license: mit
language:
- en
pretty_name: skycmd LFM3 System 1 / System 2 questions
task_categories:
- question-answering
tags:
- skycmd
configs:
- config_name: calib
data_files: data/calib.parquet
- config_name: test
data_files: data/test.parquet
skycmd LFM3 System 1 / System 2 questions
The calibration and test questions of the LFM3-1.7B System 1 / System 2 router (docs/lfm3-s1s2-prereg.md): GSM8K and MATH, drawn with a fixed seed at pinned revisions.
Part of skycmd, tiny decision models trained from scratch in Rust that run in the
browser. Written by scripts/lfm3-s1s2.sh data at commit 84c6d854.
Licences of every set: DATA_LICENSES.md.
Each row is one question: id, task (gsm8k or math), question and answer (the final
answer, compared after normalization).
Sources and licences
Each config is one source and keeps its source's licence (share-alike sources stay share-alike). Attribution goes to the upstream authors; the conversion is ours.
| config | upstream | licence | how it is used | rows |
|---|---|---|---|---|
calib |
openai/gsm8k (main, train, 740312ad) and DigitalLearningGmbH/MATH-lighteval (train, 0530c786) |
mit | 300 + 300 calibration questions, seed 1234 | 600 |
test |
openai/gsm8k (main, test) and HuggingFaceH4/MATH-500 (6e4ed1a2) |
mit | 500 + 500 test questions, seed 1234 | 1,000 |
Files
| file | rows |
|---|---|
data/calib.parquet |
600 |
data/test.parquet |
1,000 |
from datasets import load_dataset
ds = load_dataset("maxgfr/skycmd-lfm3-math", "calib")
skycmd wrote no row with a language model: the targets come from the upstream labels (some upstream sets carry their own teacher soft labels, see their cards), the games' oracles or our generators.