How to choose + Summary:


• Can use teacher weights + pursue upper limits → Soft labels
• Can only use closed-source API / generate synthetic data → Hard labels
• Joint pre-training from scratch → Collaborative distillation
The essence of distillation: replacing the computational cost of "training super-large models" with the "ability of many small models to deploy."
Which distillation path are you most interested in?
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