本项目旨在通过对 LeNet-5 在 MNIST 数据集上的 剪枝（Pruning）、量化（Quantization）和知识蒸馏（Knowledge Distillation）操作，以探索模型压缩技术（Model Compression）是如何减少计算量、提高推理速度，同时尽量保持模型性能。
active 2025-03-16 → 2025-03-16 (UTC)
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