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  MAEST is a family of Transformer models based on [PASST](https://github.com/kkoutini/PaSST) and
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  focused on music analysis applications.
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- The MAEST models are also available for inference only as part of the
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- [Essentia](https://essentia.upf.edu/models.html#MAEST) library, and in the [official repository](https://github.com/palonso/MAEST).
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  > Note: The MAEST models rely on [custom code](https://huggingface.co/docs/transformers/custom_models#using-a-model-with-custom-code). Set `trust_remote_code=True` to use them within the [🤗Transformers](https://huggingface.co/docs/transformers/)' `audio-classification` pipeline.
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  MAEST is a family of Transformer models based on [PASST](https://github.com/kkoutini/PaSST) and
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  focused on music analysis applications.
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+ The MAEST models are also available for inference in the [Essentia](https://essentia.upf.edu/models.html#maest) library and for inference and training in the [official repository](https://github.com/palonso/MAEST).
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  > Note: The MAEST models rely on [custom code](https://huggingface.co/docs/transformers/custom_models#using-a-model-with-custom-code). Set `trust_remote_code=True` to use them within the [🤗Transformers](https://huggingface.co/docs/transformers/)' `audio-classification` pipeline.
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