this post was submitted on 28 Aug 2023
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Piracy: ꜱᴀɪʟ ᴛʜᴇ ʜɪɢʜ ꜱᴇᴀꜱ
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Okay, I'm with you but...
how are we using these closed source models?
As of right now I can go to civitai and get hundreds of models created by users to be used with Stable Diffusion. Are we assuming that these closed source models are even able to be run on localized hardware? In my experience, once you reach a certain size there's nothing that layusers can do on our hardware, and the corpos aren't using AI running on a 3080, or even a set of 4090's or whatever. They're using stacks of A100's with more VRAM than everyone's GPU in this thread.
If we're talking the whole of LLM's to include visual and textual based AI... Frankly, while I entirely support and agree with your premise, I can't quite see how anyone can feasibly utilize these (models). For the moment anything that's too heavy to run locally is pushed off to something like Collab or Jupiter and it'd need to be built with the model in mind (from my limited Collab understanding - I only run locally so I am likely wrong here).
Whether we'll even want these models is a whole different story too. We know that more data = more results but we also know that too much data fuzzes specifics. If the model is, say, the entirety of the Internet while it may sound good in theory in practice getting usable results will be hell. You want a model with specifics - all dogs and everything dogs, all cats, all kitchen and cookware, etc.
It's easier to split the data this way for the end user as this way we can direct the AI to put together an image of a German Shepard wearing a chefs had cooking in the kitchen, with the subject using the dog-Model and the background using the kitchen-Model.
So while we may even be able to grab these models from corpos, without the hardware and without any parsing, it's entirely possible that this data will be useless to us.
The point about GPU's is pretty dumb, you can rent a stack of A100 pretty cheaply for a few hours. I have done it a few times now, on runpod it's 0.79 USD per HR per A100.
On the other hand the freely available models are really great and there hasn't been a need for the closed source ones for me personally.
0.79 dollars per hour is still $568 a month if you’re running it 24/7 as a service.
Which open source models have you used? I’ve heard that open source image generation with stable diffusion is on par with closed source models, but it’s different with large language models because of the sheer size and type of data they need to train it.
I have used it mainly for dreambooth, textual inversion and hypernetworks, just using it for stable diffusion. For models i have used the base stable diffusion models, waifu diffusion, dreamshaper, Anything v3 and a few others.
The 0.79 USD is charged only for the time you use it, if you turn off the container you are charged for storage only. So, it is not run 24/7, only when you use it. Also, have you seen the price of those GPUs? That 568$/month is a bargain if the GPU won't be in continuous use for a period of years.
Another important distinction is that LLMs are a whole different beast, running them even when renting isn't justifiable unless you have a large number of paying users. For the really good versions of LLM with large number of parameters you need a lot of things than just a good GPU, you need at least 10 of the NVIDIA A100 80GB (Meta's needs 16 https://blog.apnic.net/2023/08/10/large-language-models-the-hardware-connection/) running for the model to work. This is where the price to pirate and run yourself cannot be justified. It would be cheaper to pay for a closed LLM than to run a pirated instance.