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I had a model trained before the update you made 2 months ago.
Since then I updated everything to match the new version except that the cache folder stayed constant (accidentally).
I was experiencing any problem until today when I tried to run the trained model with the newly generated cache folder.
So my questions are,
Is the cache generation process any different between pre/post update?
Is there any concern if you train a new model with the post-update package with the old cache? Particularly, could it invalidate some of the nice assumptions that this model has?
Thank you so much in advance!
Nao
The text was updated successfully, but these errors were encountered:
I don't think we changed anything about the caching for a long time (if ever since the first release); but if you suspect a change somewhere, git diff allows you to compare different commits, so maybe that might help
as my answer to 1. is no, I don't suspect that using 'old caches' would lead to problems
First of all, thank you for this great work!
I had a model trained before the update you made 2 months ago.
Since then I updated everything to match the new version except that the cache folder stayed constant (accidentally).
I was experiencing any problem until today when I tried to run the trained model with the newly generated cache folder.
So my questions are,
Thank you so much in advance!
Nao
The text was updated successfully, but these errors were encountered: