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:
- 2301a04cc316fc8bc5da56ce6d59ed2facf10f4f7f5a4851ff81f1f78642a154
- Size of remote file:
- 232 kB
- SHA256:
- 3243c3738b8bd879637c2b6efce31952edf6422805439d0bbe6b65b7ace4218b
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