Description
In this visually rich post, Maarten Grootendorst offers an intuitive and deeply illustrated introduction to quantization in the context of large language models, guiding readers through fundamentals like numerical representation (FP32, FP16, BF16, INT8), symmetric vs. asymmetric quantization, and advanced techniques such as dynamic and static post-training quantization. With over 50 custom visuals, he breaks down key concepts like scale and zero-point calculations, quantization error, clipping strategies, and post-training tweaks (e.g., GPTQ, GGUF) to make compression techniques accessible and engaging—even for those new to the subject.
