Deep Learning

Model Pruning

Removing unimportant parameters or structures from a neural network.

Model pruning identifies weights, neurons, attention heads or layers that contribute little to performance. These components can be removed to create a smaller and faster network.

Pruning may be performed gradually during training or after the model has been trained. The pruned model is often fine-tuned to recover any accuracy lost during compression.

Also in Deep Learning

CNN RNN LSTM Transformers Auto Encoders Deep RL

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