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:
- 8efbe9c1ac7a4fb800db844bc348f58e44179c870797ae84237f79c4ad1eb691
- Size of remote file:
- 4.03 kB
- SHA256:
- ff7fd2ef5e570e69c2faa083f81a2b6e53fcadd1ad21d5a398c344cdf42868f1
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