efficient inference with quantized models
Efficient inference with quantized models refers to the process of performing computations with models that have been compressed or quantized, resulting in reduced memory usage and faster computations. This approach involves representing the model parameters with fewer bits, typically lower than the original precision, and utilizing techniques to maintain performance accuracy. By using quantized models, inference tasks can be executed more quickly, making them suitable for resource-constrained devices or systems with high throughput requirements.
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