Update README.md

README.md

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 license: cc0-1.0
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-# Dataset Card for OpenTextVault
+# Dataset Card for OpenTextVault_FromTheNetwork
 
 ## 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.
+**OpenTextVault_FromTheNetwork** is an open, legally compliant dataset consisting of raw, unlabeled text files (TXT format) and compressed archives containing multilingual textual data collected from various network sources.  
+This dataset offers **high-quality, large-scale, and diverse raw textual content**, totaling **hundreds of billions of unlabeled pure text tokens**, suitable for natural language processing tasks such as training and fine-tuning large language models, as well as linguistic research.  
+All included data is gathered through legal and ethical means, ensuring no copyright infringement.
 
-- **Curated by:**  OpenTextVault
+- **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.
+- Text data is sourced from publicly available or legally distributable network resources.  
+- Data is provided in plain text files and/or compressed archives for easy access.
 
 ## Uses
 
 ### Direct Use
 
-- Pretraining or fine-tuning language models (including large language models).  
+- Pretraining or fine-tuning language models, including large-scale models.  
 - Unsupervised and self-supervised NLP research.  
-- Linguistic and stylistic analysis.  
+- Multilingual raw text analysis, including stylistic and diversity studies.
 
 ### 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.
+- This dataset is **not** designed for supervised learning tasks requiring labeled or annotated data.  
+- Users should ensure compliance with relevant legal and ethical standards when utilizing 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.
+- Contains folders of raw text files (.txt) and compressed archives (.zip, .tar.gz).  
+- Each text file holds plain, unlabeled raw textual data without manual annotations or metadata.
 
 ## 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.
+The dataset was created to provide a **free, open, and legally compliant extremely large-scale resource of unlabeled raw textual data from network sources**, enabling researchers and practitioners to train and fine-tune language models without copyright concerns.
 
 ### Source Data
 
-- Texts were collected from sources verified to be legal and compliant with redistribution policies.  
+- Collected from verified legal and publicly accessible network sources.  
 
 ### Data Collection and Processing
 
-- Data is cleaned to remove corrupted files and obvious non-text content.  
-- No manual labeling or annotation was performed.
+- Cleaned to remove corrupted files and non-text content.  
+- Maintained in raw form without manual annotation or labeling.
 
 ## 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.
+- As raw and unlabeled data, it may contain biases inherited from original network sources.  
+- May include unfiltered language such as slang, dialects, or offensive expressions.
 
 ## 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.  
+Released under the **CC0 1.0 Public Domain License**.  
+No citation or attribution is required for use or publication.
+
+---
+
+**Note:** This dataset consists of **high-quality, extremely large-scale (hundreds of billions of tokens), and diverse unlabeled raw text from network sources**, making it highly suitable for **training or fine-tuning large language models**.