NER Named Entity Recognition using LLMs Like tranF5 or LLAMA2

Question

I am trying to do NER (Named entity recognition) using Large language models like Trans-F5 or LLAMA2. Till now, I found the ways of using prompt engineering. Which means we need to specify what to find in the text.
Can we fine tune and use these LLMs using the old NER techniques, like providing the label for entity and then doing inference phase to find the entity value.
Any code reference would be really helpful.