04 - Knowledge Distillation: Compress Models Efficiently

Complete guide to Knowledge Distillation: Compress Models Efficiently: architecture, practical implementation and best practices for developers and technical teams.

What you'll learn

• Distillation theory: soft labels, temperature, and dark knowledge
• Complete standard distillation implementation with PyTorch
• Feature Distillation: transferring intermediate representations
• Attention Transfer: distilling Transformer attention maps
• Self-Distillation and Born Again Networks

This article is part of the Deep Learning Avanzato series on federicocalo.dev.

Read the full article

The complete article (15 min read) with code examples, diagrams, and practical exercises is available here:

➡️ 04 - Knowledge Distillation: Compress Models Efficiently

https://federicocalo.dev/en/blog/knowledge-distillation-compress-models-efficiently

By Federico Calò — Software Developer & Technical Writer