---
dataset_info:
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 6417909784
    num_examples: 244436
  - name: test
    num_bytes: 1221971111
    num_examples: 46005
  - name: validation
    num_bytes: 1465985310
    num_examples: 54947
  download_size: 974110589
  dataset_size: 9105866205
---
# Dataset Card for "lmd_clean_8bars_32th_resolution"

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Available at [Portex](https://marketplace.portexai.com/creator-profile)

## 🎵 Lakh MIDI to MMM-Style Text Dataset

This dataset converts the Lakh MIDI Dataset into a structured text format inspired by the [Multitrack Music Machine (MMM) paper](https://arxiv.org/abs/2008.01307). It includes **344,900 samples**, each representing an **8-bar symbolic music fragment**, tokenized into a language-model-friendly format.

Each line in the dataset is a music fragment composed of tokens like:

```sql
PIECE_START COMPOSER=JOHN_FARNHAM PERIOD= GENRE=TIME_SIG=4/4 TRACK_START INST=122 DENSITY=0 BAR_START TIME_DELTA=48 BAR_END ...
```

### 🔍 Metadata
- **Modality**: Text (converted from MIDI)
- **Format**: One tokenized sequence per line (plain text)
- **Size**: 344,900 rows
- **Source**: Derived from the Lakh MIDI Dataset
- **Structure**: Each row represents an 8-bar segment tokenized to match MMM syntax


### 🤖 Use Cases
- Pretraining or finetuning symbolic music models
- Sequence modeling research for music
- Input for generative transformer models
- Creative AI applications in music composition

### 🧠 Why this dataset?
Symbolic music datasets in tokenized, language-model-ready formats are rare. This dataset bridges audio-derived symbolic data and the world of NLP modeling, saving hours of preprocessing and formatting work for researchers and ML developers.