// ⚙ Fine-tuning & PEFT

Adapters

Inserts small trainable modules between frozen layers.

Adapter 适配器 2019 Foundational core

IN PLAIN WORDS

Insert a down-project/nonlinearity/up-project bottleneck in each layer and train only it — a few percent of parameters for near full fine-tuning quality. It launched PEFT.

Used in: Multi-task model adaptation

TIMELINE · prerequisites → this → what builds on it

2018 BERT2019 Adapters2021 Prefix & Prom…2021 LoRA (Low-Ran…

01Original paper

Parameter-Efficient Transfer Learning for NLP

Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, et al. · 2019

arXiv ↗ ✓ Verified · arXiv API

02Where it sits

Learn the left column first; the right column builds on this one.

Learn first

BERT

Adapters

Then you can learn

Left: prerequisites · right: builds on this · dashed: related. Full map →

03Learning resources

Official docs, explainers, courses and reference code. All links checked.

Official docs

huggingface.co ↗EN

04Where the course teaches it

U50 Instruction Tuning & PEFT SFT, synthetic data, LoRA/QLoRA/DoRA, adapters and model merging. 10 h8 algorithms3 paperslesson ready

For AI / data

Verification: verified, checked 2026-10-21.
JSON: /api/learn/algorithms.json (id: adapters)