| --- |
| 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. |
|
|
