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)# 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
| # Third-party notices | |
| - MERT-v2-FullSong provides the public music encoder. Its weight terms remain CC BY-NC 4.0. | |
| - The BART decoder uses Hugging Face Transformers (Apache 2.0); PyTorch uses its BSD-style license. | |
| - abcjs 6.6.3 is distributed under MIT; its license accompanies the rendering assets. | |
| - Playwright is distributed under Apache 2.0. Chromium is installed separately with its accompanying notices. | |
| - FluidR3 piano samples by Frank Wen use CC BY 3.0 US. Attribution and source information accompany the samples. | |
| - Other installed dependencies retain their respective licenses. | |