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The paper introduces TINY_SCHILLER, a compact German drama corpus designed for small language models, which simplifies the process of prototyping, fine-tuning, and educational use of German literary texts. By providing a single-file resource that circumvents the need for extensive parser engineering, it enables researchers to quickly access and utilize German literature for model training. The key result is that this 2.07-megabyte corpus allows a small language model to engage with German literary text with just one line of code, significantly lowering the barrier to entry for experimentation in this domain.
Accessing German literary texts for small language models is now as easy as a single line of code.
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.