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What is the primary goal of prompt engineering with OpenAI GPT?
Which parameter controls the randomness of responses in the model?
What should you do if you encounter a token limit error?
Which part of a prompt typically contains specific instructions to generate a desired response?
How can you fine-tune your prompt engineering techniques over time?
Which of the following commands in Google Colab is used to mount your Google Drive for accessing and saving files?
What does the Python docx library allow you to do?
Which method in the docx library is used to add a paragraph to a Word document?
How can you set the font size of a paragraph in a Word document using the docx library?
Which of the following is true about Google Colab notebooks?
What is the purpose of a “run” in the context of the docx library?
In the docx library, what method can be used to insert an image into a Word document?
What is the purpose of a kernel in an IPython notebook?
What is the role of “temperature” in controlling the randomness of responses generated by OpenAI GPT?
Which parameter should you adjust to control the balance between specificity and creativity in the model’s responses?
How can you use the “System” message in a prompt to improve the clarity of instructions to the model?
What can happen if you set the “Maximum Length” parameter to a value smaller than the actual response length in prompt engineering?
When creating prompts for OpenAI GPT, why is it essential to carefully consider the wording and phrasing of instructions?
In the context of text generation with OpenAI models, which of the following statements is true regarding Top P, Frequency Penalty, and Stop Sequence?
In the context of AI language models, which term refers to the specific way the model operates and generates responses?