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!