LIMA: Less Is More for Alignment — LLM Instruction / SFT Dataset
Landmark alignment research showing that just 1,000 carefully curated examples rival GPT-4 in instruction-following quality. Challenges the 'more data is always better' assumption. LIMA 65B was competitive with GPT-4 on human preference tests despite only 1k training examples.
s1K-1.1 — Cheap, fast reasoning fine-tunes — 1k samples means minutes of training, not days
No Robots — Your first fine-tune — small, clean, 100% human-written SFT data (non-commercial license)
Python-Edu — Continued pretraining for Python code understanding
OpenHermes 2.5 — The default general-purpose SFT mix for 7B-13B fine-tunes
Frequently asked questions
Can I use LIMA: Less Is More for Alignment commercially?
Not in a product — LIMA: Less Is More for Alignment is released under CC-BY-NC-SA 4.0, which restricts use to research and other non-commercial purposes. For commercial fine-tuning, pick a permissively licensed dataset from the same category instead.
How much data does LIMA: Less Is More for Alignment contain, and do I need all of it?
LIMA: Less Is More for Alignment contains 1k Rows. You rarely need all of it: for style and format fine-tuning, a few hundred to a few thousand examples are enough — load a slice (e.g. split="train[:1000]") and scale up only if quality plateaus.
What is LIMA: Less Is More for Alignment best used for?
Style and format alignment with a tiny curated set - quality over quantity. It belongs to the Instruction / SFT section of our dataset hub, where you'll find alternatives and complementary sets.