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where does 256 come from? it's repeated in here and elsewhere that a single expert is 37B sized, so you'd have to have way more than "several hundred billion pa
by genewitch 2y ago
where does 256 come from? it's repeated in here and elsewhere that a single expert is 37B sized, so you'd have to have way more than "several hundred billion parameters", to hold 256 of those? Maybe i don't understand the architecture, but if that's the case, then everyone repeating 37B doesn't, either.
- zamadatix 2y agoI think this diagram from the DeepSeekMoE paper explains it the clearest: https://i.imgur.com/CRKttob.png https://i.imgur.com/CRKttob.png The one on the right is how the feed forward layers of DeepSeek V3/R1 work, blue and green are experts, and everything in that right section is what counts as "active parameters". K (K=8 for these models, but you can customize that if you want) experts of 256 per layer are activated at a time. The 256 comes from the model file, it's just how many they chose to build it with. In these models there is also 1 shared expert which is always active in the layer. The router picks which k routed experts to use each forward pass and then a gating mechanism combines the outputs. If you sum the 1 shared expert + K routed experts + router + output networks you end up with 37 B parameters active for each feed forward layer pass. The individual experts are therefore much smaller than the total (probably something like 4 B parameters each? I've never really checked that directly). Or, for the short answer: "37 B is the active parameters of 9 experts + 'overhead', not the parameters of a single expert".