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Hi thanks for sharing the great work. I run the LM PTB demo and finished the full embed and kdq embed training.
But according to the results, for the full embed, the final results are:
total 110508
5094892 Oct 27 23:21 model-46445.meta
79 Oct 27 23:21 checkpoint
79100812 Oct 27 23:21 model-46445.data-00000-of-00001
465 Oct 27 23:21 model-46445.index
18189654 Oct 27 19:14 graph.pbtxt
while the kdq embed results are:
total 112252
5324218 Oct 27 23:42 model-46445.meta
79 Oct 27 23:42 checkpoint
79767436 Oct 27 23:42 model-46445.data-00000-of-00001
634 Oct 27 23:42 model-46445.index
18567704 Oct 27 19:13 graph.pbtxt
It seems like the kdq model is even larger. How should I estimate the real compression performance? Thanks.
(I used K=128, D=50, type=smx, share subspace=False, additive quantization=False)
The text was updated successfully, but these errors were encountered:
Hi thanks for sharing the great work. I run the LM PTB demo and finished the full embed and kdq embed training.
But according to the results, for the full embed, the final results are:
total 110508
5094892 Oct 27 23:21 model-46445.meta
79 Oct 27 23:21 checkpoint
79100812 Oct 27 23:21 model-46445.data-00000-of-00001
465 Oct 27 23:21 model-46445.index
18189654 Oct 27 19:14 graph.pbtxt
while the kdq embed results are:
total 112252
5324218 Oct 27 23:42 model-46445.meta
79 Oct 27 23:42 checkpoint
79767436 Oct 27 23:42 model-46445.data-00000-of-00001
634 Oct 27 23:42 model-46445.index
18567704 Oct 27 19:13 graph.pbtxt
It seems like the kdq model is even larger. How should I estimate the real compression performance? Thanks.
(I used K=128, D=50, type=smx, share subspace=False, additive quantization=False)
The text was updated successfully, but these errors were encountered: