AI Dev Skills
Adapting pre-trained models to specific domains, tasks, or behaviors using your own data. Fine-tuning can dramatically outperform prompt engineering on specialized tasks.
Generic models underperform on domain-specific tasks by 15-40% in most enterprise use cases. Fine-tuning on 1,000 domain examples often beats the best prompts on the largest models.
Unsloth made fine-tuning accessible — 2x speed, 70% less memory. LoRA/QLoRA is the standard efficient method. GRPO (from DeepSeek) has replaced PPO as the preferred RL method.
4+ fine-tuning repos indicates a team that has moved beyond off-the-shelf models. They are customizing behavior, reducing hallucination on domain tasks, and building proprietary model capabilities.
No repos in this skill area yet.