Instructions to use RickyIG/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RickyIG/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="RickyIG/audio_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("RickyIG/audio_classification") model = AutoModelForAudioClassification.from_pretrained("RickyIG/audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e31651eb5d5fc5b88d1f999fa611830c0ae6e38eca3f72cccd16f8b2bea3b4c1
- Size of remote file:
- 4.09 kB
- SHA256:
- 3903cf923d3188e00e81a7f5ffe0c2f2b227933e652eb46938e984aa303311a5
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