Core
Quantization
Quantization stores model weights (and sometimes activations) in fewer bits, fp16 down to int8 or 4-bit, which cuts memory and speeds inference. The quality hit is usually small at int8 and larger at 4-bit. Knowing post-training quantization versus quantization-aware training, and when each is acceptable, is standard FDE interview ground.
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Practise this in questions
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