Article URL: https://newsletter.maartengrootendorst.com/p/a-visual-guide-to-quantization Comments URL: https://news.ycombinator.com/item?id=49202814 Points: 5 # Comments: 0

As their name suggests, Large Language Models (LLMs) are often too large to run on consumer hardware. These models may exceed billions of parameters and generally need GPUs with large amounts of VRAM to speed up inference. As such, more and more research has been focused on making these models smaller through improved training, adapters, etc. One major technique in this field is called quantization. In this post, I will introduce the field of quantization in the context of language modeling and explore concepts one by one to develop an intuition about the field. We will explore various methodologies, use cases, and the principles behind quantization. In this visual guide, there are more than 50 custom visuals to help you develop an intuition about quantization! Thanks for reading Exploring Language Models! Subscribe to receive new posts on Gen AI and the book: Hands-On Large Language Models To see more visualizations related to LLMs and to support this newsletter, check out the book I wrote on Large Language Models! P.S. If you read the book, a quick review would mean the world—it really helps us authors! LLMs get their name due to the number of parameters they contain. Nowadays, these models typically have billions of parameters (mostly weights) which can be quite expensive to store.