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I deployed the inference pipeline in a GPU provider. However, the song generation takes too long (5 mins for a 4 min song), which is much longer that what I am reading in the threads. I found that the GPU is barely used in the generation. Probably that is the issue.
Do you know what I might be missing?
Thanks
The text was updated successfully, but these errors were encountered:
What I have noticed is that what is really taking up a lot of time is the preprocessing of songs, i.e. vocal-instruments separation, vocal-background-vocal separation and vocal denoising. Under the hood this is done using MDX-net models. I tried performing the same conversions in the UVR app manually and it is noticeably faster, so there might be room for some improvement here. I am working on it myself (but progress is slow).
Hello,
I deployed the inference pipeline in a GPU provider. However, the song generation takes too long (5 mins for a 4 min song), which is much longer that what I am reading in the threads. I found that the GPU is barely used in the generation. Probably that is the issue.
Do you know what I might be missing?
Thanks
The text was updated successfully, but these errors were encountered: