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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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.
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If you're running a consumer level GPU, you'll be operating with 24GB of VRAM max (RTX 4090, RTX 3090, or Radeon 7900XTX).
90b model = 90GB at 8-bit quantization (plus some extra based on your context size and general overhead, but as a ballpark estimate, just going by the model size is good enough). You would need to drop down to 2-bit quantization to have any hope to fit it in a single consumer GPU. At that point you'd probably be better off using a smaller model will less aggressive quantization, like a 32b model at 4-bit quantization.
So forget about consumer GPUs for that size of model. Instead, you can look at systems with integrated memory, like a Mac with 96-128GB of memory, or something similar. HP has announced a mini PC that might be good, and Nvidia has announced a dedicated AI box as well. Neither of those are available for purchase yet, though.
You could also consider using multiple consumer GPUs. You might be able to get multiple RTX 3090s for cheaper than a Mac with the same amount of memory. But then you'll be using several times more power to run it, so keep that in mind.
You can use system ram for when the GPU memory fills up. Alternatively you can run multiple GPUs.