Feature Extraction
Transformers
Safetensors
sheetsage2
audio
music
music-transcription
midi
abc-notation
custom_code
Instructions to use m-a-p/SheetSage2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-a-p/SheetSage2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="m-a-p/SheetSage2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m-a-p/SheetSage2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Correct chord spelling with local keys and canonicalize key labels
Verified signatureApply the SheetSage2 LM chord-spelling scorer at each chord midpoint in LAB, ABC and playback exports. Canonicalize key labels using the LM/NoLM key map without changing numeric token IDs or the vocabulary fingerprint. Verify pitch spelling against NoLM, preserve raw decoded chord events, and add regression coverage for key changes, inversions, in-memory exports, paper mode and melody-only mode.e8b16e3
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Release SheetSage2
eab522a