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
metadata
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
- 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
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
- onnx/*.onnx: onnx format model