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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6939b7638f9e5f538e51669219f94629ee80fcf34dd0a90283f2cd1af9ab4a3
- Size of remote file:
- 154 kB
- SHA256:
- db7281a776f1c656afdc79960b0c66cb82b109cc4f7b9b857fb56d1ff07ba063
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