LocalLLaMA

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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.

Rules:

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.

founded 2 years ago

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So image generation is where it's at? (sh.itjust.works)

submitted 2 weeks ago by rkd@sh.itjust.works to c/localllama@sh.itjust.works

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Total noob to this space, correct me if I'm wrong. I'm looking at getting new hardware for inference and I'm open to AMD, NVIDIA or even Apple Silicon.

It feels like consumer hardware comparatively gives you more value generating images than trying to run chatbots. Like, the models you can run at home are just dumb to talk to. But they can generate images of comparable quality to online services if you're willing to wait a bit longer.

Like, GPT OSS 120b, assuming you can spare 80GB of memory, is still not GPT 5. But Flux Shnell is still Flux Shnel, right? So if diffusion is the thing, NVIDIA wins right now.

Other options might even be better for other uses, but chatbots are comparatively hard to justify. Maybe for more specific cases like code completion with zero latency or building a voice assistant, I guess.

Am I too off the mark?

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[–] afk_strats@lemmy.world 2 points 4 days ago (1 children)

It depends on your goals and your use case.

Do you want the most performance per dollar?You will never touch what the big datacenters can achieve.
Do you want privacy? Buy it yourself?
Do you want quality output? Go to the online providers or expect to pay more to build it yourself.

I am actively trying to work on non-Nvidia hardware because I'm a techno-masochist. It's very uphill especially at the cutting edge. People are building for CUDA.

I can do amazing image generation on a 7900xtx with 24gb of vram. One of those is under 900 in the US which is great. A 3090 would probably be easier and is more expensive although it's less performant hardware

[–] rkd@sh.itjust.works 1 points 4 days ago

I believe right now it's also valid to ditch NVIDIA given a certain budget. Let's see what can be done with large unified memory and maybe things will be different by the end of the year.