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:
- 84f165171da6c21069d037aa336f3bd80243282ae1e58c95329a29ed57af244e
- Size of remote file:
- 4.98 kB
- SHA256:
- 3f5d4b8806b7469d1ed9eae59ee1d37cab8cefda3aafd96ccd335721fc2198f5
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