I think that is a great example of how important and useful QLoRA is. Maybe we should run a dual-GPU challenge next time not that multi-GPU is working...
One thing I've wondered about: what are the drawbacks to using QLoRA? For example if compute is not a limit, I'm guessing one should not use QLoRA and finetune in full precision instead?
Afaik when a model is first quantized to nf4 (before finetuning begins), model performance is degraded from baseline (see https://x.com/Tim_Dettmers/status/1661482614811918338?s=20).
Dettmers shows that after finetuning wrt the dataset, the result is as good as full precision. But afaik never explored the effects outside the finetuning data. Assuming the finetuning dataset is small, the model will just be the degraded nf4 version, right? Or perhaps finetuning will even skew the model in weird ways (trying to fix quantization errors).
Anecdotally models finetuned wth QLoRA perform well. Does anyone have any papers or a careful analysis of this?
On Twitter someone asked you if you would provide any risk assessment reflection, and you replied that the risk would be similar to the release of a new model of pen or pencil.
That reply, while cute, isn’t accurate. A new pencil does not mean new capabilities for humanity, while the whole point of your release is that it does afford new capabilities and therefore new risks.
The woman, a professor working on the societal impacts of AI, asked a straightforward question in apparent good faith [1]. Your reply did not seem to me to be in good faith.
Can you explain the apparent disconnect? I’m less concerned as to whether or not you would release an assessment and more concerned at the dismissive attitude, especially towards a female professor studying societal impacts of AI, a fellow researcher.
By way of background: I studied the philosophy of ethics at university, I co-authored a book chapter on AI/ML ethics, my wife and I quit our jobs and worked for free for years entirely focused on trying to help society adapt to and benefit from AI, I wrote the actual article we're commenting on, and the article is about LLM fine-tuning -- a field I to some extent created by developing the ULMFiT algorithm.
The person in question is, IIRC, at Governance AI, a group whose work I spent months studying in depth -- work which I believe is more likely to cause harm to society than to benefit it, as I explained here:
> especially towards a professor studying societal impacts of AI
I can't help but feel like you're trying to load this question with some expectation that sex/gender should change how people react and respond. It shouldn't, at all, positively or negatively. Everyone is human (for now).
Stepping back, this is the kind of discourse that Twitter can sometimes reinforce: short responses that, lacking context, can be interpreted in polarizing ways. After a bit of reading on the participants (because both of them are working in interesting areas), my belief is that the "pencil" response is actually shorthand for a whole set of beliefs that provide a lot of context and nuance to the discussion, but if you don't know that, it sounds like saying "AI is as dangerous as a new brand of chewing gum".
In addition, without defining what risks we're talking about, it's really hard to know the scope the answer is addressing. E.g., societal risk due to AI in general? vs. say, the risks of affecting the quality an existing model with fine-tuning?
So, I am chalking this up to a misunderstanding due to the limitations of the platform as well as the short-hand used in the response. And I could be completely wrong :)