LLM Training and Development

Arpita Sharma11 Sep, 2024News

Large Language Models (LLMs) are trained through a two-phase process: pre-training and fine-tuning. In pre-training, the model is exposed to vast amounts of text data from books, websites, and articles to learn general language patterns, such as sentence structure, grammar, and context. The model processes this data using a transformer architecture, which helps it understand relationships between words. After pre-training, the model undergoes fine-tuning, where it is trained on more specific datasets tailored to particular tasks, such as answering questions or generating creative content. This fine-tuning ensures the model performs accurately in real-world applications like customer service or content creation. Training an LLM requires massive computational power and time, but the result is a highly intelligent model capable of understanding and generating human-like text.