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I'd like to train models on data that with sample rates other than 48k and use them in the plugin. Currently, this could be done by hacking the training process and just knowing the sample rate to pick when running the plugin. But, I'd like this to be more fool-proof. This also currently rules out having two models with different expected sample rates from being used at the same time.
The text was updated successfully, but these errors were encountered:
I'd like to train models on data that with sample rates other than 48k and use them in the plugin. Currently, this could be done by hacking the training process and just knowing the sample rate to pick when running the plugin. But, I'd like this to be more fool-proof. This also currently rules out having two models with different expected sample rates from being used at the same time.
The text was updated successfully, but these errors were encountered: