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A marketing LLM is producing bland, predictable content. The team wants more creative variations. What should they adjust?
A
Reduce temperature to 0.2
B
Increase top-p to 0.95 and temperature to 0.9
Explanation:
Correct Answer: B (Increase top-p to 0.95 and temperature to 0.9)
Temperature Parameter:
Temperature controls the randomness/creativity of the model's output
Lower temperature (like 0.2) makes the model more deterministic and predictable
Higher temperature (like 0.9) introduces more randomness and creativity
For marketing content that needs to be more creative and varied, increasing temperature is appropriate
Top-p (Nucleus Sampling) Parameter:
Top-p sampling controls the diversity of word selection
A higher top-p value (like 0.95) allows the model to consider a wider range of possible next tokens
This leads to more diverse and creative outputs
Combined Effect:
Increasing both temperature and top-p together creates the most creative and varied outputs
Temperature adds randomness to the probability distribution
Top-p ensures diversity in token selection from that distribution
Reducing temperature to 0.2 would make the model even more deterministic and predictable
This would exacerbate the problem of bland, predictable content
Lower temperature values cause the model to consistently choose the most probable next token
Temperature: Controls randomness (0 = deterministic, 1 = creative)
Top-p: Controls diversity of token selection (0.0-1.0, higher = more diverse)
For creative marketing content, you typically want higher values for both parameters
The specific values in Option B (top-p=0.95, temperature=0.9) are well-suited for generating creative variations
This adjustment would help the marketing team get more diverse, creative content rather than repetitive, predictable outputs.