Instructions to use Imxxn/AudioCourseU4-MusicClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Imxxn/AudioCourseU4-MusicClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Imxxn/AudioCourseU4-MusicClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Imxxn/AudioCourseU4-MusicClassification") model = AutoModelForAudioClassification.from_pretrained("Imxxn/AudioCourseU4-MusicClassification") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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metrics:
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---
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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## Model description
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.88
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8804
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- Accuracy: 0.88
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## Model description
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