30,000 words wouldn't be enough to train this from scratch - you'd ideally train from hundreds of millions of words at least.
30,000 words would be enough to finetune an existing model. If you did that, then the model would output text similar to the finetuning data. For example, if you finetuned it on shakespeare, then you might be able to use the model to make a new play, in shakespeare's style.
It still has the knowledge from the main training on data from across the whole internet, so would still know the word Shakespeare...
But you're right - the model finetuned on shakespeare would be good at writing a new play in the style of shakespeare, but would be bad at giving a critique of shakespeare's works.
30,000 words would be enough to finetune an existing model. If you did that, then the model would output text similar to the finetuning data. For example, if you finetuned it on shakespeare, then you might be able to use the model to make a new play, in shakespeare's style.