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I feel like Phi-2 is all about the context of the fact that it is a <3b parameter model. It is incredible in that context, it isn't incredible in others.

it's definitely what it's about. it's insanely strong for its size

Phi-2 basically demonstrated that you don't need a very large model to figure out language. It not very smart but speaks perfect English. it's not obvious the best way to gain IQ is to have a larger language model. some other structure might be needed.

But isn't that something that even smaller GPT-2 models demonstrated already?

No, and this is covered in the various Phi papers, as well as TinyStories [0]:

> Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can rarely generate coherent and consistent English text beyond a few words even after extensive training.

[0] https://arxiv.org/abs/2305.07759

Did you try Dolphin Phi-2? The Dolphin fine-tune seems better to me in this case.

It’s a model for low rM usage 4gigs? I heard it would work well for RAG to speak to your docs, instead of relying purely on its parameters to answer.

maybe it's useful for fine-tuning jobs, not for free prompting

I have had a similar bad experience with it trying to prompt it