Instructions to use WWWxp/wav2vec2_spoof_dection1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WWWxp/wav2vec2_spoof_dection1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="WWWxp/wav2vec2_spoof_dection1")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("WWWxp/wav2vec2_spoof_dection1") model = AutoModelForAudioClassification.from_pretrained("WWWxp/wav2vec2_spoof_dection1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6968afddaee3453bc02ad747016b606fcd2330701ef43dc1da708c45cfdb04b
- Size of remote file:
- 3.58 kB
- SHA256:
- 697dac4653cf1066daab37f3444134d0b5149deaccb0f5ab08353602c605d8ca
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