# This is the code for the paper "Symbolic Music Generation with Fine-grained Interactive Textural Guidance" submitted to ICLR 2025

## 1. Data

First, run data/train_test_data_generation.py to generate the training samples and the test samples

## 2.Training

Due to file size limits, we do not provide the pre-trained checkpoints. You can run train.py to train your own model. It takes roughly 10 minutes to train on a NVIDIA RTXA6000 Ada GPU

## 3. Generation

The notebook generation.ipynb provides the code for generation. It generates 4-measure pieces from the data in our test set. You can use your own data to replace them.