Answer: Enable repetition penalty with frequency = 1.5

## Explanation **Correct Answer: B - Enable repetition penalty with frequency = 1.5** **Why this is correct:** - **Repetition penalty** is specifically designed to reduce repetitive phrasing in LLM outputs - Setting frequency = 1.5 applies a penalty to tokens that have already appeared, making them less likely to be repeated - This directly addresses the problem of "repeating phrases too frequently" while maintaining the overall tone and creativity **Why other options are incorrect:** **A. Reduce temperature to 0.1** - Lowering temperature makes outputs more deterministic and less creative, which could actually increase repetition as the model becomes more predictable. This doesn't specifically target repetition reduction. **C. Lower top-k to 20** - Reducing top-k limits the vocabulary diversity by only considering the top 20 most likely tokens. While this might reduce some randomness, it doesn't specifically address repetition and could limit creativity. **D. Disable top-p entirely** - Top-p (nucleus sampling) helps with diverse outputs by sampling from tokens whose cumulative probability exceeds p. Disabling it would make outputs more deterministic and could actually increase repetition. **Key Concepts:** - **Repetition penalty**: A parameter that penalizes tokens that have already appeared in the generated text - **Frequency penalty**: A specific type of repetition penalty that penalizes tokens based on how frequently they've appeared - **Creativity vs. Repetition**: The challenge is to reduce repetition while maintaining creative tone - repetition penalty specifically targets this balance

Author: Ritesh Yadav