AIF-C01 · Question #162
A company is using a pre-trained large language model (LLM) to extract information from documents. The company noticed that a newer LLM from a different provider is available on Amazon Bedrock. The…
The correct answer is C. Adjust the prompt template. Transitioning to a new large language model (LLM) on Amazon Bedrock typically involves minimal changes when the new model is pre-trained and available as a foundation model. Since the company is moving from one pre-trained LLM to another, the primary task is to ensure…
Question
A company is using a pre-trained large language model (LLM) to extract information from documents. The company noticed that a newer LLM from a different provider is available on Amazon Bedrock. The company wants to transition to the new LLM on Amazon Bedrock. What does the company need to do to transition to the new LLM?
Options
- ACreate a new labeled dataset
- BPerform feature engineering.
- CAdjust the prompt template.
- DFine-tune the LLM.
How the community answered
(27 responses)- A4% (1)
- B4% (1)
- C78% (21)
- D15% (4)
Explanation
Transitioning to a new large language model (LLM) on Amazon Bedrock typically involves minimal changes when the new model is pre-trained and available as a foundation model. Since the company is moving from one pre-trained LLM to another, the primary task is to ensure compatibility between the new model's input requirements and the existing application. Adjusting the prompt template is often necessary because different LLMs may have varying prompt formats, tokenization methods, or response behaviors, even for similar tasks like document When switching between foundation models in Amazon Bedrock, you may need to adjust the prompt template to align with the new model's expected input format and optimize its performance for your use case. Prompt engineering is critical to ensure the model understands the task and generates accurate outputs.
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