If i have multiple 7b models where each model is trained on one specific topic (e.g. roleplay, math, coding, history, politic…) and i have an interface which decides depending on the context which model to use. Could this outperform bigger models while being faster?
Yeah if that’s the case, I can see gpt-4 requiring about 220-250B of loaded parameters to do token decoding