how is Llama with 13B parameters able to compete with GPT3 with 175B parameters? It's 10x+ less? How much RAM goes it take to run "a single node" of GPT3 / GPT3.5 / GPT4?
> the "number B" stands for "number of billions" of parameters... trained on?
No, it's just the size of the network (i.e. number of learnable parameters). The 13/30/65B models were each trained on ~1.4 trillion tokens of training data (each token is around half a word).
> Llama.cpp 30B
> LLaMA-65B
the "number B" stands for "number of billions" of parameters... trained on?
like you take 65 billion words (from paragraphs / sentences from like, Wikipedia pages or whatever) and "train" the LLM. is that the metric?
why aren't "more parameters" (higher B) always better? aka return better results
how many "B" parameters is ChatGPT on GPT3.5 vs GPT4?
GPT3: 175b
GPT3.5: ?
GPT4: ?
https://blog.accubits.com/gpt-3-vs-gpt-3-5-whats-new-in-open...
how is Llama with 13B parameters able to compete with GPT3 with 175B parameters? It's 10x+ less? How much RAM goes it take to run "a single node" of GPT3 / GPT3.5 / GPT4?