Mini toolsDefinition
A technique for reducing model size by removing unnecessary connections or neurons. This process identifies and eliminates redundant or less important parameters.
Detailed Explanation
Pruning involves systematically removing weights neurons or entire layers from a neural network while maintaining performance. Methods include magnitude-based pruning importance scoring and structured pruning. The process often involves training the original network pruning according to some criteria and fine-tuning the remaining connections.
Use Cases
Model optimization Mobile deployment Edge computing Resource-constrained applications
