AIF-C01 · Question #357
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…
The correct answer is C. Continued pre-training. Continued pre-training uses the company’s unlabeled domain data to further train a pre-trained LLM, expanding its knowledge in specific technical areas without requiring labeled datasets. This makes it the best fit for the scenario.
Question
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?
Options
- AFull training
- BSupervised fine-tuning
- CContinued pre-training
- DRetrieval Augmented Generation (RAG)
How the community answered
(34 responses)- A3% (1)
- B9% (3)
- C85% (29)
- D3% (1)
Explanation
Continued pre-training uses the company’s unlabeled domain data to further train a pre-trained LLM, expanding its knowledge in specific technical areas without requiring labeled datasets. This makes it the best fit for the scenario.
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