This is the greatest misconception in this field. Weights are
not a binary form! In fact you can't "run" the weights as they are. They only represent some fixed values.
Whenever you use an LLM you "load" the weights, using (usually open source) code and you run inference with that code. The weights are not binary and the analogy to the binary form of distributing software is not valid, IMO.
That is why I used the analogy of a python code with ifs all the way, based on hardcoded values. That is what you are arguing is not open source. The weights are just "hardcoded values".
Open source never had the requirement of the author explaining what, why or how they got a hardcoded value in their shared code. Why it suddenly does for LLMs is what I find funny.
