this post was submitted on 24 Jul 2024
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[–] [email protected] 23 points 3 months ago (2 children)

What’s the resources requirements for the 405B model? I did some digging but couldn’t find any documentation during my cursory search.

[–] [email protected] 40 points 3 months ago* (last edited 3 months ago) (8 children)

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.

[–] [email protected] 20 points 3 months ago

Typically you need about 1GB graphics RAM for each billion parameters (i.e. one byte per parameter). This is a 405B parameter model.

[–] [email protected] 13 points 3 months ago (2 children)

Or you could run it via cpu and ram at a much slower rate.

[–] [email protected] 11 points 3 months ago (2 children)

Yeah uh let me just put in my 512GB ram stick…

[–] [email protected] 7 points 3 months ago

Samsung do make them.

Goodluck finding 512gb of VRAM.

[–] [email protected] 1 points 3 months ago

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$

[–] [email protected] 2 points 3 months ago

Finally! My dumb dumb 1TB ram server (4x E5-4640 + 32x32GB DDR3 ECC) can shine.

[–] [email protected] 8 points 3 months ago* (last edited 3 months ago)

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

[–] [email protected] 4 points 3 months ago

When the 8 bit quants hit, you could probably lease a 128GB system on runpod.

[–] [email protected] 3 points 3 months ago

Can you run this in a distributed manner, like with kubernetes and lots of smaller machines?

[–] [email protected] 2 points 3 months ago

According to huggingface, you can run a 34B model using 22.4GBs of RAM max. That's a RTX 3090 Ti.

[–] [email protected] 1 points 3 months ago* (last edited 3 months ago)

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.

[–] [email protected] 1 points 3 months ago

Ypu mean my 4090 isn't good enough 🤣😂

[–] [email protected] 6 points 3 months ago

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.