this post was submitted on 30 Oct 2023
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LocalLLaMA
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Community to discuss about Llama, the family of large language models created by Meta AI.
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It looks weird going from 75B text-davinci-003 to 20B gpt-3.5-turno. But a) we don't know how they count this - a quantization effectively halves the number of parameters and b) we don't know anything how they made it.
except c) they threw much more money at it, using humans to clean the dataset. A clean dataset can make 20B sing. We are using META chaos in llama2 70b with everything thrown at it...
text-davinci-003 is 175B. You missed a 1 there