@Flopsie4: Hopefully in future work it's also explore how these byte models respond to quantization. If they respond the same or e…
Summary
A discussion on future work exploring how byte-level models respond to quantization for potential improvements in local AI, based on a Meta paper showing byte models outperforming token models as compute scales.
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Cached at: 09/15/26, 09:41 AM
Hopefully in future work it’s also explore how these byte models respond to quantization. If they respond the same or even better, this could provide big strides for local AI!
I will try to do some explorative research on this and will post my results publicly in a few days!
elvis (@omarsar0): Banger paper from Meta.
This work shows that byte-level models start out behind token models and then pass them as compute grows.
They show this for distilled 1B models trained on up to 1 trillion bytes.
To distill a byte student from a token teacher, they convert the
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