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--- |
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language: |
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- fr |
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license: mit |
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size_categories: |
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- 1M<n<10M |
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task_categories: |
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- text-generation |
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pretty_name: Tiny Molière |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 2387600 |
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num_examples: 1 |
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download_size: 2387600 |
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dataset_size: 2387600 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/tinymoliere.txt |
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tags: |
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- literature |
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- french-literature |
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- moliere |
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- classical-text |
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- character-level |
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--- |
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# tiny-moliere |
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A dataset repo generating `tinymoliere.txt` containing Molière's complete work. |
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Inspired by [tinyshakespeare](https://github.com/karpathy/char-rnn/blob/master/data/tinyshakespeare/input.txt) by Andrej Karpathy, this project provides a consolidated small text corpus ideal for training and learning with small transformer models. |
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## What it does |
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Downloads Molière's complete works from public PDFs, processes them to remove headers/footers and table of contents, then outputs a single clean text file suitable for machine learning tasks. |
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## Usage |
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```bash |
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uv sync |
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uv run python main.py |
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``` |
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This will: |
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1. Download the source PDFs to `data/` directory |
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2. Process and clean the text |
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3. Generate `data/tinymoliere.txt` |
