There are some truly impressive open-source large language models out there. But when using them in a production environment, which performance metrics should I focus on? Considering the advantages of data privacy and local execution, how can I balance model size and hardware requirements? What methods do you prefer, and which model sizes (7B, 13B, 70B) are best suited for which scenarios?
What should we watch out for with open-source LLMs?
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Just two months into Python and I can't even run a 7B LLM 😅 70B? That would be next-level! 😮 Should I start with a GTX 1050? 🤔