Instructions to use hf-internal-testing/tiny-random-HubertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-HubertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-HubertForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-HubertForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-HubertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5ac8505c74ef838a3137098dcecc09ebed580a59d48b12e76803aa06284e3ac
- Size of remote file:
- 135 kB
- SHA256:
- 14265067f1a9eae9ddf7a021432e0ce4064a7e2d68add8b7ab574027d3bd5e66
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