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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q214-Q219):

NEW QUESTION # 214
You are designing a prompt to converse with a model for multilingual translation.
How would you frame the prompt to translate an English business email to Japanese, ensuring that the translated email is formal and appropriate for a business setting in Japan?

A. "Translate this business email into Japanese, making sure the tone is formal and culturally appropriate for a business context."
B. "Translate this business email into Japanese but do not consider the tone or formalities."
C. "Translate the following business email into Japanese, focusing on word-for-word accuracy."
D. "Translate this business email into Japanese using informal language."

Answer: A

NEW QUESTION # 215
IBM Watsonx Tuning Studio provides metering options to help monitor and optimize fine-tuning processes.
Which of the following best describes how these metering options can optimize resource usage during fine-tuning?

A. Fine-tuning metering enables hyperparameter search, automatically testing multiple configurations to find the most optimal one for the current task.
B. Fine-tuning metering provides insights into token usage and computational costs, allowing users to set budget constraints and minimize expenses during the tuning process.
C. Fine-tuning metering options automatically halt the training process if no significant improvements in model accuracy are observed, reducing unnecessary resource usage.
D. Fine-tuning metering adjusts the learning rate dynamically to optimize both training speed and accuracy.

Answer: B

NEW QUESTION # 216
You are fine-tuning a generative model to generate text-based responses in a customer service chatbot. You want to ensure the responses are concise and relevant, without causing the model to produce overly long or irrelevant output.
Which of the following parameters and stopping criteria would be most effective for achieving this goal?

A. Set a low top-k value and implement a repetition penalty with a low maximum token limit.
B. Use greedy decoding with no repetition penalty and a high stopping probability threshold.
C. Increase the temperature to 1.5 and set a high maximum token limit.
D. Use beam search decoding with a low beam width and a high repetition penalty.

Answer: A

NEW QUESTION # 217
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 "STOP"
B. Set the stop sequence to "End of Response"
C. Set the stop sequence to "<|stop|>"
D. Set the stop sequence to " n n"

Answer: B

NEW QUESTION # 218
You are tasked with improving the performance of a generative AI model used for customer service automation. The model needs to respond quickly and with high accuracy, particularly for complex queries. You have access to Tuning Studio as part of your optimization toolkit.
Which of the following is a primary benefit of using Tuning Studio to optimize the model in this scenario?

A. It provides automated fine-tuning of the model's hyperparameters to improve performance on domain-specific tasks.
B. It allows you to manually edit the output tokens to ensure correctness.
C. It automates the process of cleaning and preprocessing the input data before model training.
D. It enables the creation of new datasets by generating synthetic data based on prompts.

Answer: A

NEW QUESTION # 219
......

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