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最新的 IBM Certified watsonx Generative AI Engineer - Associate C1000-185 免費考試真題 (Q54-Q59):

問題 #54
You are optimizing a large language model (LLM) by prompt-tuning it for specific enterprise-level tasks. The goal is to initialize the prompt in such a way that it helps the model generalize well across various enterprise domains, such as finance, healthcare, and retail.
What is the most effective method to initialize the prompt for such a use case?

A. Start with a general prompt and gradually specialize it during fine-tuning
B. Use a short prompt that provides no guidance and allow the model to self-optimize
C. Use a single, highly specific prompt tailored to only one domain, such as finance
D. Initialize the prompt with an ensemble of prompts covering multiple domains

答案：D

問題 #55
When deploying a machine learning model in a highly regulated industry (e.g., healthcare or finance), which strategy is most effective to ensure ongoing model performance while adhering to AI governance standards?

A. Deploy the model with hard-coded rules to ensure it does not drift from expected behavior
B. Implement a model performance monitoring framework with fairness and bias detection metrics
C. Ensure model interpretability is maximized by simplifying the architecture to a linear model
D. Perform real-time continuous training of the model using live data from the production environment

答案：B

問題 #56
Your team has developed multiple versions of a custom Watsonx Generative AI model to address different use cases. During deployment, the client requires that all model versions be deployed concurrently, allowing requests to be routed to the appropriate model based on the input data.
What deployment strategy would best accommodate this requirement?

A. Multi-model serving with dynamic routing
B. Blue-Green deployment
C. A/B testing deployment
D. Canary deployment

答案：A

問題 #57
You are using IBM watsonx's generative AI model to generate responses for a chatbot, and you want to ensure that the model stops generating text when it encounters a specific phrase like ":End of Response." Which of the following settings for stop sequences is most appropriate to achieve this goal?

A. Set the stop sequence to "End of Response"
B. Set the stop sequence to "STOP"
C. Set the stop sequence to " n n"
D. Set the stop sequence to "<|stop|>"

答案：A

問題 #58
You have just finished a prompt tuning experiment for a large language model (LLM) to optimize its output for generating customer support summaries. The tuning results show that while the accuracy of the generated summaries is high (95%), the response time for generating them has significantly increased. The experiment data suggests that increasing the maximum token length during tuning led to better quality summaries but with slower generation.
Which parameter should you adjust to improve the model's response time without sacrificing too much summary quality?

A. Change the decoding strategy from beam search to greedy decoding
B. Decrease the maximum token length
C. Increase the batch size
D. Decrease the number of epochs

答案：A

問題 #59
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C1000-185認證考試的學習資料

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