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I can explain Quantization
Shrinking a model so it runs faster with less memory.
Quantization reduces the numeric precision of model weights (for example from 16-bit to 4-bit) to cut memory and often speed inference, with some quality trade-offs.
Sticky trick
Quantize to fit; re-eval quality after you shrink.
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In plain English, what is Quantization?
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