metadata
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"
Available at Portex
🎵 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. 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:
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.