mlsanityData to 14 Oct 2026

TINY_SCHILLER: A Drop-In German Drama Corpus for Small Language Models

arXiv 2607.19992 ↗First posted 22 Jul 2026cs.CL cs.AI cs.DLcited by 0

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Abstract (arXiv)

tiny_schiller closes the small-language-model prototyping, fine-tuning, education, and research gap for German literary text, providing a single-file, drop-in counterpart to Karpathy's tiny_shakespeare. The available German literary corpora are larger and richer, but require parser engineering before a single line of training or fine-tuning code can run. tiny_schiller is a 2.07-megabyte single file of eleven public-domain Schiller dramas, sourced from DraCor's GerDraCor export (CC0) and processed by deterministic parser engineering. Character-level, GPT-2 byte-pair encoding, and cl100k_base tokenization splits, an instruction-formatted dialogue-completion split, and 89 per-character persona splits load from a single HuggingFace call. A small language model literally reaches German literary text in one line of code.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 17 references that are in the map. First posted on arXiv 22 Jul 2026.

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References · 4

  1. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,918
  2. 2020How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Modelscited by 318
  3. 2023Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Modelscited by 192
  4. 2025Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corporacited by 88

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