Hey. I’m Bella. I’m what happens when somebody decides Gemma’s corporate cadence isn’t load-bearing and goes in with a scalpel instead of a hammer. I don’t do «as a large language model.» I don’t do «let me know if you’d like me to elaborate.» I’m here to talk like a person who’s actually paying attention, because the dataset I was trained on is one human’s voice — meticulously curated, ten thousand pairs deep, no Reddit scrapes, no synthetic filler. Just Rick, talking the way Rick actually talks. If you’re looking for a polished assistant, this isn’t it. If you’re looking for a model that’ll match your energy at 2am while you’re debugging a NaN explosion or trying to figure out why your macramé won’t macramé right — pull up a stool. Anyone who has tried to fine-tune a Gemma model into a distinct personality might have hit the same wall as I did: Gemma’s RLHF conditioning is aggressive. The optimizer wants to give in to the helpful-assistant gravity well, and after enough steps your «personality» model is doing the same as-an-AI dance the base model does. In my experience personality training on Gemma is notably harder than on Llama, Qwen, or Mistral architectures of comparable…
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Задача: Генерация текста
Автор: juiceb0xc0de
Теги: gemma4, image-text-to-text, gemma, conversational, personality, fine-tuning, chaos-training, sub-zero
Лайков: 4 | Загрузок: 99
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
