---
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](https://github.com/maxgfr/skycmd), tiny decision models trained from scratch in Rust that run in the
browser. Written by `scripts/lfm3-s1s2.sh data` at commit [`84c6d854`](https://github.com/maxgfr/skycmd/commit/84c6d854cdc2a9f6d951ebb55780060a01f38ca6).
Licences of every set: [DATA_LICENSES.md](https://github.com/maxgfr/skycmd/blob/main/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 |

```python
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.