this post was submitted on 21 Nov 2024
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No. This is an inference model, not a generative model. You generally cannot train a model for both, unless you do it on purpose, and they certainly did not (especially since inference models are way easier to train than generative models).
A generative model uses the classifier as part of its training. If you generate a picture of pure random noise, then iteratively pick random noise that the classifier says "looks" more like csam, then you can effectively generate images that the classifier says it's 100% certain is csam. Whether or not that looks anything like what a human would consider to be csam depends on other factors but it remains a possibility.
You are describing the way deepdream works, not the way modern Diffusion models work. It's the difference between psychedelic dog faces and a highly adherent generative image of a German Sheppard.
I can't imagine you're going to get anything out of this model that actually looks like CSAM, unless there's some sort of breakthrough in using these models for previously unrealized generative purposes.