Update README.md

README.md

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 license: cc0-1.0
 language:
 - zh
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 ### Dataset Description
 
-**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.
+**OpenTextVault_FromTheNetwork** is an open, legally compliant dataset consisting of raw, unlabeled text files (TXT format) and compressed archives collected from diverse network sources.  
+It provides **high-quality, large-scale, and diverse raw textual content**, totaling **hundreds of billions of unlabeled pure text tokens**, suitable for a wide range of natural language processing tasks, such as large language model (LLM) training, fine-tuning, and linguistic research.
+
+A key highlight of this dataset is its **extensive amount of high-quality unlabeled Chinese text**, covering a broad range of topics, domains, and linguistic styles—from news and literature to online discussions and commentary.  
+All materials are collected through **legal and ethical channels**, ensuring full compliance and no copyright violations.
 
 - **Curated by:** OpenTextVault  
-- **Language(s):** Multiple languages (depending on source)  
+- **Language(s):** Primarily Chinese, with additional multilingual content  
 - **License:** CC0 1.0 Universal (Public Domain)  
 
-### Dataset Sources
+---
+
+## Dataset Sources
 
-- 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.
+- Text data originates from legally distributable or publicly accessible network resources.  
+- Provided in plain text (.txt) and/or compressed archive formats (.zip, .tar.gz) for direct usability.
+
+---
 
 ## Uses
 
 ### Direct Use
 
-- Pretraining or fine-tuning language models, including large-scale models.  
-- Unsupervised and self-supervised NLP research.  
-- Multilingual raw text analysis, including stylistic and diversity studies.
+- Pretraining or fine-tuning large-scale language models (especially for Chinese and multilingual NLP).  
+- Unsupervised or self-supervised language model research.  
+- Analysis of linguistic diversity, stylistic variation, and large-scale text distributions.
 
 ### Out-of-Scope Use
 
-- 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.
+- Not intended for supervised learning tasks requiring labeled or annotated data.  
+- Users must ensure compliance with local laws, ethical standards, and data governance policies.
+
+---
 
 ## Dataset Structure
 
-- 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.
+- Organized into directories containing raw text files (.txt) and compressed archives (.zip, .tar.gz).  
+- Each text file contains unprocessed, unlabeled natural text without metadata or annotation.
+
+---
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-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.
+The dataset was created to offer a **free, open, and legally safe large-scale source of unlabeled textual data from the internet**, enabling open research, model training, and large-scale language model experimentation—particularly for the **Chinese language**.
 
 ### Source Data
 
-- Collected from verified legal and publicly accessible network sources.  
+- Collected exclusively from verified, legally accessible, and ethically sound network sources.  
 
 ### Data Collection and Processing
 
-- Cleaned to remove corrupted files and non-text content.  
-- Maintained in raw form without manual annotation or labeling.
+- Files are cleaned to remove corrupted or non-text content.  
+- Maintained in raw form to preserve linguistic diversity and authenticity.  
+
+---
 
 ## Bias, Risks, and Limitations
 
-- 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.
+- As raw, unlabeled network text, the dataset may reflect biases present in the original online sources.  
+- Content may include slang, dialectal expressions, or potentially offensive language.
+
+---
 
 ## Citation
 
 Released under the **CC0 1.0 Public Domain License**.  
-No citation or attribution is required for use or publication.
+No citation or attribution is required, though acknowledgment of **OpenTextVault_FromTheNetwork** is appreciated.
 
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-**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**.
+**Note:**  
+This dataset contains **a massive volume of high-quality unlabeled Chinese text**, making it exceptionally suitable for **training, pretraining, and fine-tuning large Chinese or multilingual language models**.