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- license: cc-by-nc-sa-4.0
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- # OmniCult
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- OmniCult is a high-quality, curated dataset designed for the **continued pre-training** and fine-tuning of compact language models (e.g., Quark 135M). It bridges the gap between classical humanistic thought and rigorous scientific logic.
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- ## 🎯 Core Topics
 
 
 
 
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- The dataset is architected around four primary intellectual pillars:
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- * **Higher Geometry & Spatial Logic:** Foundational texts on multi-dimensional space, tesseracts, and geometric abstraction.
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- * **Classical Literature & Philology:** The complete works of foundational English playwrights and poets, preserving archaic syntax and complex narrative structures.
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- * **Scientific Method & Natural Philosophy:** Historical treatises on physics, electromagnetism, and the evolution of scientific inquiry.
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- * **Lexical Precision:** Structured dictionary data focused on scientific and technical terminology from the 19th and early 20th centuries.
 
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- ## 🧠 Neural-Ready Features
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- * **Semantic Tagging:** Integrated `[CONCEPT: ...]` metadata to reinforce cross-domain reasoning (Logical, Detective, and Scientific reasoning).
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- * **High Fidelity:** Total removal of OCR noise and modern editorial bloat. Original Victorian punctuation and emphasis are preserved to maintain stylistic depth.
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- * **Optimized Chunking:** Text segments are precisely balanced (~2,000 tokens) to fit modern transformer context windows.
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- ## 🚀 Future Scope
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- OmniCult is a living project. Regular updates will expand the archive with further explorations into classical philosophy, early quantum theory, and expanded linguistic corpora.
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- ## ⚖️ License
 
 
 
 
 
 
 
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- Licensed under **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)**.
 
 
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- *Intended for research and educational use only.*
 
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+ # OmniBook
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+ OmniBook is a large‑scale, high‑quality English text corpus designed for pre‑training and fine‑tuning language models of any size – from compact 135M parameter models to larger architectures. It collects thousands of complete books from **Project Gutenberg** and other public domain sources, covering the full spectrum of human knowledge, literature, and science.
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+ - **Language:** English
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+ - **Size:** ~25 GB (raw text)
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+ - **Source:** Project Gutenberg + curated additions
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+ - **License:** CC BY‑NC‑SA 4.0
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+
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  ---
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+
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+ ## 📚 Dataset Composition
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+ OmniBook is built around **general culture** and includes:
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+ - **Complete works**
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+ - **Historical scientific texts**
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+ - **Philosophy and political thought**
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+ - **Poetry, drama, and essays**
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+
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+ All texts are **unmodified** from their original Project Gutenberg sources except for:
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+ - Removal of boilerplate headers/footers
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+ - Deduplication of near‑identical editions
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+
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  ---
 
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+ ## 🧠 Key Features
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+ ### High Fidelity
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+ - **No OCR noise** – texts are manually proofread by Project Gutenberg volunteers.
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+ - **Original punctuation and emphasis** preserved (Victorian‑era italics, archaic spelling where intentional).
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+
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+ ---
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+ ## 📊 Example Record
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+ ```json
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+ {
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+ "text": "It is a truth universally acknowledged, that a single man in possession of a good fortune, must be in want of a wife..."
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+ }
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+ ```
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+ **🤝 How to Use This Dataset**
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+ ```python
 
 
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+ from datasets import load_dataset
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+ dataset = load_dataset("OvercastLab/OmniBook", split="train")
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+ ```
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+ Or stream directly (recommended for large‑scale training):
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+ ```python
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+ dataset = load_dataset("OvercastLab/OmniBook", streaming=True)
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+ for example in dataset:
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+ text = example["text"]
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+ # your training loop
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+ ```
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+ **📈 Future Plans**
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+ - Add classical Greek and Latin works (in translation)
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+ - Expand with early 20th‑century scientific journals (public domain)
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+ OmniBook is maintained by OvercastLab. For questions or contributions, please open an issue on the Hugging Face repository.