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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fbd042065bb0fc2534b15dd14c5c7ba210a2b73718a75f8ed02b7935bb689cb
- Size of remote file:
- 153 kB
- SHA256:
- 09ae323961c1421c8207742939765974645593d654856a183e200df17e774bcc
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