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:
- 4d4e4542fead3ea90f04f27d3b97843079c231b9ba47ade8a213aaca1aba2346
- Size of remote file:
- 52.1 MB
- SHA256:
- 3099375b7d1fde7be7f4a0a0f66f570bca8fc5e9b16260b822168d829977b229
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