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:
- 9f9e884385a2accc521141c0b62b1ae1ea2244e527880dc0d3f4a0102daaa8b0
- Size of remote file:
- 4.54 kB
- SHA256:
- 8eb6cd0bfdd832ede4a3a715b5ed3195824ed818f08c721b1d32d5bb6dfde78f
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