Typically you need about 1GB graphics RAM for each billion parameters (i.e. one byte per parameter). This is a 405B parameter model. Ouch.
Edit: you can try quantizing it. This reduces the amount of memory required per parameter to 4 bits, 2 bits or even 1 bit. As you reduce the size, the performance of the model can suffer. So in the extreme case you might be able to run this in under 64GB of graphics RAM.
https://www.ebay.com/p/116332559 lga2011 motherboards quite cheap, insert 2 xeon 2696v4 44 threads each totalling at 88 threads and 8 ddr4 32gb sticks, it comes quite cheap actually, you can also install Nvidia p40 with 24gb each, you can max out this build for ai for under 2000$
So does OSM data. Everyone can download the whole earth but to serve it and provide routing/path planning at scale takes a whole other skill and resources. It’s a good thing that they are willing to open source their model in the first place.
Technically correct ™
Before you get your hopes up: Anyone can download it, but very few will be able to actually run it.
What’s the resources requirements for the 405B model? I did some digging but couldn’t find any documentation during my cursory search.
Typically you need about 1GB graphics RAM for each billion parameters (i.e. one byte per parameter). This is a 405B parameter model. Ouch.
Edit: you can try quantizing it. This reduces the amount of memory required per parameter to 4 bits, 2 bits or even 1 bit. As you reduce the size, the performance of the model can suffer. So in the extreme case you might be able to run this in under 64GB of graphics RAM.
Or you could run it via cpu and ram at a much slower rate.
Yeah uh let me just put in my 512GB ram stick…
Samsung do make them.
Goodluck finding 512gb of VRAM.
https://www.ebay.com/p/116332559 lga2011 motherboards quite cheap, insert 2 xeon 2696v4 44 threads each totalling at 88 threads and 8 ddr4 32gb sticks, it comes quite cheap actually, you can also install Nvidia p40 with 24gb each, you can max out this build for ai for under 2000$
Finally! My dumb dumb 1TB ram server (4x E5-4640 + 32x32GB DDR3 ECC) can shine.
At work we habe a small cluster totalling around 4TB of RAM
It has 4 cooling units, a m3 of PSUs and it must take something like 30 m2 of space
When the 8 bit quants hit, you could probably lease a 128GB system on runpod.
According to huggingface, you can run a 34B model using 22.4GBs of RAM max. That’s a RTX 3090 Ti.
Hmm, I probably have that much distributed across my network… maybe I should look into some way of distributing it across multiple gpu.
Frak, just counted and I only have 270gb installed. Approx 40gb more if I install some of the deprecated cards in any spare pcie slots i can find.
Ypu mean my 4090 isn’t good enough 🤣😂
As a general rule of thumb, you need about 1 GB per 1B parameters, so you’re looking at about 405 GB for the full size of the model.
Quantization can compress it down to 1/2 or 1/4 that, but “makes it stupider” as a result.
This would probably run on a a6000 right?
Edit: nope I think I’m off by an order of magnitude
“an order of magnitude” still feels like an understatement LOL
My 35b models come out at like Morse code speed on my 7800XT, but at least it does work?
When the RTX 9090 Ti comes, anyone who can afford it will be able to run it.
That doesn’t sound like much of a change from the situation right now.
So does OSM data. Everyone can download the whole earth but to serve it and provide routing/path planning at scale takes a whole other skill and resources. It’s a good thing that they are willing to open source their model in the first place.