OmniBook / README.md
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metadata
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

{
  "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


from datasets import load_dataset

dataset = load_dataset("OvercastLab/OmniBook", split="train")

Or stream directly (recommended for large‑scale training):

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.