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5min chapter
Large models on CPUs
Practical AI: Machine Learning, Data Science, LLM
The Importance of Intuition in Quantization
There's one or two layers in some of these that are extremely sensitive for whatever reason to quantization that you can't quantize it. So removing those, then you get 100% recovery. Pruning is much more of a requirement to do training aware on the pruning side,. But you definitely will see this kind of the choices that are made in the hyper parameters that are chosen. Those can significantly affect the recovery and equality. If they were seeing drops in performance, it's primarily because of those choices and those issues and just the wide breaths that's available right now and not knowing how to narrow it down.
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