Instructions to use hf-internal-testing/tiny-random-UniSpeechSatForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UniSpeechSatForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-UniSpeechSatForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UniSpeechSatForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-UniSpeechSatForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43fb4160e9df4be35e6b45de7365c5b5bbf26666dcd5c2442f1c42c03f6294c0
- Size of remote file:
- 136 kB
- SHA256:
- 5a92a5d7778f376963c663662bd7c3a8477bb103249cf0a02766ebe1d8983ffd
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