Instructions to use DavidCombei/wavLM-base-Deepfake_V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidCombei/wavLM-base-Deepfake_V3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="DavidCombei/wavLM-base-Deepfake_V3")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("DavidCombei/wavLM-base-Deepfake_V3") model = AutoModelForAudioClassification.from_pretrained("DavidCombei/wavLM-base-Deepfake_V3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e66347a278818c82517616b610ba1fb27f3239d24962e40a8c509986f1a344a
- Size of remote file:
- 378 MB
- SHA256:
- c13868878bb7f19c1d28773761c6e34dcb5486d0a70c9877e48046da9ee66d29
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