Unraveling the Enigma of Large Language Models: A Journey into Pretraining and Their Marvelous Applications
Hey there, language enthusiasts! Have you ever wondered how those amazing language models like BERT, GPT, and T5 come into existence? Well, get ready for an exciting journey into the world of pretraining large language models (LLM). In this guide, we’ll demystify the process of training these remarkable models and explore different types of LLMs, such as encoder-only, decoder-only, and sequence-to-sequence models. Don’t worry if you’re not an expert in the field — we’ll make sure the journey is smooth and enjoyable. So, grab your favorite beverage and let’s dive into the magical realm of pretraining large language models!
How Large Language Models are Trained:
To create those powerful language models we all love, they undergo an intricate process called pretraining. During pretraining, the model is fed a vast amount of data — think billions of sentences! This data helps the model learn the patterns and structures of language, turning it into a language genius.
The data used for pretraining comes from various sources, including books, articles, websites, and more. This data is usually scraped from various sources of internet and requires a huge amount of preprocessing before it can be used…
