Audio Classification
Transformers
PyTorch
Safetensors
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/distilhubert-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/distilhubert-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Sagicc/distilhubert-finetuned-gtzan")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Sagicc/distilhubert-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("Sagicc/distilhubert-finetuned-gtzan") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6832c96b16a91fc298c0c3a489fc567f47bb24fdfdbfe8afecace7abcab0bed3
- Size of remote file:
- 94.8 MB
- SHA256:
- 1f850070446c9004273cd9a14d043f090ca441a5fe96b5e1bd027575682b3c05
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