Instructions to use hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2fdc9594df3dc08d070c3d6c1c2bbdeb5b18b4be6b10f8fe768b1b9599a4c95
- Size of remote file:
- 136 kB
- SHA256:
- c218fb93939625ded3bd48c03c67163e9adfce15e8873e913079d406f031d123
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