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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.
gemma 26b-a4b was fantastic, anything in that area is ideal
running my tiny rx6600 8gb vram
Oh hell yeah
I'm on my 1070 8gb copium so we're twinsies
Maybe they release a huge moe model with non-uniform quants and then we can get even more quality on those cute little cards
How's your experience with the 1070?
Mixed?
It's the lower bound of where LLMs are helpful. Anything less and the models would be either too slow to work or too dumb. With the 1070 they are already painfully slow but at least they're still good enough to do some menial tasks.
A good harness for web search etc does a lot though.
I have an M4 Pro 24GB and I still use Gemma 26B-A4B as my primary model. Beats every other model I’ve ever tried locally on most stuff except coding and tool use, so a Qwen 4 at this size would be super interesting