• ranzispa@mander.xyz
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    2 hours ago

    Fair, I guess I’d also want some ram if I did not have access to a compute cluster.

    But to be fair, for what I do I don’t really think you can fit that much ram on a consumer motherboard.

    In machine learning I don’t generally find memory to be the bottleneck, as long as the GPU can handle it.

    But sure, opening huge files can be big trouble.

    • brucethemoose@lemmy.world
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      1 hour ago

      I can rent cloud stuff, but it’s just not worth it for casual/experimental use.

      Like keeping Deepseek V4 loaded and hitting it rarely, but I want it to be in my control… it’s just easier to do it locally.

      Or experiments I launch like 30 times before it works. I’d waste hours moving all my stuff to a cloud instance, configuring it, tinkering with the experiment to get it to launch; the thing would be idle the vast majority of the time. And yeah, I know I can containerize stuff, but some projects I can’t even test without a sizable memory pool.