---
pretty_name: "MMLU: 500 random test questions (QiSpace)"
license: mit
tags:
- lightrider
- quantum-provenance
- evaluation
- subset
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-00000-of-00001.parquet
---
# MMLU: 500 random test questions (QiSpace)

500 rows chosen at random from the 14042 rows of the `test` split of [cais/mmlu (all)](https://huggingface.co/datasets/cais/mmlu), revision `c30699e8356d`. The rows are unchanged; `_lr_source_index` gives each row's position in the source split.

The rows keep the source dataset's MIT license ([license text](https://github.com/hendrycks/test/blob/master/LICENSE)).

The dataset was generated from a seed drawn from `qispace_kds_001` through
[Light Rider](https://entropy.lightriderinc.com). The seed comes with a signed receipt, so anyone
can check where the data came from and regenerate it exactly.

## Provenance

| | |
|---|---|
| Entropy source | `qispace_kds_001` |
| Drawn | 2026-10-19 17:54 UTC |
| Light Rider request | `lr_sreq_4e103f300d674c3c83421b3a2be5b913` |
| Seed | `9f51784980c33e204321de4d235ae41be73ab9a55980c898a7f0d9a69b543ec9` |
| Generator | `eval_subset/1` |
| Rows | 500 |

Parameters:

```json
{
  "source_dataset": "cais/mmlu",
  "config": "all",
  "split": "test",
  "revision": "c30699e8356da336a370243923dbaf21066bb9fe",
  "source_num_rows": 14042,
  "n": 500,
  "requested": {
    "n": 500,
    "fraction": null
  }
}
```

<details>
<summary>Full technical record</summary>

| | |
|---|---|
| Receipt signature | Ed25519, key fingerprint (SHA-256) `363b9750db0acd16ab188e4ecc8a58e4f811b28f5870cfc3ba4522274a11645e` |
| Output commitment (signed) | `sha256:8d81a1f45d1c1cfec1e7ffb372d89f7eb7eccfd3e5b0b5b061fac8cb8e2cb350` |
| Commitment salt | `6155d874ceb1462bbcba8a7db822419fe9b7b01019b872122022a0eb19246a44` |
| Generator stream | LR-ChaCha20 v1, domain `eval_subset` |
| Content hash (lr-canonical-jsonl/1) | `729f451c60bb7ff33073a161dd2316e668b5f1db6cf438d8aabf9ef82b932a53` |
| Built with | lightrider-huggingface 0.1.1, lightrider 1.6.2, pyarrow 26.0.0 |

The complete record is in [`lightrider_provenance.json`](lightrider_provenance.json). The signed receipt, exactly as
issued, is in [`receipt.json`](receipt.json).

</details>

## How to verify

```bash
pip install lightrider-huggingface
```

```python
import lightrider_huggingface as lrhf

print(lrhf.verify("LightRiderInc/mmlu-random-sample-qispace"))
```

This needs no Light Rider account. It prints each check as PASS or FAIL.

For a subset of a very large dataset, `lrhf.verify(..., indices_only=True)` skips re-downloading the source.

## How verification works

1. **The receipt is genuine.** Light Rider signs every draw's receipt (Ed25519). The public key is
   at [entropy.lightriderinc.com/api/v1/public-key](https://entropy.lightriderinc.com/api/v1/public-key).
2. **The seed is that draw's output.** The signed receipt includes a hash of the exact bytes drawn,
   so a seed from any other draw doesn't match.
3. **The data follows from the seed.** Generation is deterministic, so `verify` rebuilds every row
   from the seed and parameters and compares it with the published data.

## What this doesn't claim

That quantum randomness makes this dataset better than one built with a good classical generator.
It's an alternative source whose origin you can check. A receipt also can't show that the publisher
drew only once; its timestamp shows when the draw happened.