Instructions to use Danieljava/distilhubert-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Danieljava/distilhubert-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Danieljava/distilhubert-finetuned-gtzan")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Danieljava/distilhubert-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("Danieljava/distilhubert-finetuned-gtzan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ced75ea9b02bad887f6ca8931bf4f25194058037c6bcadbacc80b30a7856203d
- Size of remote file:
- 5.2 kB
- SHA256:
- 2b791a1d8a819547ffce408d27e4185b77a1a0a1c5e6ede714ebedf758459f96
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