Having spent quite a bit of time playing around with llama.cpp, alpaca.cpp, loras, and the many other llama-based weights lately, here is my impression:

The biggest deal with this isn't the published lora adapter (which seems limited to llama 7b), but the cleaned training data, which is likely better than the previous data sets used to train the alpaca-inspired loras that have been publicly released so far. [0]

If you're really limited to running "just" llama 7b, this is great for you. But the biggest value will be when people inevitably release lora adapters for the 13b, 30b, and 65b, based on this training data (assuming it really is better than the previously released adapters).

[0] admittedly, this is based off anecdotes and github issues, and not real measurements. but smarter people than I have claimed the currently most popular loras were trained on messy data, and have started an effort to clean that data and retrain. So if the training data in this repo is high quality like the authors claim, it will benefit models of all sizes.

This sentence defies lay people:

The biggest deal with this isn't the published lora adapter (which seems limited to llama 7b), but the cleaned training data, which is likely better than the previous data sets used to train the alpaca-inspired loras that have been publicly released so far.

I have casually followed countless different news cycles on various complicated tech topics over my decades long career. I can't recall a single one that has consistently made me feel like an idiot more than how people talk about this recent AI wave. There just seems to be so much more jargon involved in this subject that makes casual perusing of the latest developments impenetrable.

its ok you are not alone, most of us feel the same way on theiri buzwords

That's not what's happening in the parent comment. They're talking about projects like

https://github.com/ZrrSkywalker/LLaMA-Adapter

https://github.com/microsoft/LoRA

https://github.com/tloen/alpaca-lora

and specifically the paper: https://arxiv.org/pdf/2106.09685.pdf

Lora is just a way to re-train a network for less effort. Before we had to fiddle with all the weights, but with Lora we're only touching 1 in every 10,000 weights.

The parent comment says GPT4all doesn't give us a way to train the full size Llama model using the new lora technique. We'll have to build that ourselves. But it does give us a very huge and very clean dataset to work with, which will aid us in the quest to create an open source chatGPT killer.