Instructions to use Dax99993/test_run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dax99993/test_run with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Dax99993/test_run")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Dax99993/test_run") model = AutoModelForAudioClassification.from_pretrained("Dax99993/test_run", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac4ce8903d99310d174169b7bdcb6f6ba7382f2a2b91904a0558de3025ae2fe0
- Size of remote file:
- 5.27 kB
- SHA256:
- 556ea06dd06d75388977e4b345eab4ab0ccd972fe3c53a659646fbef7851ecae
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