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.
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.
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This Dockerfile worked for me to build the llama-cpp-turboquant fork: https://huggingface.co/spaces/ai-engineering-at/llama-cpp-turboquant-guide/blob/main/Dockerfile. Should work for upstream too. The Dockerfile I made myself crashed 2 different machines, but then I found this one and can confirm it works well.
I've got an AMD system so that probably won't work for me, but glad it's working for you and maybe it will help others!
How does the model compare to Qwen and Gemma4 so far?
Ah, ok, hope it helps someone. I’ll probably try the model this week sometime.