Instructions to use hf-tiny-model-private/tiny-random-SEWDForSequenceClassification 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-SEWDForSequenceClassification 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-SEWDForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SEWDForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-tiny-model-private/tiny-random-SEWDForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f1c8cadeeafeb9dea3970c80be3ca9e1a5cd3df7bf3dc75603af67a0510cca0
- Size of remote file:
- 307 kB
- SHA256:
- 1e8ca39361b9e9218f473e73a7fb83bfda3c3d53074f0ff969c12ed9e1a7ab44
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