If I am reading this correctly, priming would refer to the act of passing a sequence into the model expecting that the model’s meta learning capability would affect its output?

You’ve nailed it on the head. When talking about a left-to-right model like GPT-N, priming is just prepending text that is similar in some way to the text you are predicting which often helps the model to predict it correctly.
Incidentally, this is the thing that GPT-3 seems to be especially good at. There seems to be something about language models that we don’t completely understand that can make priming a surprisingly effective meta-learning technique, especially when the models get really big. See this Twitter thread 54 for some examples.
And yes, this kind of question is perfect for the forums. However, I’d say Research is probably a better category fit since this more about general NLP/research talk and rather than the HF libraries