| --- |
| language: |
| - de |
| license: |
| - cc0-1.0 |
| license_details: "Corpus text is sourced from DraCor's GerDraCor export (CC0). Underlying works (Schiller, d. 1805) are public domain. Code/docs are MIT (see LICENSE)." |
| task_categories: |
| - text-generation |
| pretty_name: tiny_schiller |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| # tiny_schiller |
| |
| A small (~2 MB) German-language analogue to Karpathy's [tiny_shakespeare](https://huggingface.co/datasets/karpathy/tiny_shakespeare) — 11 of Friedrich Schiller's dramatic works, cleaned and tokenised for tutorial-scale language models. |
| |
| For a compact, agent-friendly summary (file inventory, load patterns, licensing), see [DATA_CARD.md](DATA_CARD.md). |
| |
| *"Das Leben ist nur ein Moment, der Tod ist auch nur einer."* — Friedrich Schiller |
| |
|  |
| |
| ## Corpus |
| |
| ~2.07 MB · 11 works · 2,019,857 characters · sourced from DraCor / GerDraCor (CC0). See [LICENSING.md](LICENSING.md) for details. |
| |
| | Tokenizer | Tokens | chars/token | |
| |---|---|---| |
| | character-level | 2,019,857 | 1.00 | |
| | GPT-2 BPE | 854,611 | 2.36 | |
| | `cl100k_base` | 642,593 | 3.14 | |
|
|
| Use **character-level** for teaching-scale models (88-token vocab, no tokenizer needed). Use **cl100k** over GPT-2 when sequence length matters — German umlauts and compounds tokenise 25% more efficiently. |
|
|
| ## Works |
|
|
| - Die Räuber |
| - Die Verschwörung des Fiesco zu Genua |
| - Kabale und Liebe |
| - Don Carlos, Infant von Spanien |
| - Wallensteins Lager |
| - Maria Stuart |
| - Die Jungfrau von Orleans |
| - Die Braut von Messina oder Die feindlichen Brüder |
| - Wilhelm Tell |
| - Die Piccolomini |
| - Wallensteins Tod |
|
|
| ## Quick Start — nanoGPT |
|
|
| ```bash |
| python schiller_char/prepare.py # char-level, 88-vocab |
| python schiller_bpe/prepare.py # GPT-2 BPE, 50k vocab |
| python schiller_cl100k/prepare.py # cl100k, 100k vocab |
| ``` |
|
|
| ## HuggingFace Datasets |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("mrkschtr/tiny_schiller") |
| print(ds["train"][0]["title"]) |
| print(ds["train"][0]["text"][:200]) |
| ``` |
|
|
| 9 works in train, 2 in test (Wilhelm Tell, Die Braut von Messina). Each row is one complete work with `title` and `text` fields. |
|
|
| ## Instruction & Character Datasets |
|
|
| Pre-built instruction-format parquet files are in `data/` on the Hub. |
|
|
| **General dialogue style** — 7,607 examples teaching Schiller's dramatic register: |
| ```python |
| ds = load_dataset("mrkschtr/tiny_schiller", data_files="data/instruct.parquet", split="train") |
| print(ds[0]["prompt"]) |
| print(ds[0]["completion"]) |
| ``` |
|
|
| **Per-character** — fine-tune a model to respond as a specific character: |
| ```python |
| # 330 examples as Wallenstein · 325 as Carlos · 313 as Fiesco |
| # 237 as Marquis · 195 as Ferdinand · 194 as Königin · ... |
| ds = load_dataset("mrkschtr/tiny_schiller", data_files="data/char_WALLENSTEIN.parquet", split="train") |
| ``` |
|
|
| Rebuild locally (generates `data/instruct.parquet` + 89 `data/char_*.parquet` files by default): |
| ```bash |
| python scripts/build_instruct.py # all characters |
| python scripts/build_instruct.py --list-characters # show available characters + turn counts |
| python scripts/build_instruct.py --character KARL # single character only |
| ``` |
|
|
| ## Fine-tuning small LLMs |
|
|
| ```bash |
| pip install transformers trl datasets accelerate |
| python examples/finetune_sft.py --model TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
| ``` |
|
|
| Default context window is 2048 tokens. Match your model with `--context_length`: |
|
|
| ```bash |
| python examples/finetune_sft.py --model microsoft/Phi-3-mini-4k-instruct --context_length 4096 |
| python examples/finetune_sft.py --model Qwen/Qwen2.5-0.5B --context_length 4096 |
| ``` |
|
|
| Tested: TinyLlama 1.1B · Phi-3 Mini 3.8B · Llama 3.2 1B/3B · Qwen2.5 0.5B–3B. |
|
|
| ## License |
|
|
| Text: public domain (Schiller died 1805) and sourced from DraCor / GerDraCor under CC0. See [LICENSING.md](LICENSING.md) for details. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{schutera2023tinyschiller, |
| author = {Schutera, Mark}, |
| title = {tiny\_schiller: a small German Schiller corpus for small language models}, |
| year = {2023}, |
| howpublished = {\url{https://github.com/schutera/tiny_schiller}}, |
| note = {Source texts: DraCor / GerDraCor (CC0) and public domain.} |
| } |
| ``` |
|
|