Instructions to use anderloh/testModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/testModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/testModel")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/testModel") model = AutoModelForAudioClassification.from_pretrained("anderloh/testModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bf802fec9796fdd44c2caed90872cb5ab297c7f1767280510ba03fc0500c344
- Size of remote file:
- 95.9 MB
- SHA256:
- 9a09185a17f010331fa30a6f90e9ed772b8d6a73736f0f590c26c3a173232702
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