What type of data is used to train LLMs?

Large Language Models (LLMs) are trained on vast amounts of text data, including: 1. Books and articles: Fiction and non-fiction books, academic papers, and online articles. 2. Web pages: Websites, blogs, and online forums. 3. Social media: Platforms like Twitter, Facebook, and Instagram. 4. Conversations: Transcripts of conversations, dialogues, and chats. 5. Product reviews: Reviews of products, services, and apps. 6. Forums and discussions: Online forums, comments, and discussion boards. 7. Text datasets: Specialized datasets like Wikipedia, Reddit, OpenWebText and usecase specific custom training datasets. This diverse range of text data helps LLMs learn about: - Language structure and grammar - Vocabulary and semantics - Context and nuances - Style and tone By training on this vast amount of text data, LLMs can generate coherent and natural-sounding language outputs!

What type of data is used to train LLMs?

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