# Evaluation

The scripts behind the numbers on the model card. You only need [uv](https://docs.astral.sh/uv/getting-started/installation/).

```bash
uv sync
uv run song_describer.py jaisawhney/SonicEmbed
uv run clap_eval.py
uv run mteb_tasks.py jaisawhney/SonicEmbed --output-dir mteb-results/sonicembed
```

Models can be a Hugging Face ID or a local folder, so `google/embeddinggemma-2` scores the base model. Add `--device mps` on Apple silicon or `--device cpu` if you don't have an NVIDIA GPU.

Song Describer downloads 3.3 GB on the first run.