mtg-upf
/

discogs-maest-10s-dw-75e

Audio Classification

audio-spectrogram-transformer

Inference Endpoints

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p-alonso commited on Nov 8, 2023

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@@ -13,6 +13,8 @@ MAEST is a family of Transformer models based on [PASST](https://github.com/kkou
 focused on music analysis applications.
 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).
 > 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.

 focused on music analysis applications.
 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).
+> Note: This model is available under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license for non-commercial applications and under proprietary license upon request.
+> [Contact us](https://www.upf.edu/web/mtg/contact) for more information.
 > 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.