Audio Classification
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Shamik/whisper-base.en-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shamik/whisper-base.en-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Shamik/whisper-base.en-finetuned-gtzan")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Shamik/whisper-base.en-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("Shamik/whisper-base.en-finetuned-gtzan") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c0a8903218be000f6daf1b190939fc051a783278a40cfa634b31b8fc930b3df
- Size of remote file:
- 4.6 kB
- SHA256:
- 27b5ff35d069cd9ab901455574743026df132e6323748e088c356480401e538d
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