Instructions to use amupd/parallel_wavegan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amupd/parallel_wavegan with Transformers:
# Load model directly from transformers import ParallelWaveGANGenerator model = ParallelWaveGANGenerator.from_pretrained("amupd/parallel_wavegan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f384a652283f46ecb30fd32a239c2f3c9df3a99f06be12fa3aed8fcb89a41421
- Size of remote file:
- 5.41 MB
- SHA256:
- cab10e9c27bcb62103caa39361bb26f576f7973dea38e547cfe5a9b1edc01e26
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