Introduction to Fine-Tuning

Learn about the importance of fine-tuning for LLMs.


Fine-tuning refers to the process of adjusting the parameters of a pretrained model on a specific dataset to enhance its performance on a specific task. In large language models, fine-tuning is generally used to transform a foundation model into a specialized one for a particular use case.

Fine-tuning large language models brings several key benefits. It sharpens the model’s skills for specific jobs, like answering medical questions or writing legal documents. Learning how to fine-tune models can help individuals adapt powerful large language models for their specific use cases.

Get hands-on with 1200+ tech skills courses.