LocalLLaMA
Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.
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Rule 1 - No harassment or personal character attacks of community members. I.E no namecalling, no generalizing entire groups of people that make up our community, no baseless personal insults.
Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.
Rule 3 - No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they're still using the same algorithms since <over 10 years ago>.
Rule 4 - No implying that models are devoid of purpose or potential for enriching peoples lives.
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If you don't need cuda or ai, the 7900 is great.
You can run CUDA apps on ROCm HIP. It’s easy.
Whoa need to me. I'll have to dig in on that.
Well that's the question...
What you mean with "not needing ai"? I mean oobabooga and stable diffusion have AMD installers, and that's exactly what I am asking about. Therefore I post in community...
To find out how good those AIs run on AMD
Oops. I wasn't looking at the community just my main feed. Ok, so from what I understand the amd installer is a bit of a pain on Linux. If you're on windows it's probably a different story.
I am on Linux, but I can live with a painful install. I wanted to hear if it performs on par with nvidia
Again. Apologies for the confusion. I had thought my initial comment was on a gaming community. Here is puget systems benchmarks and they don't look great - https://www.pugetsystems.com/labs/articles/stable-diffusion-performance-nvidia-geforce-vs-amd-radeon/#Automatic_1111
"Although this is our first look at Stable Diffusion performance, what is most striking is the disparity in performance between various implementations of Stable Diffusion: up to 11 times the iterations per second for some GPUs. NVIDIA offered the highest performance on Automatic 1111, while AMD had the best results on SHARK, and the highest-end GPU on their respective implementations had relatively similar performance."
Sorry, not trying to come at you, but I’m just trying to provide a bit of fact checking. In this link, they tested on Windows which would have to be using DirectML which is super slow. Did Linus Tech Tips do this? Anyway, the cool kids use ROCm on Linux. Much, much faster.
Yeah that was what i was worried about after reading the article; I've heard about the different backends...
Do you have AMD + Linux + Auto111 / Ooobabooga? Can you give me some real-life feedback? :D
Haha, you're not, I definitely stumbled into this. These guys mainly build edit systems for post companies, so they stick to windows. Good to know about ROCm, got something to read up on.
No worries
Interesting article Never heard about SHARK, seems interesting then