Mini toolsDefinition
A technique that reduces model size by converting floating-point weights to lower-precision formats. This significantly reduces memory usage and computational requirements.
Detailed Explanation
Quantization reduces the numerical precision of model weights and activations typically from 32-bit floating-point to 8-bit integer or even lower precision formats. This process involves careful calibration to maintain accuracy while reducing memory and computational requirements. Different quantization schemes (post-training quantization-aware training) offer different trade-offs between accuracy and efficiency.
Use Cases
Edge device deployment Mobile applications IoT devices Real-time processing systems
