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:
- c634e45429c5971810d511373581d39d52f2dacd1d6d8ce868a5e0b24061d9b2
- Size of remote file:
- 153 kB
- SHA256:
- b44f70d8483152200b0578a697c03957a7287d35eff45a89143f072ca2c04c11
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