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:
- 05e6737ae78621c50f17885aafe6ae596f1e57ba3e2829af77e724a58d6be636
- Size of remote file:
- 378 MB
- SHA256:
- 61f046095e067203694eb7ac3b56101f802c222508ff36c0e8a4fbc1f72d4125
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