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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44e760293de968ef71b9ee00356530bf5eb02a0dbb1fe31bebb35c7c72f4b4d3
- Size of remote file:
- 154 kB
- SHA256:
- 7e1013dafae133423333b40ff80c55d68f40a88fe802211ef39fb62964eef065
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