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DeepNewz, mobile.
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Recent developments in the field of Language Model (LLM) technology have shown significant improvements in speed and efficiency. Justine Tunney has made llamafile 1.3x - 5x faster than llama.cpp on CPUs for various evaluation tasks. Local open-source LLMs are now faster and more efficient on personal computers, eliminating the need for centralized AI. Testing has shown that prompt evaluation times with llamafile can be up to 500% faster compared to llama.cpp when using specific weights on CPUs.
How to rate LLM AI? The Street Fighter game. The amazing @rschu built the new way to test for speed, strategy, logic and 3D awareness. You can test ANY LLM! My weekend test: Grok-1 open source from https://t.co/KthS0SlWM4 won against all! Code: https://t.co/CTtzkWZDgv https://t.co/jFXJSlwdjp
As expected the LLM from @enq_AI fucks. Not only is it uncensored, unbiased and based. It is also beautiful, fast and provides answers of comparable quality and depth of chatgpt. My thesis: decentralised AI will win. Open source always wins in the end. Why would people pay… https://t.co/bfHR0ifpf3
LLaMA Now Goes Faster on CPUs "Compared to llama.cpp, prompt eval time with llamafile should go anywhere between 30% and 500% faster when using F16 and Q8_0 weights on CPU." https://t.co/NOrBi4BRbh
