Audio Classification
Transformers
TensorBoard
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Eval Results (legacy)
Instructions to use anand095/ast-finetuned-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anand095/ast-finetuned-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anand095/ast-finetuned-custom")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("anand095/ast-finetuned-custom") model = AutoModelForAudioClassification.from_pretrained("anand095/ast-finetuned-custom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse filesUpdated model and training details
README.md
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# ast-finetuned-gtzan
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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value: 0.94
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# ast-finetuned-gtzan
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## Model description
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MIT/ast-finetuned-audioset-10-10-0.4593 model has been used with the head replaced for classification of the 10 music genres.
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## Intended uses & limitations
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## Training and evaluation data
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GTZAN dataset has been used for training. 20% split was used for evaluation.
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## Training procedure
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