Releasing the trained model does not make it open source.

Open source means something else.

Calling released trained models open source is akin to releasing the binaries of a software for free, without releasing the source code, and calling it open source.

This comes down to arguing over semantics. Many will argue that "open source" means using a license listed at https://opensource.org/licenses/ . Even CC0 isn't considered open source by this standard.

Even I feel that "700M monthly active user" gives not-so-open vibes, but frankly many of these "open source" licenses have oddly restrictive requirements as well.

You demonstrably don't understand what open source means, which is basically my point, that people like Lecun have been trying to corrupt the meaning to be equivalent to "source available".

I agree with the point you made elsewhere that releasing the data is irrelevant.

> LLAMA2 is very much open source.

The inference and training software used to run the model are open source, the concrete model -- that is, the thing for which the weights are the object code -- is not.

The concrete model is free-to-use closed source, which is better than an undisclosed blob hiding behind a SaaS service, but still not open source.

It's also good that the inference and training code are open source, even though the training data and configuration is not.

It's only open source if you can generate the binary weights from the training data and the training algorithm and training (hyper) parameters, from scratch. Releasing only the binary weights, does not make it open source, just like releasing only binary executables has nothing to do with open source.