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@@ -4,7 +4,7 @@ A PyTorch implementation of [SampleRNN: An Unconditional End-to-End Neural Audio
![A visual representation of the SampleRNN architecture](http://deepsound.io/images/samplernn.png)
-It's based on the reference implementation in Theano: https://github.com/soroushmehr/sampleRNN_ICLR2017. Unlike the Theano version, our code allows training models with arbitrary number of tiers, whereas the original implementation allows maximum 3 tiers. However it doesn't have weight normalization and doesn't allow using LSTM units (only GRU). For more details and motivation behind rewriting this model to PyTorch, see our blog post: http://deepsound.io/samplernn_pytorch.html.
+It's based on the reference implementation in Theano: https://github.com/soroushmehr/sampleRNN_ICLR2017. Unlike the Theano version, our code allows training models with arbitrary number of tiers, whereas the original implementation allows maximum 3 tiers. However it doesn't allow using LSTM units (only GRU). For more details and motivation behind rewriting this model to PyTorch, see our blog post: http://deepsound.io/samplernn_pytorch.html.
## Dependencies