Pre-computed MERT-v1-330M embeddings for the FMA-Small dataset. 7,997 tracks, each represented as a 1024-dimensional vector, with banger scores (0-10) derived from log-normalized play counts.
Use this dataset to train music quality scorers, explore music similarity, or experiment with audio representation learning -- without needing to download 7.2 GB of audio or run MERT yourself.
Each row represents one track from FMA-Small… See the full description on the dataset page:
https://huggingface.co/datasets/treadon/fma-mert-embeddings.
