How does knowledge distillation work?

Can you explain what knowledge distillation is?

Knowledge distillation is a process where a smaller model is trained to replicate the behavior of a larger, more complex model.

Why would we want to use a smaller model?

Smaller models are faster and require less computational resources, making them ideal for deployment in real-time applications.

How does the training process work in knowledge distillation?

In knowledge distillation, the smaller model learns from the outputs of the larger model, often using soft labels to capture more nuanced information.

Are there any limitations to knowledge distillation?

Yes, knowledge distillation may not always capture all the complexities of the larger model, potentially leading to a loss in accuracy.