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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9642dae173b07f5f3cbe25ad9ffc58c36ca7d19dbb1a77c193a32d590ee12e4e
- Size of remote file:
- 181 kB
- SHA256:
- ef6649323383fb261d94b601bbaf5ef2fea3a5d396ffc160c3410d51805dfa2f
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