What does it mean to limit tokens for fine tuning?

One has to make very clear a conflation that newcomers have made.

Fine-tune is a machine-learning technique on API for producing your own AI models, by refining the weights that are used in token production, and using a very large training file that has examples of how an AI should respond. A fine-tune model is only available within an API organization that created it.

GPTs and Assistants, instead are agents. They can operate more autonomously, making multiple calls to AI models, and have built-in features that supplement the AI model capabilities. ChatGPT GPTs only use the GPT-4 AI that is within ChatGPT Plus, and assistants can only use the newest AI models also introduced in November if one wants success. Fine-tune AI models are blocked from being used.

Training file example length refers to individual fine-tune conversations in full. It is the total length of one of the many chat examples that can be in a fine-tune training file to make the AI learn how to respond.

Token limits depend on the model you select. For gpt-3.5-turbo-1106, the maximum context length is 16,385 so each training example is also limited to 16,385 tokens. For gpt-3.5-turbo-0613, each training example is limited to 4,096 tokens.