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