Transformers
Safetensors
Slovenian
wav2vec2-bert
audio-frame-classification
prosody
segmentation
audio
speech
Instructions to use classla/wav2vecbert2-prosodicUnit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/wav2vecbert2-prosodicUnit with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioFrameClassification processor = AutoProcessor.from_pretrained("classla/wav2vecbert2-prosodicUnit") model = AutoModelForAudioFrameClassification.from_pretrained("classla/wav2vecbert2-prosodicUnit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0becec32cd30928c1f005a9d1597c5d76a7cd30007df8a91e92fdfd9a4dcddd3
- Size of remote file:
- 2.32 GB
- SHA256:
- 01bf3d88497c8445add500252e1df8037b84d4a761a5d43e766edb9f8cb1ff9c
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