3 ms·
Hello you might be talking about reducing the size of the model itself (i.e., the trained weights) by orders of magnitude without losing accuracy, that's indeed
by 3Sophons 3y ago
Hello you might be talking about reducing the size of the model itself (i.e., the trained weights) by orders of magnitude without losing accuracy, that's indeed a different challenge. But the article discusses reducing the inference app size by 100x
- hnarayanan 3y agoOh. Did not think that was even a goal.
- 3Sophons 3y agoI guess making it portable is still quite important?
- hnarayanan 3y agoI am not trying to troll. I genuinely don’t see why a few MB on some binary matter when the models are multiple GB large. This is why I fundamentally misunderstood the article, my brain was looking for the other number going down as that’s genuinely a barrier for edge devices.