I like open-everything as much as the next person, but I don’t really agree with this position. The source code to run the model is open, as are the weights of the thing you’re running. I think it’s fair to say that they have open-sourced an LLM inference system. This isn’t traditional software, and it’s not clear how the term “open source” should be defined.
To stretch the analogy a different way, it could have been argued that PyTorch isn’t “open source” because the repo doesn’t include the private notes, sketches and communications of the team that developed it. How could someone reproduce the source code for themselves without access to the inputs that went into designing it?
Of course, we don’t define “open source” in that way for source code. But we could have.
You can't build the model from source with code. That's because the input data is an essential source of the model.
> I think it’s fair to say that they have open-sourced an LLM inference system.
Maybe they have. That's separate from the model though, and a lot of people use different, more standardized inference systems (Ollama, vLLM, etc).
> it could have been argued that PyTorch isn’t “open source” because the repo doesn’t include the private notes, sketches and communications of the team that developed it.
Those aren't inputs used to build a runnable package of PyTorch. The source of some binary is the human readable and editable input used to produce the binary. Notes and communications are human readable input to the already human readable code; it's therefore not a source for binaries build from the code.
LLM Weights are not human readable nor human editable. They are machine readable (through inferencing) and machine editable (through fine tuning). If that counts as open source, then so is any binary executable since patchelf and co exist.
The model is open weight, despite an OSI approved license sitting in the same directory as the binary blob.