| license: mit | |
| task_categories: | |
| - text-generation | |
| tags: | |
| - synthetic-data | |
| - pre-training | |
| - language-modeling | |
| # Synthetic Pre-pretraining Datasets | |
| This repository contains the pre-processed datasets released with the paper [Synthetic Pre-pretraining Survives Scale, but Not as a Grammatical Prior](https://huggingface.co/papers/2609.39827). | |
| The datasets cover both pre-pretraining (PPT) tasks and pre-training (PT) mixtures used in the paper. PPT tasks include k-Shuffle Dyck, Set, MP-Struct Core, and NCA; PT mixtures include C4, SmolLM3, Olmo3, Marin, and FineWeb-Edu configurations. The pre-processed data are tokenized and organized by configuration. | |
| - Paper: [https://huggingface.co/papers/2609.39827](https://huggingface.co/papers/2609.39827) | |
| - Code: [https://github.com/gucci-j/verify-ppt-at-scale](https://github.com/gucci-j/verify-ppt-at-scale) | |
| - Project page: [https://huggingface.co/verify-ppt](https://huggingface.co/verify-ppt) | |
| For details on dataset composition, preprocessing, training, and evaluation, please refer to the [GitHub repository](https://github.com/gucci-j/verify-ppt-at-scale). |