AWS Certified AI Practitioner AIF-C01 Practice Question
A development team must choose a foundation model to summarize lengthy legal contracts that can be over 8,000 tokens long. Which model-selection criterion most directly ensures the model can accept the entire contract in one prompt?
The maximum context window-often expressed as supported input/output length-sets the upper limit on how many tokens the model can receive and generate in a single inference. Verifying that the model's supported input/output length meets or exceeds 8,000 tokens guarantees the whole contract can be provided at once. Multilingual capability, licensing cost, and overall parameter count do not determine how many tokens the model can handle in a single prompt.
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What is a context window in AI models?
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Why is supported input/output length important for text summarization?
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How do tokenization and token limits affect AI model performance?
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What is a token in the context of foundation models?
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What is the context window of a model and why is it important?
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How do you verify if a model supports an input length exceeding 8,000 tokens?
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AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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