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
| license: apache-2.0 | |
| datasets: | |
| - projectlosangeles/Los-Angeles-MIDI-Dataset | |
| library_name: transformers | |
| tags: | |
| - music | |
| - midi | |
| - music generation | |
| - midi generation | |
| # Model Card for midi-model | |
| Midi event transformer for music generation | |
| ### Model Updates | |
| - tv2o-medium model: MidiTokenizerV2. [skytnt/midi-model-tv2o-medium](https://huggingface.co/skytnt/midi-model-tv2o-medium) | |
| - v1.2 : Optimise the tokenizer and dataset. The dataset was filtered by MIDITokenizer.check_quality. Using the higher quality dataset to train the model, the performance of the model is significantly improved. | |
| ## Model Details | |
| ### Model Description | |
| - **Developed by:** SkyTNT | |
| - **Model type:** Transformer | |
| - **License:** apache-2.0 | |
| ### Model Sources | |
| - **Repository:** https://github.com/SkyTNT/midi-model | |
| - **Demo:** https://huggingface.co/spaces/skytnt/midi-composer | |
| ## Training Details | |
| ### Training Data | |
| - [projectlosangeles/Los-Angeles-MIDI-Dataset](https://huggingface.co/datasets/projectlosangeles/Los-Angeles-MIDI-Dataset) | |
| #### Training Hyperparameters | |
| - basemodel: v1.1 | |
| - lr: 1e-4 | |
| - weight-decay: 0.01 | |
| - batch: 2x2x2 | |
| - fp16 mixed precision | |
| #### Loss | |
| - val loss: 0.238 | |
| ## Files | |
| - model.ckpt: latest model checkpoint | |
| - soundfont.sf2: soundfont file, i put it here for convenient downloading , [source](https://github.com/musescore/MuseScore/tree/master/share/sound) | |
| - onnx/*.onnx: onnx format model | |