LocalLLaMA

2775 readers

34 users here now

Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.

Get support from the community! Ask questions, share prompts, discuss benchmarks, get hyped at the latest and greatest model releases! Enjoy talking about our awesome hobby.

As ambassadors of the self-hosting machine learning community, we strive to support each other and share our enthusiasm in a positive constructive way.

founded 2 years ago

MODERATORS

SkySyrup@sh.itjust.works

pax@sh.itjust.works

noneabove1182@sh.itjust.works

Smokeydope@lemmy.world

MonsterBug@sh.itjust.works

Beginner questions thread (sh.itjust.works)

submitted 2 years ago by noneabove1182@sh.itjust.works to c/localllama@sh.itjust.works

28 comments fedilink hide all child comments

Trying something new, going to pin this thread as a place for beginners to ask what may or may not be stupid questions, to encourage both the asking and answering.

Depending on activity level I'll either make a new one once in awhile or I'll just leave this one up forever to be a place to learn and ask.

When asking a question, try to make it clear what your current knowledge level is and where you may have gaps, should help people provide more useful concise answers!

you are viewing a single comment's thread
view the rest of the comments

[–] corvus@lemmy.ml 2 points 1 month ago (1 children)

Yeah I tested with lower numbers and it works, I just wanted to offload the whole model thinking it will work, 2GB it's a lot. With other models it prints about 250MB when fails and if you sum up the model size it's still well below the iGPU free memory so I dont get it... anyway, I was thinking about upgrading the memory to 32GB or may be 64GB but I hesitate because with models around 7GB and CPU only I get around 5 t/s and with 14GB 2-3 t/s, so I run one of around 30GB I guess it will get around 1 t/s? My supposition is that increasing RAM doesn't increase performance per se, just let's you upload bigger models to memory, so performance is approximately linear on model size... what do you think?

[–] hendrik@palaver.p3x.de 2 points 1 month ago* (last edited 1 month ago) (1 children)

From what I know, I assume yes, the relation between model size and speed/performance should be linear. Maybe there is some additional small overhead making it a bit faster or slower than expected. But I'm really not an expert on the maths, so don't trust me.

And maybe have a look at this bugreport: https://github.com/ggml-org/llama.cpp/issues/11332
I think it matches your situation. They resolve this by messing with the batch size and someone recommends not to use Vulkan on an iGPU.

[–] corvus@lemmy.ml 1 points 1 month ago

Oh great, thanks