└── README.md


/README.md:
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 1 | # Open unmix for tensorflow
 2 | 
 3 | Since the release of [open-unmix](https://open.unmix.app) in September 2019, the source separation landscape has evolved regarding pre-trained models.
 4 | 
 5 | Open-unmix was designed as a baseline to make it easier to do source separation research. Now, spleeter has been made available and got much popularity since its release. We believe it is a good implementation for users to apply source separation in a signal processing pipeline.
 6 | 
 7 | For this reason, we decided to __not release the tensorflow implementation of open-unmix publicly__, but rather to make it available for commercial applications.
 8 | 
 9 | We continue to improve and update the [PyTorch release](https://github.com/sigsep/open-unmix-pytorch) and we believe that in terms of academic research, this follows the current trend in the community to vastly favor this framework.
10 | 


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