Did you run the fine-tuning on LLaMA yourselves based on the 52k examples from Alpaca? Or is there a 7B pre-trained alpaca model out there that you grabbed?
We also fine-tuned and OSS'd a 30b version here that you can checkout (on the cleaned 52k Alpaca dataset) https://huggingface.co/baseten/alpaca-30b
I've been running alpaca.cpp 13b locally and your 7b model performs much better than it does. I had assumed this was because alpaca.cpp was converting weights to 4bits from float16, but is there some other fine tuning you're doing that might also account for the better performance of chatLLaMA over alpaca.cpp?