Comment by mips_avatar
8 days ago
From the model card: "the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning" aka they will take your ML research code and inject bugs into it until it breaks using a LORA (or some other form of PEFT)
Are they trying to fight back against model distillation?
“Limit effectiveness” could mean introducing performance degradation in your code. Which is arguably some sort of performance bug (I mean, ML codes are supposed to be high performance so I’d call unnecessary degradation a bug), but it could be borderline.
No, it is just a prominent "Cyber Security threat detected" blocker, with a button to appeal. I appealed because my work had nothing to do with neither cyber nor security, but the appeal was auto-closed. So no more Claude for this work.
Thanks, I thought maybe I missed something. That's an interesting way to interpret that.
Anthropic is trying to hide bad behavior by being vague, it's important to not be vague when calling it out.
I'm of the opinion that removing guardrails is how you force regulation. What's your opinion on the balance?
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PEFT is a library, one of its capabilities is to produce LoRAs.
See:
https://heidloff.net/article/efficient-fine-tuning-lora/
It's just an acronym, "parameter-efficient fine tuning". LoRA is one method, prefix tuning is another, there are more.