Instructions to use Bagus/wav2vec2_swbd_emodb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bagus/wav2vec2_swbd_emodb with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Bagus/wav2vec2_swbd_emodb") model = AutoModel.from_pretrained("Bagus/wav2vec2_swbd_emodb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fed95765ca548df0968f7ce11ba83952d916f3559584677e44ab176a9df2443b
- Size of remote file:
- 1.27 GB
- SHA256:
- ba2316fc9d94c6d8c6f07f6333d2530247afa416539d79010b0680a3042efb76
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