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bartowskiΒ 
posted an update 8 days ago
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4771
Looks like Q4_0_N_M file types are going away

Before you panic, there's a new "preferred" method which is online (I prefer the term on-the-fly) repacking, so if you download Q4_0 and your setup can benefit from repacking the weights into interleaved rows (what Q4_0_4_4 was doing), it will do that automatically and give you similar performance (minor losses I think due to using intrinsics instead of assembly, but intrinsics are more maintainable)

You can see the reference PR here:

https://github.com/ggerganov/llama.cpp/pull/10446

So if you update your llama.cpp past that point, you won't be able to run Q4_0_4_4 (unless they add backwards compatibility back), but Q4_0 should be the same speeds (though it may currently be bugged on some platforms)

As such, I'll stop making those newer model formats soon, probably end of this week unless something changes, but you should be safe to download and Q4_0 quants and use those !

Also IQ4_NL supports repacking though not in as many shapes yet, but should get a respectable speed up on ARM chips, PR for that can be found here: https://github.com/ggerganov/llama.cpp/pull/10541

Remember, these are not meant for Apple silicon since those use the GPU and don't benefit from the repacking of weights

Huh interesting, however all inference engines need to adapt newer llama.cpp version correct? Q4_0 and IQ4_NL? Just scrolled throught the pull request. How do you know IQ4_NL should work this way also?

Β·

oh right sorry, forgot to include that PR, i'll add it above but it's here:

https://github.com/ggerganov/llama.cpp/pull/10541

I think the inference engines will just need to update to the newer versions and they'll get the repacking logic for free, if that's what you meant then yes

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