Knowledge Distillation
How teacher-student training compresses large models into smaller, faster ones while preserving most of the original accuracy.
How teacher-student training compresses large models into smaller, faster ones while preserving most of the original accuracy.
How structured and unstructured pruning reduce neural network size by removing redundant weights, neurons, or layers.
How INT8 and INT4 quantization compress neural network models for faster inference and lower memory usage with minimal accuracy loss.