Instructions to use DunnBC22/Is_Vinyl_Scratched_Or_Not with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/Is_Vinyl_Scratched_Or_Not with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="DunnBC22/Is_Vinyl_Scratched_Or_Not")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("DunnBC22/Is_Vinyl_Scratched_Or_Not") model = AutoModelForAudioClassification.from_pretrained("DunnBC22/Is_Vinyl_Scratched_Or_Not") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b44233abf074762f51edeac421b93bb15b614582d93272a84374cb73af2619c8
- Size of remote file:
- 3.5 kB
- SHA256:
- 4521181070c5206d39fa1359aeb62443676d9d133bf030a8d47fe7908ee32f60
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