Instructions to use anderloh/HuggingfaceTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceTest")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceTest") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceTest") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61193c6570e27131edfc0a14b98d28a21c34bdd00bc0dbed4eaac69a17c63197
- Size of remote file:
- 52.2 MB
- SHA256:
- e5fd8245595ad7fe1d3fdf171cad01ec66fd98baf68ba18e05b7868b9bd40bcf
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