Audio Classification
Transformers
TensorBoard
Safetensors
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use SLPL/Hubert-base-ShEMO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SLPL/Hubert-base-ShEMO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="SLPL/Hubert-base-ShEMO")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("SLPL/Hubert-base-ShEMO") model = AutoModelForAudioClassification.from_pretrained("SLPL/Hubert-base-ShEMO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad296cacc9d0fbe02172af3bba8fddd05b824e36431ea6732124a7272a02216a
- Size of remote file:
- 5.11 kB
- SHA256:
- 3010b2f261505a6c8b31bd49d040ae3a03ddbf88942a3afd35b62b72d7eea0a6
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