Instructions to use dima806/classical_composer_classification-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/classical_composer_classification-new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/classical_composer_classification-new")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dima806/classical_composer_classification-new") model = AutoModelForAudioClassification.from_pretrained("dima806/classical_composer_classification-new") - Notebooks
- Google Colab
- Kaggle
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README.md
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- [Mozart](https://en.wikipedia.org/wiki/Wolfgang_Amadeus_Mozart);
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- [Brahms](https://en.wikipedia.org/wiki/Johannes_Brahms).
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More details in https://www.kaggle.com/code/dima806/speech-accent-multiclass-classification.
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- [Mozart](https://en.wikipedia.org/wiki/Wolfgang_Amadeus_Mozart);
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- [Brahms](https://en.wikipedia.org/wiki/Johannes_Brahms).
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More details in [my Kaggle notebook](https://www.kaggle.com/code/dima806/speech-accent-multiclass-classification) and [my Medium post](https://pub.towardsai.net/creating-an-audio-classification-pipeline-for-identifying-classical-music-composers-1b3a5c453a66?sk=804fec0f2a3ba90e69724f95e703d677).
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