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:
- a3b6cc7ab1d3a1346a5b0b703707b98767f021f77baa23fdbff5e787147645be
- Size of remote file:
- 94.8 MB
- SHA256:
- c8869b74be9eb583c40e300a6f02c665446e6feb929a56fb669b55f11c7323c4
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