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pretty_name: tinyrouter-m1
task_categories:
- text-classification
tags:
- tinyrouter
- milestone-1
- gci-bench
license: other
configs:
- config_name: 5-domain
data_files:
- split: train
path: 5-domain/train.parquet
- split: test
path: 5-domain/test.parquet
- config_name: 20-domain
data_files:
- split: train
path: 20-domain/train.parquet
- split: test
path: 20-domain/test.parquet
- config_name: default
data_files:
- split: train
path: 5-domain/train.parquet
- split: test
path: 5-domain/test.parquet
---
# tinyrouter-m1
Two **separate** Milestone-1 triage datasets. Same schema; different domain taxonomies.
## Overview
| config | #domains | train | test | total | difficulty levels present |
| --- | ---: | ---: | ---: | ---: | --- |
| **`5-domain`** | 5 | 311,868 | 16,414 | 328,282 | 1, 2, 3, 4, 5 |
| **`20-domain`** | 20 | 4,750 | 250 | 5,000 | 2, 3, 4 |
## Schema (both)
| column | type | meaning |
| --- | --- | --- |
| `id` | string | stable row id (`source:split:idx`) |
| `domain` | string | closed domain label for that config |
| `difficulty` | int | 1–5 |
| `prompt` | string | user / problem text |
## `5-domain` — detailed
Full Milestone-1 pool remeshed to 5 router buckets.
**Difficulty:** 1=118, 2=92,844, 3=218,087, 4=14,812, 5=2,421
| domain | description / sources | train | test | total |
| --- | --- | ---: | ---: | ---: |
| `math` | GSM8K, MATH-500, AIME, AQuA-RAT, … | 102,658 | 5,442 | 108,100 |
| `code` | HumanEval, MBPP, BigCodeBench, … | 3,009 | 158 | 3,167 |
| `knowledge` | MMLU, MMLU-Pro, GPQA, ARC, TruthfulQA, GCI, … | 134,537 | 7,109 | 141,646 |
| `commonsense` | HellaSwag | 57,027 | 2,923 | 59,950 |
| `instruction` | Dolly-15k, IFEval | 14,637 | 782 | 15,419 |
## `20-domain` — detailed
[GCI-Bench](https://huggingface.co/datasets/Glint-Research/GCI_Bench) rows only
(GPL-3.0). `domain` = official GCI `topic`; topic labels from upstream `topicLabel`.
Difficulty: easy→2 / medium→3 / hard→4.
**Difficulty:** 2=1,447, 3=2,278, 4=1,275
| domain | topic label | train | test | total | difficulty (2/3/4) |
| --- | --- | ---: | ---: | ---: | --- |
| `agriculture` | Agriculture & Crops | 228 | 22 | 250 | 75/120/55 |
| `archaeology` | Archaeology | 237 | 13 | 250 | 69/121/60 |
| `architecture` | Architecture & Construction | 237 | 13 | 250 | 76/121/53 |
| `astronomy` | Astronomy & Space | 242 | 8 | 250 | 69/115/66 |
| `automotive` | Automotive Mechanics | 241 | 9 | 250 | 60/130/60 |
| `aviation` | Aviation | 241 | 9 | 250 | 74/117/59 |
| `chemistry` | Chemistry Lab Processes | 242 | 8 | 250 | 72/114/64 |
| `cooking` | Culinary Science | 241 | 9 | 250 | 82/105/63 |
| `energy` | Renewable Energy | 232 | 18 | 250 | 81/103/66 |
| `finance` | Personal Finance | 239 | 11 | 250 | 74/104/72 |
| `gardening` | Home Gardening | 235 | 15 | 250 | 75/110/65 |
| `hardware` | Computer Hardware | 237 | 13 | 250 | 66/113/71 |
| `marine` | Marine Biology | 237 | 13 | 250 | 87/94/69 |
| `music` | Music Theory & Instruments | 239 | 11 | 250 | 82/113/55 |
| `photography` | Photography | 236 | 14 | 250 | 60/111/79 |
| `physiology` | Human Physiology | 235 | 15 | 250 | 66/113/71 |
| `sports` | Sports Training | 233 | 17 | 250 | 76/120/54 |
| `textiles` | Textile & Fashion | 245 | 5 | 250 | 75/108/67 |
| `weather` | Weather & Climate | 239 | 11 | 250 | 70/109/71 |
| `wildlife` | Wildlife & Animal Behavior | 234 | 16 | 250 | 58/137/55 |
## Load
```python
from datasets import load_dataset
ds5 = load_dataset("James-Cuda/tinyrouter-m1", "5-domain", split="train")
ds20 = load_dataset("James-Cuda/tinyrouter-m1", "20-domain", split="train")
print(ds5[0]["domain"], ds5[0]["difficulty"])
print(ds20[0]["domain"], ds20[0]["difficulty"])
```
Built by `scripts/build_tinyrouter_m1_slim.py`.
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