Pre-Training and Fine-Tuning Techniques

 Pre-training is a process where a model is trained on a large and diverse text corpus, such as the entire internet, to learn general language representations. 

The model is then fine-tuned for a specific task, like sentiment analysis or text classification. This approach has shown impressive results in improving the performance of large language models.

• Integration of domain-specific knowledge: Large language models can be further trained on a particular domain, like legal texts or medical documents, to improve their performance on specific tasks. 
  This approach, known as domain adaptation, has been shown to improve the accuracy of large language models on certain tasks.