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Definition of can dish it but can't take it

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[-] p03locke@lemmy.dbzer0.com 3 points 2 days ago

open-weights aren’t open-source.

This always has been a dumb argument, and really lacks any modicum of practicality. This is rejecting 95% of the need because it is not 100% to your liking.

As we've seen in the text-to-image/video world, you can train on top of base models just fine. Or create LoRAs for specialization. Or change them into various styles of quantized GGUFs.

Also, you don't need a Brazilian LLM because all of the LLMs are very multilingual.

Spending $3000 on training is still really cheap, but depending on the size of the model, you can still get away with training on 24GB or 32GB cards, which cost you the price of the card and energy. LoRAs take almost nothing to train. A university that is worth anything is going to have the resources to train a model like that. None of these arguments hold water.

[-] obbeel@mander.xyz 1 points 3 hours ago

Well, I think you must agree that it makes sense to do it for science. Beyond stock markets and things like that, there is social and scientific interest in developing LLMs, or people wouldn't do it. Ok, so let's take a market kind of thing and say Microsoft only does Phi-4 and Phi-4-mini because of stocks and stockholders. Even if that translates into money, at the hollow core of this is social and scientific interest. So I think it makes much sense to have a Brazilian LLM, thank you.

this post was submitted on 13 Feb 2026
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