The issue is that "open source" is a term for computer software. And it doesn't really apply to other things. But people use it regardless. With software, it means you share the recipe, the program code. With machine learning models, there isn't really such a thing. It's a pile of numbers (the weights) that are the important thing. They get shared in this case. But you can't reproduce them. For that you'd need the dataset that went in (which Meta doesn't share because lots of that is copyrighted and they have several court cases running because they just stole the texts and said it's alright.) But what open source allows (amongst other things) is to build upon things and modify them. And that can be done with the models to a certain degree. They can be fine-tuned and incorporated in custom projects. In the end they (Meta) want to frame things a certain way and be the good guys. But the term still doesn't really mean what it's supposed to mean.
There are other models with other licenses. There are Apache-licensed models available. There are models which do or don't allow for commercial usage. We also have some with the datasets and everything available. But at least those aren't state of the art anymore.