this post was submitted on 23 Jul 2024
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[–] 0laura@lemmy.world 8 points 3 months ago (2 children)

even better, what lora did you use.

[–] rickyrigatoni@lemm.ee 9 points 3 months ago (2 children)

Anti-AI people don't know enough about AI to know what a lora is.

[–] 0laura@lemmy.world 10 points 3 months ago (1 children)

true. it kinda sucks seeing people argue against ai when they don't understand it. like, there's many things to criticize about ai, I'm not saying they'd like ai if they knew more about it. I just wish their hatred was more educated.

[–] PeriodicallyPedantic@lemmy.ca 3 points 3 months ago

Idk, wrt Lora specifically. I agree in general it'd be good if haters of anything were more educated in that thing, but they probably don't need to be that educated, especially in niche topics.

I'd consider myself an AI hater.
My job is also building ai-assisted tools.
But also I don't need to understand how the AI works to understand it's use, beyond a bit of prompt engineering.

Don't ask about my job satisfaction 😭

[–] JackbyDev@programming.dev 2 points 3 months ago

That's why it's funnier

[–] desktop_user@lemmy.blahaj.zone 0 points 3 months ago (1 children)
[–] 0laura@lemmy.world 4 points 3 months ago

I'm talking about LoRA, not LoRa. I'm a fan of both though. I've been considering getting a Lilygo T-Echo to run Meshtastic for a while. Maybe build a solar powered RC plane and put a Meshtastic repeater in there, seems like a cool project.

https://en.wikipedia.org/wiki/Fine-tuning_(deep_learning) Low-rank adaptation (LoRA) is an adapter-based technique for efficiently fine-tuning models. The basic idea is to design a low-rank matrix that is then added to the original matrix.[13] An adapter, in this context, is a collection of low-rank matrices which, when added to a base model, produces a fine-tuned model. It allows for performance that approaches full-model fine-tuning with less space requirement. A language model with billions of parameters may be LoRA fine-tuned with only several millions of parameters.