Generative AI models, like large language models, often exceed the capabilities of consumer-grade hardware and are expensive to run. Compressing model

Quantization Fundamentals with Hugging Face

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2024-04-16 15:00:06

Generative AI models, like large language models, often exceed the capabilities of consumer-grade hardware and are expensive to run. Compressing models through methods such as quantization makes them more efficient, faster, and accessible. This allows them to run on a wide variety of devices, including smartphones, personal computers, and edge devices, and minimizes performance degradation.

By the end of this course, you will have a foundation in quantization techniques and be able to apply them to compress and optimize your own generative AI models, making them more accessible and efficient.

This is an introduction to the fundamental concepts of quantization for learners with a basic understanding of machine learning concepts and some experience with PyTorch, who is interested in learning about model quantization in generative AI.