We trained a personal voice DoRA on Qwen3-8B for $1.50 — beat stock model 100% in blind A/B
A developer successfully trained a personal voice adapter using DoRA on the Qwen3-8B model for just $1.50. The process involved using 6,128 personal Telegram messages to fine-tune the model, resulting in an adapter that outperformed the base Qwen3-8B model in blind A/B testing. This method also demonstrated no significant degradation in general knowledge tasks and produced a voice that was perceived as more representative of the individual than their own actual writing. AI
IMPACT Demonstrates a highly accessible and cost-effective method for personalizing LLM voice, potentially enabling widespread custom voice applications.