Distilling step-by-step: Outperforming larger language models with less training data and smaller model sizes
Distilling step-by-step: Outperforming larger language models with less training data and smaller model sizes
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Woah this is pretty interesting stuff, I wonder how practical it is to do, I don't see a repo offering a script or anything so may be quite involved but looks promising. Anything to reduce size while maintaining performance is huge at this time
The code is available here:
Somehow this is even more confusing because that code hasn't been touched in 3 months, maybe just took them that long to validate? Will have to read through it, thanks!