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.
Akshually, while training models requires (at the moment) massive parallelization and consequently stacks of A100s, inference can be distributed pretty well (see petals for example). A pirate 'ChatGPT' network of people sharing consumer graphics cards could probably indeed work if the data was sourced. It bears thinking about. It really does.
You definitely can train models locally, I am doing so myself on a 3080 and we wouldn't be as many seeing public ones online if that were the case! But in terms of speed you're definitely right, it's a slow process for us.
I was thinking more of training the base models, LLAMA(2), and more topically GPT4 etc. You're doing LoRA or augmenting with a local corpus of documents, no?
Ah yeah my mistake I'm always mixing up language and image based AI models. Training text based models is much less feasible locally lol.
There's no model for my art so I'm creating a checkpoint model using xformers to bypass the VRAM requirement and then from there I'll be able to speed up variants of my process using LORA's but that won't be for some time, I want a good model first.
Fair cop, Godspeed!