New C1000-185 Test Answers - C1000-185 Exam Training

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q112-Q117):

NEW QUESTION # 112
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. A hard prompt explicitly specifies all constraints, while a soft prompt relies on implicit learning from continuous inputs during training.
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. Soft prompts are more readable and natural, whereas hard prompts consist of short, technical instructions.

Answer: B

NEW QUESTION # 113
In a system that generates product recommendations using a generative AI model, you are tasked with creating prompts that incorporate dynamic variables to ensure more relevant and personalized responses.
Prompt Template: "Recommend products for [customer_name] based on their interest in [product_category]." Which portion of the prompt is the best candidate to be replaced with variables to achieve greater personalization and flexibility? (Select two)

A. "[product_category]"
B. "[customer_name]"
C. "for"
D. "Recommend products"
E. "based on their interest"

Answer: A,B

NEW QUESTION # 114
While customizing an LLM in InstructLab to generate more human-like responses for a customer service chatbot, you notice that the responses are too formal and lack empathy.
Which of the following techniques will best address this problem and help tailor the model to generate more empathetic responses?

A. Adjust the model's max sequence length to encourage longer responses
B. Apply transfer learning with a dataset containing casual language
C. Use prompt engineering to guide the model towards empathetic responses
D. Change the decoder strategy from greedy decoding to beam search to increase response quality

Answer: C

NEW QUESTION # 115
How can developers best ensure that prompt templates are version-controlled and any changes to the templates can be tracked efficiently in a collaborative team environment?

A. Manually keep a changelog of prompt template modifications in a shared document
B. Use a centralized cloud storage system that automatically saves all versions of the prompt templates
C. Implement a versioning system for prompt templates in a source control tool like Git
D. Update prompt templates directly in production and rely on error logs for tracking changes

Answer: C

NEW QUESTION # 116
When tuning the generative model parameters, which of the following scenarios describes an appropriate use of the maximum tokens setting, and how will it influence the model's output?

A. Setting the maximum tokens to 0 will allow the model to generate an unlimited amount of text
B. Setting the maximum tokens to 500 will guarantee that the model always generates exactly 500 tokens
C. Setting the maximum tokens to 100 will prevent the model from generating coherent sentences, as it cuts off abruptly after 100 tokens
D. Setting the maximum tokens to 100 ensures that the model's output will not exceed 100 tokens, but it may stop earlier if the generation ends naturally

Answer: D

NEW QUESTION # 117
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New C1000-185 Test Answers - C1000-185 Exam Training

C1000-185 Exam Training & C1000-185 Test Fee

IBM watsonx Generative AI Engineer - Associate Sample Questions (Q112-Q117):

Free PDF 2025 IBM Professional New C1000-185 Test Answers

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