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README.md

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 ---
-license: mit
+license: other
+license_name: cc-by-nc-sa-4.0
+license_link: https://creativecommons.org/licenses/by-nc-sa/4.0/
+tags:
+- audio-to-score-transcription
+- music-information-retrieval
+- lead-sheet
+- lyrics
+library_name: pytorch
 ---
+
+# SheetSage-A2LS model checkpoints
+
+Model checkpoints for **Audio-to-Lead-Sheet Transcription (A2LS)**, the retrained
+models described in our paper (under review). Each checkpoint greedily decodes a
+Humdrum `**kern` lead sheet (melody `**kern`, chords `**cdata`, lyrics `**text`)
+from pre-computed [MuQ](https://github.com/tencent-ailab/MuQ) features.
+
+| file | lyrics tokeniser |
+|---|---|
+| `final_no_lyrics_augmented.ckpt` | none |
+| `final_syllable_augmented.ckpt` | syllable |
+| `final_char_augmented.ckpt` | character |
+| `final_bpe_augmented.ckpt` | BPE (GPT-2) |
+
+Inference and evaluation code: [GitHub repository](https://github.com/Multimodal-Music-Research-Lab/Audio-to-Lead-Sheet-Transcription).
+
+Weights are released under CC-BY-NC-SA 4.0.

final_bpe_augmented.ckpt

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final_char_augmented.ckpt

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final_no_lyrics_augmented.ckpt

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final_syllable_augmented.ckpt

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