Instructions to use Library-Mutsumi/midi-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Library-Mutsumi/midi-model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Library-Mutsumi/midi-model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cc219d585256d381744722bff96c07a80c004f2784a9d89eea98c97a80fa584
- Size of remote file:
- 821 MB
- SHA256:
- 66c80e17d437c7c8f00d5974849f55fc3aa6ae55db4def3f2ba18670b7f7d8a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.