[zingelshuher]

It's a matter of opinion how much open model should be to be called 'open source'. Looks like some believe they have the right to define it for everybody else to use. Like for software. Have to disagree. Why don't we introduce a separate term: 'open source, training infrastructure and data included for free'?

"open weight model" is confusing, because actually the architecture is open too, only data is missing.

[snowpid]

the point of traditional open source software is what you can reproduce your build. This is not possible with open weight models.

[zingelshuher]

It's a different animal. In general you cannot reproduce the model even having all the training data. There are too many random factors and nobody keeps track of them. Just pushing the training data is done at random from the dataset. This results in some interesting facts. Having the model and the data it's impossible to say if the model was trained on that exactly data. All we can say is that some pieces of that data were used in training, in some cases. Model can be 'watermarked' in hard to detect, stable to quantization and finetuning way.

So, you cannot have a reproducible, 'open source' in its strict interpretation, model.