Phi 2 on Intel Meteor Lake Coding question

March 20, 2024
What if we could run state-of-the-art open-source LLMs on a typical personal computer? Did you think it was a lost cause? Well, it's not! In this post, thanks to the Hugging Face Optimum library, we apply 4-bit quantization to the 2.7-billion Microsoft Phi-2 model, and we run inference on a mid-range laptop powered by an Intel Meteor Lake CPU. More in the blog post: "A chatbot on your laptop" https://huggingface.co/blog/phi2-intel-meteor-lake

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About the Author

Julien Simon is the Chief Evangelist at Arcee AI , specializing in Small Language Models and enterprise AI solutions. Recognized as the #1 AI Evangelist globally by AI Magazine in 2021, he brings over 30 years of technology leadership experience to his role.

With 650+ speaking engagements worldwide and 350+ technical blog posts, Julien is a leading voice in practical AI implementation, cost-effective AI solutions, and the democratization of artificial intelligence. His expertise spans open-source AI, Small Language Models, enterprise AI strategy, and edge computing optimization.

Previously serving as Principal Evangelist at Amazon Web Services and Chief Evangelist at Hugging Face, Julien has helped thousands of organizations implement AI solutions that deliver real business value. He is the author of "Learn Amazon SageMaker," the first book ever published on AWS's flagship machine learning service.

Julien's mission is to make AI accessible, understandable, and controllable for enterprises through transparent, open-weights models that organizations can deploy, customize, and trust.