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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45eb68901df4540f25310208833afb37258da1cf983cdb0c47004e374e00f495
- Size of remote file:
- 4.41 kB
- SHA256:
- 83a4f91271ced36eb6bbf9bb98dc019db10300be6cf9d9722118e2b7943a656e
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