Last time I looked into this, the answer was "because huggingface transformers and torch.load are written to do it this way"

You could absolutely do something streaming, or mmap the weights instead of loading them into system RAM. Just the default interfaces don't.

I'm not sure it could be for this complex quantization scheme. It's not a simple round to nearest quantization. Even if it is possible, it would require someone to develop that functionality. Currently it does load the entire unquantized model into RAM first.