Parameter used in generative AI models, particularly in large language models (LLMs), to control the repetition of words or phrases in the generated text. It discourages the model from using the same words or phrases multiple times, promoting diversity and novelty in the output.
The Presence Penalty is a mechanism that adjusts the likelihood of the model selecting a word or token that has already been used. When a word is repeated, the presence penalty immediately lowers its score, making it less likely for the model to choose that word again, even if it has only been used once.
This parameter ranges from -2.0 to 2.0, with positive values increasing the likelihood of discussing new topics by penalizing tokens that have already been used. A higher presence penalty encourages the model to generate more diverse and creative output, while a lower penalty allows for more repetition.
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