AWS Certified AI Practitioner Practice Mode

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A2

  if yo want to tune the output or the quality of the output , then you should touch the hyperparameters such as Top K( for randomness ), Top P, Max Tokens etc But when you want to tune or modify the response format , then we should touch the prompt only , such as output formatting in the llm prompt , mentioning the specific language Hope this helps

• Chose A1

  A) Adjust the prompt. is correct – You can directly instruct the model in the prompt to produce concise responses in the desired language, ensuring output meets the company’s requirements. B) Choose an LLM of a different size. not correct – Changing the model size may impact performance or understanding, but it won’t guarantee the output is shorter or in a specific language. C) Increase the temperature. not correct – Temperature affects randomness and creativity in responses, not the length or format. D) Increase the Top K value. not correct – The model can choose from more options, which makes output more varied and creative, but it doesn’t control the length of the answer or the language

• Chose A1

  A: adjust the prompt is a powerful way to ensure the llm mmets the company's needs the concise and language speciific outputs.