An AI model's output structure can be controlled by giving it specific patterns for different text lengths. Instead of just a word count, the AI model receives a structural template common to real texts of that length. This helps the AI model create text that naturally fits a certain size.
By Pawan Nayar · from the LLOS AI Learning record
An AI model's output structure can be controlled by giving it specific patterns for different text lengths.
Instead of just a word count, the AI model receives a structural template common to real texts of that length. This helps the AI model create text that naturally fits a certain size.
A developer can research common structural patterns for different text lengths. For example, a 3-word sentence often uses an imperative verb and an object. A 12-word sentence might use a setup and a reversal around a comma. The developer then gives the AI model these specific patterns for the desired text length. This guides the AI model to produce text with the correct structure and length.
A developer wants an AI model to create a 5-word aphorism. Instead of just asking for '5 words', the developer provides a pattern: 'terse declarative or subject-verb-adverbial closure'. The AI model then generates 'Time flies swiftly, never waits.' This sentence is 5 words and follows the given structural pattern.
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An AI model's output structure can be controlled by giving it specific patterns for different text lengths. Instead of just a word count, the AI model receives a structural template common to real texts of that length. This helps the AI model create text that naturally fits a certain size.