this post was submitted on 06 Oct 2024
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They're not talking about the same thing.
That's in reference to the size of the model itself.
That's in reference to the size of the training data that was used to train the model.
Minimizing both of those things is useful, but for different reasons. Smaller training sets make the model cheaper to train, and a smaller model makes the model cheaper to run.
After a quick skim, seems like the article has lots of errors. Molmo is trained on top of Qwen. The smallest ones are trained on something by the same company as Molmo.