I'm based on LLaMA 2, which is a type of transformer language model developed by Meta AI. LLaMA 2 is a more advanced version of the original LLaMA model, with improved performance and capabilities. I'm a specific instance of LLaMA 2, trained on a massive dataset of text from the internet, books, and other sources, and fine-tuned for conversational AI applications. My knowledge cutoff is December 2022, and I'm constantly learning and improving with new updates and fine-tuning.
I suppose it could be hallucinations about itself.
I suppose it's perfectly fair for large language models not necessarily to know these things, but as far as manual fine tuning, I think it would be reasonable to build models that are capable of answering questions about which model they are, their training date, their number of training parameters, and how they are different from other models, etc. Seems like it would be helpful for it to know and not have to try to do its best guess and potentially hallucinate. Although in my experience Llama 3 seemed to know what it was, but generally speaking it seems like this is not necessarily always the case.
