Monadize Fine-Tunes Gemma 4 31B for More Diverse Names
Developer u/zoraruha fine-tuned Gemma 4 31B to create Monadize, aiming to reduce repetitive names by shifting next-token probability distributions and using single-character tokenization for new names. In a developer-run test at temperature 1, the base model generated repeated names, while Monadize produced 60 unique names across 30 character-name and 30 city-name generations. The developer describes Monadize as experimental, warns that unexpected behavior may occur and recommends keeping thinking disabled because it was fine-tuned that way.
The release presents a specific fine-tuning method for reducing repetitive name generation, supported by the developer’s comparison showing a wider spread of starting letters and unique names in a small test.