When using GPT, here are some experiences and best practices:
Make sure your input data is in the correct format so that GPT can understand and generate the output correctly.
Training a model requires a lot of computing resources and time, so you need a powerful computer to handle the task.
Adjusting a model's parameters can affect the output generated, so experimentation and tuning are required to find the best combination of parameters.
For some specific tasks, you may need to fine-tune GPT to ensure that the generated output meets specific requirements.
Finally, check the generated output to ensure its accuracy and readability.