| # Tiny memorization synthetic datasets | |
| Uniformly-random token datasets replicating the methodology of | |
| ["How much do language models memorize?"](https://huggingface.co/papers/2505.24832) | |
| (arXiv:2505.24832). | |
| Each variant `/<tag>/dataset_tokens.npy` is an `(N, 65)` int64 array: a BOS token | |
| (id 2048) followed by 64 uniform iid tokens in `[0, 2048)`. The exact entropy is | |
| `H = N * 64 * log2(2048) = N * 704` bits (see each `generation_params.json`). | |
| Tokens are sampled with `numpy.random.default_rng(seed)`; the seed is recorded per variant. | |