Skip to content
English

Switch theme

// ⚙ Fine-tuning & PEFT

Instruction Tuning (FLAN)

Fine-tuning on many instruction–response tasks for zero-shot generalization.

指令微调(FLAN) 2021 Foundational core

IN PLAIN WORDS

Rewriting 60+ NLP datasets as instructions and fine-tuning greatly improves zero-shot performance on unseen tasks. It underlies the SFT stage of every chat model.

Used in: SFT of every chat model

TIMELINE · prerequisites → this → what builds on it

2019 T5 (Text-to-T…2020 GPT-3 & In-Co…2021 Instruction Tunin…2022 Reinforcement…2022 STaR (Self-Ta…2022 Self-Instruct2023 Visual Instru…

01Original paper

Finetuned Language Models Are Zero-Shot Learners

Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al. · 2021

arXiv ↗ ✓ Verified · arXiv API

02Where it sits

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

Related:LoRA (Low-Rank Adaptation)

T5 (Text-to-Tex…GPT-3 & In-Cont…Reinforcement L…STaR (Self-Taug…Self-InstructVisual Instruct…LoRA (Low-Rank … Instruction Tuning …

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

03Learning resources

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

Courses

Official docs

04Where the course teaches it

On learning paths:Post-training & Reasoning Models

For AI / data

Data updated: AI algorithms & curriculum(UTC+8)