Would the following requirement be suitable for fine-tuning OpenAI's model?

The entire requirement includes:

  1. Contain the part name, brand name, and part category. (The part name and brand name determine the part category.)
  2. There are 520 fixed part categories, and I can provide 10 high-quality data for each category. In the future, after the business inputs the part name, the model will recommend a category.

In the fine-tuning docs on classification, you can see the full requirements, including that you should “aim for at least ~100 examples per class.”

You could fine-tune a model with 10 datapoints for each category, but it may not be very accurate.

Thank you for your response.
As you said, having more samples is essential for achieving more accurate results.
As a supply chain business professional, if I have enough sample data, it means that I have completed a specific business scenario. Currently, it is not very clear which specific business scenarios OpenAI can implement, especially for large enterprises.