# 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.