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---
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.