README.md

metadata

license: mit
task_categories:
  - text-generation
language:
  - en
tags:
  - agent
size_categories:
  - 100M<n<1B

WebText-3 Corpus

WebText-3 is a large-scale, diverse text corpus collected from publicly available web pages. It contains cleaned and normalized sentences suitable for natural language processing (NLP), machine learning, and AI training.

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Dataset Overview

• Format: Plain text (.txt), one sentence per line
• Approximate Size: 200,000+ sentences
• Languages: Primarily English, with occasional Hebrew content
• Source Types: Wikipedia articles, technology news sites, blogs, educational resources, social media platforms, and developer documentation
• Content Coverage:
  • Artificial intelligence, machine learning, and large language models
  • Programming languages, software, and tools
  • Science, astronomy, and mathematics
  • Technology trends, cloud platforms, and AI research
  • News, politics, global events, and human-related topics
  • Entertainment, gaming, online culture, and social media
  • Miscellaneous topics such as philosophy, space, and general knowledge

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Data Characteristics

• Sentence Length: Varies; short to medium-length sentences
• Cleanliness: Text has been cleaned to remove invisible characters, unusual symbols, and excessive whitespace
• Usability: Ready for NLP tasks such as language modeling, text classification, summarization, or AI fine-tuning

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Example Usage

• Training large language models or chatbots
• Benchmarking NLP algorithms
• Data analysis or text mining
• Educational research on language patterns

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WebText-3 provides a rich and broad textual resource suitable for both research and practical AI applications.