Prompt Poet shines for its seamless integration of “few-shot learning,” a powerful technique for rapid customization of LLMs without requiring complex and expensive model fine-tuning.

It compared few-shot learning, which involves fine-tuning the models with a limited number of samples, to full fine-tuning using the entire dataset.

Upload datasets to the fine-tuning dashboard and select either GPT-4o or GPT-4o Mini as the base model. Monitor training progress and metrics to ensure effective learning and make necessary ...

The disadvantage of few-shot learning is that it doesn’t work as well as fine-tuning, and that data scientists and machine learning engineers have less control over the model because they are ...