Instructions to use deepthink8/Deeepfake-audio-Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepthink8/Deeepfake-audio-Recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="deepthink8/Deeepfake-audio-Recognition")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("deepthink8/Deeepfake-audio-Recognition") model = AutoModelForAudioClassification.from_pretrained("deepthink8/Deeepfake-audio-Recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a88ab8f8600fda6043f5065bc47654c8932fb6fe9982b621de0a5939dcdb3c9b
- Size of remote file:
- 1.06 kB
- SHA256:
- 5699a0932df3dd97f15fcfcceb2d361d521d7117e842cbdb8f8aaaa5ca19c383
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