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emerging-techniques-knowledge-distillation — Claude Code skill

This skill outlines ways to transfer a large model’s outputs or probability signals to a smaller student. Use it when planning a distillation training workflow.

Install into Claude Code · claude-code-templates All methods and platforms ↓ 
npx claude-code-templates@latest --skill ai-research/emerging-techniques-knowledge-distillation
Open on GitHub

What emerging-techniques-knowledge-distillation does

The skill describes teacher-to-student knowledge transfer through softened probability targets or teacher-generated responses. Its examples cover temperature scaling, a loss that combines KL divergence with cross-entropy, and MiniLLM’s reverse-KLD approach. It guides training setup; it does not provide a command that compresses a model on its own.

The examples use transformers, torch, and datasets; the installation section also gives commands for accelerate, deepspeed, and wandb for training. MiniLLM is presented as a separate implementation option. You still need a configured training loop to produce a student model.

What it helps with

  • choose a loss for teacher-student distillation
  • transfer knowledge from a large teacher to a smaller student
  • train a student on teacher-generated responses
  • compare standard and reverse KL divergence

Example prompts for the agent

  • Explain how to transfer a large teacher model’s knowledge to a smaller student.
  • Plan student training using responses generated by a teacher model.
  • Show how reverse KLD fits into generative-model distillation.

How to install emerging-techniques-knowledge-distillation

1claude-code-templates

npx claude-code-templates@latest --skill ai-research/emerging-techniques-knowledge-distillation

2Skills CLI (Vercel)

npx skills add davila7/claude-code-templates --skill emerging-techniques-knowledge-distillation -a claude-code

3Manually: put the files in place

~/.claude/skills/emerging-techniques-knowledge-distillation/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/emerging-techniques-knowledge-distillation/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about emerging-techniques-knowledge-distillation

How do I install emerging-techniques-knowledge-distillation in Claude Code?

Run npx claude-code-templates@latest --skill ai-research/emerging-techniques-knowledge-distillation.

What does emerging-techniques-knowledge-distillation do?

It explains methods for transferring information from a larger model to a smaller one, including temperature scaling, soft targets, logit distillation, and training on generated responses.

How does reverse KLD fit into the skill?

The skill presents reverse KLD as the MiniLLM approach to generative-model distillation. It also contrasts that method with forward KL.

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