Instructions to use WWWxp/wav2vec2_spoof_dection_project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WWWxp/wav2vec2_spoof_dection_project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="WWWxp/wav2vec2_spoof_dection_project")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("WWWxp/wav2vec2_spoof_dection_project") model = AutoModelForAudioClassification.from_pretrained("WWWxp/wav2vec2_spoof_dection_project") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d3e6aaa0a89aaebfa431ef77269725d0558a0dc3d010d0dcd58f61ab1e1cb6c1
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size 378302312
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