Instructions to use hf-internal-testing/tiny-random-ASTForAudioClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ASTForAudioClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-ASTForAudioClassification")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-ASTForAudioClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-ASTForAudioClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82e9eda33fccdbcbe9b8b329371a354a374c97718189e86dd43742b3dde03d0a
- Size of remote file:
- 314 kB
- SHA256:
- 1beaf5126a63db33498b1bd0c55085081476ab98436cf36cf9223ccb366dc3d1
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