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> Train your LLM at scale on our infrastructure Is it really their infrastructure or are they using a cloud provider and this wraps it up and provides convenie
by jstx1 3y ago
> Train your LLM at scale on our infrastructure
Is it really their infrastructure or are they using a cloud provider and this wraps it up and provides convenience for a price?
- perfmode 3y agoWhat’s the difference?
- melx 3y agoYou end up paying more in the latter instance.
- marcinzm 3y agoNot counting the cost of learning how to cluster together 500 GPUs, the cost of learning how to train models efficiently on 500 GPUs, the cost of convincing a cloud provider to let you get 500 GPUs, the cost of trying to find a cloud provider that actually has 500 GPUs you can book, etc, etc.
- jsemrau 3y agoI'd think "infrastructur" includes the nice front end and Python API that they have proven to be capable to pull off already.
- brucethemoose2 3y agoAzure and such get such massive scaling cost benefits from scaling that HF's own GPUs would probably be more expensive anyway, even if they go AMD/Intel. It does seem like they should run their own storage nodes, with the sheer quantity of models they host...
- fxtentacle 3y agoEveryone claims that, yet I have never seen it happen. Typically, small companies get rebates on NVIDIA GPUs, but big established ones do not. So I would expect a startup with 100 GPUs to pay less per GPU than Azure.