Instructions to use hf-tiny-model-private/tiny-random-UniSpeechSatForSequenceClassification 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-UniSpeechSatForSequenceClassification 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-UniSpeechSatForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechSatForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechSatForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4adf06de4d368b00c2a923f1de8352e76739ede406d3e3a38a399ed06b58584f
- Size of remote file:
- 136 kB
- SHA256:
- 50592fe5063ce3eda2f46aea599c5db8bbb1eafea3e94e9405a126b8e4b2611f
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