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最新的 IBM Certified watsonx Generative AI Engineer - Associate C1000-185 免費考試真題 (Q193-Q198):

問題 #193
In the context of generative AI, you are tasked with optimizing a model's performance for a variety of use cases by tuning the prompts. One of your colleagues mentions using a "soft prompt" to improve the model's adaptability.
What best describes the difference between a hard prompt and a soft prompt?

A. A soft prompt is a fixed string of text used in fine-tuning, while a hard prompt adjusts dynamically based on input data.
B. Soft prompts are more readable and natural, whereas hard prompts consist of short, technical instructions.
C. Hard prompts are less efficient because they need to be re-trained with each task, while soft prompts are more versatile and adaptive across multiple tasks.
D. A hard prompt explicitly specifies all constraints, while a soft prompt relies on implicit learning from continuous inputs during training.

答案：D

問題 #194
Which of the following factors is most likely to contribute to biased outputs in a generative AI system?

A. The use of too many input parameters in the prompt.
B. Repeatedly using the same prompt for multiple generations.
C. Prompt length that exceeds the model's context window.
D. Insufficient diversity in the training dataset used to train the model.

答案：D

問題 #195
In which scenario would using a soft prompt be more beneficial than a hard prompt in optimizing generative AI outputs?

A. When fine-tuning a pre-trained model for domain-specific tasks, allowing the system to adapt its understanding through learned embeddings.
B. When the model needs to generate a strictly factual output with minimal deviation from the prompt.
C. When the prompt needs to be manually adjusted by the user in real time during interaction with the AI.
D. When the task requires explicit and consistent user instructions to ensure deterministic outcomes.

答案：A

問題 #196
You are tasked with designing a prompt using a few-shot strategy for Watsonx AI to generate a legal contract summary. You provide two examples of contract summaries before asking the model to summarize a new contract.
Which of the following options best demonstrates an effective few-shot prompt for this task?

A. "Example 1: [First Contract]
B. "Example 1: [First Contract] Summary: [First Contract Summary]
Example 2: [Second Contract] Summary: [Second Contract Summary]
Generate a summary of the following contract: [New Contract]."
C. "Generate a summary for [New Contract]."
D. "Provide a summary of the following contract: [New Contract].
Example 1: [First Contract]
Summary: [First Contract Summary]
Example 2: [Second Contract]
Summary: [Second Contract Summary]."

答案：B

問題 #197
You are tasked with fine-tuning a pre-trained large language model (LLM) using synthetic data generated through the IBM watsonx user interface.
Which of the following steps should you follow to ensure the model is fine-tuned correctly and the synthetic data is used effectively?

A. Directly upload synthetic data without inspecting or validating it and initiate the fine-tuning process.
B. Select the pre-trained model, generate synthetic data, and fine-tune the model using default parameters without further customization.
C. Use synthetic data as a replacement for real-world data without cross-validation or any quality control measures.
D. Select the pre-trained model, generate synthetic data, inspect the generated data for quality, and fine-tune the model by adjusting hyperparameters and training settings.

答案：D

問題 #198
......

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C1000-185真題材料，C1000-185認證考試解析

最佳的C1000-185真題材料和認證考試的領導者材料和精准覆盖的C1000-185認證考試解析

最新的 IBM Certified watsonx Generative AI Engineer - Associate C1000-185 免費考試真題 (Q193-Q198):

高水準的C1000-185真題材料，最好的學習資料幫助妳壹次性通過C1000-185考試

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