Instructions to use Bagus/wav2v2c_swbd_emodb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bagus/wav2v2c_swbd_emodb with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Bagus/wav2v2c_swbd_emodb") model = AutoModel.from_pretrained("Bagus/wav2v2c_swbd_emodb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 825fd6e71b75a385eadf7f4553bc28c2bd496e57ba75a8a9369f5379e3849d8c
- Size of remote file:
- 1.27 GB
- SHA256:
- f53ddd60f52482d68b5290490f4d5edee04cf065899eac6cf02e082019527dea
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