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systemMessage: 'The starting message that defines how model should behave.',
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temperature: 'Controls the randomness of the generated text by affecting the probability distribution of the output tokens. Higher = more random, lower = more focused.',
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dynatemp_range: 'The added value to the range of dynamic temperature, which adjusts probabilities by entropy of tokens.',
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dynatemp_exponent: 'Smoothes out the probability redistribution based on the most probable token.',
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top_k: 'Keeps only k top tokens.',
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top_p: 'Limits tokens to those that together have a cumulative probability of at least p',
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min_p: 'Limits tokens based on the minimum probability for a token to be considered, relative to the probability of the most likely token.',
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xtc_probability: 'The probability that the XTC sampler will cut token from the beginning.',
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xtc_threshold: 'If XTC is used, all top tokens with probabilities above this threshold will be cut.',
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typical_p: 'Sorts and limits tokens based on the difference between log-probability and entropy.',
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repeat_last_n: 'Last n tokens to consider for penalizing repetition',
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repeat_penalty: 'Controls the repetition of token sequences in the generated text',
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presence_penalty: 'Limits tokens based on whether they appear in the output or not.',
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frequency_penalty: 'Limits tokens based on how often they appear in the output.',
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dry_multiplier: 'Sets the DRY sampling multiplier.',
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dry_base: 'Sets the DRY sampling base value.',
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dry_allowed_length: 'Sets the allowed length for DRY sampling.',
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dry_penalty_last_n: 'Sets DRY penalty for the last n tokens.',
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max_tokens: 'The maximum number of token per output.',
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custom: '',// custom json-stringified object
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};
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// config keys having numeric value (i.e. temperature, top_k, top_p, etc)
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