license: cc0-1.0
Dataset Card for OpenTextVault
Dataset Details
Dataset Description
OpenTextVault is an open, legally compliant dataset consisting of raw text files (TXT format) and compressed archives containing multilingual, unlabeled textual data.
The dataset is curated to provide high-quality, diverse textual content suitable for natural language processing tasks, including language model training, fine-tuning, and linguistic research.
All data included in this dataset are obtained through legal and ethical means, ensuring no copyright infringement.
- Curated by: OpenTextVault
- Language(s): Multiple languages (depending on source)
- License: CC0 1.0 Universal (Public Domain)
Dataset Sources
- Text content comes from publicly available or otherwise legally distributable sources.
- Data is provided as plain text files or compressed archives for easy use.
Uses
Direct Use
- Pretraining or fine-tuning language models (including large language models).
- Unsupervised and self-supervised NLP research.
- Linguistic and stylistic analysis.
Out-of-Scope Use
- This dataset is not intended for supervised learning tasks requiring labeled data.
- Users should ensure compliance with any local laws and ethical standards when using this dataset.
Dataset Structure
- The dataset contains folders of raw text files (.txt) and/or compressed archives (.zip, .tar.gz).
- Each text file contains plain, unlabeled text data.
- No additional annotations or metadata are provided.
Dataset Creation
Curation Rationale
The dataset was created to provide a free, open resource of raw textual data for NLP practitioners and researchers seeking diverse multilingual text for language model training without copyright concerns.
Source Data
- Texts were collected from sources verified to be legal and compliant with redistribution policies.
Data Collection and Processing
- Data is cleaned to remove corrupted files and obvious non-text content.
- No manual labeling or annotation was performed.
Bias, Risks, and Limitations
- Since the dataset is unlabeled and raw, users should be aware of potential biases inherited from the original sources.
- The dataset may contain unfiltered language reflecting real-world usage, including slang or offensive content.
Citation
This dataset is released under CC0 1.0 Public Domain License.
You are not required to cite or attribute this dataset in any use or publication.