Customizing ChatGPT training requires specific technical expertise and resources, which are typically available within OpenAI’s framework.
As an individual user, you may not be able to directly adjust the training process of ChatGPT, as the model is trained on a general dataset collected from the Internet. This training involves two steps: pre-training, which learns from a random dataset and fine-tuning, handled by human reviewers following guidelines provided by OpenAI.
However, OpenAI is working on an upgrade that will allow users to customize the behavior of ChatGPT, although specifics about what sort of customization will be possible have not been released yet.
Another way to train your AI models, like GPT-3, is through reinforcement learning from human feedback. You can gather comparison data by having humans rank different model responses by quality. This can be used to create a reward model and fine-tune your model.
For any further customization, you would need access to the underlying AI framework, which isn’t public for GPT-3 but is available for earlier models like GPT-2.
