Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0750dcdb20972e0bd0b8ef56ebffbe62b0b1c2d0db3e4e9f16c2d3ea2f8d74d
- Size of remote file:
- 153 kB
- SHA256:
- 8bc743805e21b28e12bbf9238159475f8f0b6083cdd5da74e958645d94929ec3
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