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C_AIG_2412 · Question #67
C_AIG_2412 Question #67: Real Exam Question with Answer & Explanation
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Question
You want to assign urgency and sentiment categories to a large number of customer emails. You want to get a valid json string output for creating custom applications. You decide to develop a prompt for the same using generative Al hub. What is the main purpose of the following code in this context? prompt_test = """Your task is to extract and categorize messages. Here are some examples: {{?technique_examples}} Use the examples when extract and categorize the following message: {{?input}} Extract and return a json with the following keys and values: - "urgency" as one of {{?urgency}} - "sentiment" as one of {{?sentiment}} "categories" list of the best matching support category tags from: {{?categories}} Your complete message should be a valid json string that can be read directly and only contains the keys mentioned int import random random.seed(42) k = 3 examples random. sample (dev_set, k) example_template = """<example> {example_input} examples '\n---\n'.join([example_template.format(example_input=example ["message"], example_output=json.dumps (example[ f_test = partial (send_request, prompt=prompt_test, technique_examples examples, **option_lists) response = f_test(input=mail["message"])
Options
- AGenerate random examples for language model training
- BEvaluate the performance of a language model using few-shot learning
- CTrain a language model from scratch
- DPreprocess a dataset for machine learning
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