biggest barrier to this is the hardware requirements. I saw an estimate on r/machinelearning that based on the parameter count, gpt-3 needs around 350GB of VRAM. maybe you could cut that in half, or even one-eighth if someone figures out some crazy quantization scheme, but it's still firmly outside of the realm of consumer hardware right now.

stuff like koboldai can let you run smaller models on your hardware though (https://github.com/KoboldAI/KoboldAI-Client).