasonable rate of speed. And now, with optimizations that reduce the model size using a technique called quantization, LLaMA can run on an M1 Mac or a lesser Nvidia consumer GPU.

Typically, running GPT-3 requires several datacenter-class A100 GPUs (also, the weights for GPT-3 are not public), but LLaMA made waves because it could run on a single beefy consumer GPU. If this keeps up, we may be looking at a pocket-sized ChatGPT competitor before we know it. Then someone showed it running on a Pixel 6 phone, and next came a Raspberry Pi (albeit running very slowly). Soon thereafter, people worked out how to run LLaMA on Windows as well. An anonymous reader quotes a report from Ars Technica: On Friday, a software developer named Georgi Gerganov created a tool called 'llama.cpp' that can run Meta's new GPT-3-class AI large language model, LLaMA, locally on a Mac laptop.

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