Training of Large Language Models (LLMs) usually happens in two main stages: pre-training and fine-tuning. In the first stage, the model is exposed to extensive writing to acclimatize it to the general principles and interrelationships in a language not necessarily targeting any particular task. This step is aimed at making sure that there is a ground understanding of human language. The other phase follows, which is fine-tuning, and it narrows down on particular tasks or domains, thus refining its specialized application.