Instructions to use mbien/fma2vec2popularity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbien/fma2vec2popularity with Transformers:
# Load model directly from transformers import AutoProcessor, Wav2Vec2ForAudioClassification processor = AutoProcessor.from_pretrained("mbien/fma2vec2popularity") model = Wav2Vec2ForAudioClassification.from_pretrained("mbien/fma2vec2popularity") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e178ad589feeb1eb445971dea0750ebd86810a6f4b97ca2256de948ee09b4363
- Size of remote file:
- 378 MB
- SHA256:
- 011837f784bbabc21c2cb696e158b9d565038e4c1eb3d461dd2381d998793add
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