Instructions to use hf-internal-testing/tiny-random-WavLMForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WavLMForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-WavLMForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WavLMForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-WavLMForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49041d30edba301df74091726f7afbedbc5ca4c63ca134a303c57f1fdca15075
- Size of remote file:
- 141 kB
- SHA256:
- a26ba4aa82f10226421f8c1915282350366a11958e3c74ceec6d5f340c7b2f44
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