AWS Certified AI Practitioner (AIF-C01) — Question 232

A company is using a pre-trained large language model (LLM). The LLM must perform multiple tasks that require specific domain knowledge. The LLM does not have information about several technical topics in the domain. The company has unlabeled data that the company can use to fine-tune the model.

Which fine-tuning method will meet these requirements?

Answer options

• A. Full training
• B. Supervised fine-tuning
• C. Continued pre-training
• D. Retrieval Augmented Generation (RAG)

Correct answer: C

Explanation

The correct choice is Continued pre-training as it allows the model to learn from unlabeled data in its specific domain, enhancing its performance on related tasks. Full training and supervised fine-tuning require labeled datasets, which are not available in this scenario. Retrieval Augmented Generation (RAG) is not a fine-tuning method but rather a technique for enhancing information retrieval.