| --- |
| license: cc-by-nc-sa-4.0 |
| task_categories: |
| - text-generation |
| language: |
| - en |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| ## 📚 Dataset Composition |
|
|
| OmniBook is built around **general culture** and includes: |
|
|
| - **Complete works** |
| - **Historical scientific texts** |
| - **Philosophy and political thought** |
| - **Poetry, drama, and essays** |
|
|
| All texts are **unmodified** from their original Project Gutenberg sources except for: |
| - Removal of boilerplate headers/footers |
| - Deduplication of near‑identical editions |
|
|
| --- |
|
|
| ## 🧠 Key Features |
|
|
| ### High Fidelity |
| - **No OCR noise** – texts are manually proofread by Project Gutenberg volunteers. |
| - **Original punctuation and emphasis** preserved (Victorian‑era italics, archaic spelling where intentional). |
|
|
| --- |
|
|
| ## 📊 Example Record |
|
|
| ```json |
| { |
| "text": "It is a truth universally acknowledged, that a single man in possession of a good fortune, must be in want of a wife..." |
| } |
| ``` |
|
|
| **🤝 How to Use This Dataset** |
|
|
| ```python |
| |
| from datasets import load_dataset |
| |
| dataset = load_dataset("OvercastLab/OmniBook", split="train") |
| |
| ``` |
| Or stream directly (recommended for large‑scale training): |
| ```python |
| dataset = load_dataset("OvercastLab/OmniBook", streaming=True) |
| for example in dataset: |
| text = example["text"] |
| # your training loop |
| ``` |
|
|
| **📈 Future Plans** |
| - Add classical Greek and Latin works (in translation) |
| - Expand with early 20th‑century scientific journals (public domain) |
|
|
| *OmniBook is maintained by **OvercastLab**. For questions or contributions, please open an issue on the Hugging Face repository.* |
