Instructions to use hf-internal-testing/tiny-random-UniSpeechForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UniSpeechForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-UniSpeechForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UniSpeechForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-UniSpeechForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9c9b5cb0f80674c63623dbccb9b0ad92e4d819876297072b41c85e84e7e3917
- Size of remote file:
- 136 kB
- SHA256:
- eec9299e614b138731000f6161330c269abb3f6d7335c95cc2fc1e7dcf9b466a
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