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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q125-Q130):

NEW QUESTION # 125
While working on generating a concise response to a user prompt, you notice that the generative AI model in IBM watsonx is producing excessively long outputs. You want to ensure that the response is informative but doesn't exceed a specific length.
Which of the following parameters should you adjust, and what is the most appropriate value to achieve a concise output without cutting off essential information?

A. Set max_tokens to 10
B. Set max_tokens to 1000
C. Set max_tokens to 5
D. Set max_tokens to 100

Answer: D

NEW QUESTION # 126
You are fine-tuning the output behavior of a generative AI model in IBM Watsonx for creative content generation. You decide to adjust the temperature parameter to influence the randomness of the model's output.
Which of the following best describes the effect of increasing the temperature value?

A. A higher temperature setting reduces the length of the generated output by limiting the number of tokens in each response.
B. Raising the temperature makes the model more likely to repeat tokens, reducing variability in its responses.
C. Raising the temperature encourages the model to consider less likely tokens, leading to more diverse and creative outputs.
D. Increasing the temperature makes the model generate more deterministic responses by always selecting the most probable token at each step.

Answer: C

NEW QUESTION # 127
You are designing a generative AI model to generate customer support responses. During testing, you notice that the model frequently outputs gendered language when referring to certain professions, reinforcing stereotypes.
Which of the following strategies would most effectively reduce bias in the model' responses?

A. Increase the diversity of the dataset used to train the model, ensuring that all professions are equally represented.
B. Train the model with a lower learning rate to make it less sensitive to biased patterns in the data.
C. Apply a post-processing filter that removes any gendered language after the model generates the response.
D. Reduce the maximum token limit so that the model generates shorter responses, minimizing the chance for bias.

Answer: A

NEW QUESTION # 128
In the context of the decoding process for generative AI models in IBM Watsonx, what is the main characteristic of greedy decoding?

A. Greedy decoding generates multiple possible sequences and selects the most grammatically correct one based on predefined rules.
B. Greedy decoding alternates between high and low probability tokens, ensuring a balance between creativity and correctness.
C. Greedy decoding selects the highest probability token at each step, leading to deterministic and often coherent outputs.
D. Greedy decoding always selects the token with the lowest probability to encourage diversity in the generated response.

Answer: C

NEW QUESTION # 129
Which of the following best describes the process of large-scale iterative alignment tuning in the context of customizing LLMs with InstructLab?

A. A single training run of the model on a dataset to generate better predictions for a fixed number of prompts
B. Repeated fine-tuning of a model using reinforcement learning, focusing on aligning its outputs with human preferences across a diverse set of tasks
C. Direct training of the model on an expanded version of the dataset, without adjusting prompts or training tasks
D. Fine-tuning the model exclusively on binary classification tasks to improve its generalization on all other tasks

Answer: B

NEW QUESTION # 130
......

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