CCAO-F Claude Model Fundamentals Practice Question
Exhibit
{
"model": "claude-3-5-sonnet-20240620",
"max_tokens": 500,
"messages": [
{"role": "user", "content": "Explain AI."}
],
"stop_sequences": ["\n\nHuman:"]
}Refer to the exhibit. What is the specific purpose of the 'stop_sequences' parameter in this JSON payload?
⚠ Common exam trap
Candidates often confuse 'stop_sequences' with 'max_tokens', assuming the former is for limiting response length rather than defining specific exit points to prevent the model from continuing into unwanted conversational turns.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
It instructs the model to stop generating text when it encounters that sequence.
Stop sequences allow developers to force the model to cease generation when it hits a specific string. This is essential for controlling output length and preventing the model from hallucinating a continuing conversation (e.g., trying to generate the next 'Human:' turn). Mastering this parameter is key to integrating Claude into existing chat UI architectures where the developer needs precise control over when the model hands control back to the user.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It forces the model to ignore user inputs after that sequence.
Why it's wrong here
Stop sequences do not change the model's behavior or its ability to process input. They are purely structural triggers that signal the API to terminate the response generation. They act as a hard boundary for the output, ensuring the model does not generate unwanted text beyond the defined marker.
- ✓
It instructs the model to stop generating text when it encounters that sequence.
Why this is correct
The 'stop_sequences' parameter tells the model to halt generation as soon as it produces any of the provided strings. This is a common technique to prevent the model from entering a conversation loop or generating content beyond the intended response, ensuring the output is clean and ready for integration.
- ✗
It increases the probability of the model using that sequence.
Why it's wrong here
Stop sequences have the opposite effect; they terminate the generation immediately upon encountering the sequence. The model will not 'use' or include the sequence in the generated output as a stylistic choice. They are purely for output control and do not influence the probability of specific tokens occurring.
- ✗
It reduces the model's temperature to 0.
Why it's wrong here
Stop sequences and temperature are independent configuration settings. Temperature is defined in the top-level parameters and controls the randomness of token selection. Stop sequences are structural markers. Changing one does not affect the other, and stop sequences are not a mechanism for enforcing deterministic or low-temperature generation behavior.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Anthropic exam blueprint
This CCAO-F practice question is part of Courseiva's free Anthropic certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CCAO-F exam.