Quantization-Aware Training (QAT)
A training process that models quantization error during the forward pass to minimize precision loss.
QAT inserts simulated quantization errors during model training. This allows weights to adapt to precision constraints, maintaining model accuracy when exported to low-precision formats (like INT8).
Historical figures and technical concepts for informational purposes only. Not technical, professional, legal, or financial advice. Sources: Official Documentation.