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Its architecture is similar to the [HuBERT model](https://huggingface.co/docs/transformers/model_doc/hubert), but it has been specifically designed for music through the use of specialized pre-training strategies.
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It is SOTA-comparable on multiple MIR tasks even under probing settings, while keeping fine-tunable on a single 2080Ti.
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It outperforms Jukebox representation on GTZAN (genre classification) and GiantSteps (key classification) datasets.
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Larger models trained with more data are on the way
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Its architecture is similar to the [HuBERT model](https://huggingface.co/docs/transformers/model_doc/hubert), but it has been specifically designed for music through the use of specialized pre-training strategies.
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It is SOTA-comparable on multiple MIR tasks even under probing settings, while keeping fine-tunable on a single 2080Ti.
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It outperforms Jukebox representation on GTZAN (genre classification) and GiantSteps (key classification) datasets.
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Larger models trained with more data are on the way.
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Noted: we also release a pre-trained MIR model [music2vec](https://huggingface.co/m-a-p/music2vec-v1/blob/main/README.md) before, which shares similar model structure but has weaker performance.
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