How do I implement knowledge distillation in my models?

How do I implement knowledge distillation in my models?

Knowledge distillation is a technique where a smaller model (student) learns from a larger model (teacher). Would you like a step-by-step guide?

Yes, please provide the steps.

1. Train your teacher model on the dataset. 2. Use the teacher to generate soft labels for the training data. 3. Train the student model using these soft labels along with the original labels.

What are soft labels?

Soft labels are the probabilities output by the teacher model for each class, rather than hard labels which are binary.

Can you give an example of how to generate soft labels?

Sure! After training your teacher model, you can pass your input data through it to get the output probabilities for each class, which are your soft labels.