i'm curious what HF does, because iiuc they're mostly just hosting model files? i know that they have some compute offers, and also created/maintain a few libraries, but it's not particularly widely used, i'm really not sure how they're supposed to earn money...
I've been asking myself that for a while. Would they be so popular if they didn't host & serve petabytes of model files for free? How will they monetize that aspect to match this valuation?
Whilst the scale of their model hosting is impressive, the functionality seems pretty basic. The models are just BLOBs in git LFS repos, you're usually relying on knowing which users to follow, then learning the way they name their models and how that naming convention applies to the particular framework and hardware you're using.
As an example the user "TheBloke" is prolific at publishing LLM models for various hardware / framework combos, but look how little the HF interface actually helps navigate or find what you're after: https://huggingface.co/TheBloke
Also, is anybody using HF Hub in "production"? We've deployed a few LLMs now and once we've decided on a model the first thing we do is get it off HF and into our own storage ready for deployment. There seems no reason to tightly integrate HF Hub with production systems given it's a just a bunch of files you can copy and keep.
> I've been asking myself that for a while. Would they be so popular if they didn't host & serve petabytes of model files for free? How will they monetize that aspect to match this valuation?
From what I gather it's mainly hosting with some maintaining of a few libraries, but then I recently starting to see they are offering lots of classes via DeepLearning platform; these lat couple of months as an AI student I've been asked to enroll into classes (temporarily for free) to assess where they are, here is the most recent example [0].
To what end, I'm not entirely sure, but I guess it's to get an overall pulse on what can be monetized and take it from there? I really think that this a low number compraed to where we were in the last few years, but ti also shows how little investment actually exists in the AI and ML space: consider that Git got bought by M$ for 7.5B and then tried cash in on it by releasing Co-Pilot and then got into legal issues as a result and then tried it's hand with Open AI and $10B.
This is starting to seem like a reversion to the mean, and AI's promise was always to lower the cost to everything it can, but I think one of the harder pills to swallow is that the traditional VC model is not really being supported after all the hype and losses.
Personally speaking, I'm thinking of moving on to Cyber Security after my finals this semester; I come from Bitcoin and the hype cycles there are something I was looking to get away from after nearly 13 years in that side of fintech.
Some of the models in TheBloke's repo are optimised for things like ggml, which runs well on Mac chips. Not sure if that's what you mean?
Have been experimenting with deploying to Mac's for inference as they are cheaper and use less power. But also still deploy to a substantial amount of gpus too.
Either way I try to take connections to huggingface hub out of the equation at deployment time.
Thanks for responding. I was curious if there are any alternative to OpenAI in terms of pricing. Deployment of a capable model starts at around $80/mo and I am not sure how many requests it can handle then. Either way it is a lot higher than GPT-3.5.
Those are pretty lackluster in my experience. Do they even support GPUs? And in any case, it seems like they go down for anything sufficiently popular.
