---
configs:
- config_name: a
  data_files: "a.jsonl"
- config_name: b
  data_files: "b.jsonl"
- config_name: c
  data_files: "c.jsonl"
- config_name: d
  data_files: "d.jsonl"
- config_name: e
  data_files: "e.jsonl"
- config_name: f
  data_files: "f.jsonl"
- config_name: g
  data_files: "g.jsonl"
- config_name: h
  data_files: "h.jsonl"
- config_name: i
  data_files: "i.jsonl"
- config_name: j
  data_files: "j.jsonl"
- config_name: k
  data_files: "k.jsonl"
- config_name: l
  data_files: "l.jsonl"
- config_name: m
  data_files: "m.jsonl"
- config_name: n
  data_files: "n.jsonl"
- config_name: o
  data_files: "o.jsonl"
- config_name: p
  data_files: "p.jsonl"
- config_name: q
  data_files: "q.jsonl"
- config_name: r
  data_files: "r.jsonl"
- config_name: s
  data_files: "s.jsonl"
- config_name: t
  data_files: "t.jsonl"
- config_name: u
  data_files: "u.jsonl"
- config_name: v
  data_files: "v.jsonl"
- config_name: w
  data_files: "w.jsonl"
- config_name: x
  data_files: "x.jsonl"
- config_name: y
  data_files: "y.jsonl"
- config_name: z
  data_files: "z.jsonl"
- config_name: embedding-subset1
  data_files: "verse-00001.jsonl"
- config_name: embedding-subset2
  data_files: "verse-00002.jsonl"
- config_name: YouTube Metadata
  data_files: "yt_metadata.jsonl"
- config_name: Missing YouTube Links
  data_files: "missing_links_processed.jsonl"
---

Excited to share Sleeping-DISCO 9M, a revolutionary dataset in the field of Music and artificial intelligence. We call it revolutionary because it was possible parts of recent legal landscape development done in EU (European Union) countries and in Germany. In the past, attempts were made to create a corpus like this in limited scale i.e. Genius Expertise from Cornell University, bandits datasets on Kaggle (owned by Google) and many other music platforms. 

Those attempts' scope were limited because of the uncharted legal territory of this field and finding good and verified information were hard as well. As there was no unified and verified catalogue such as Wikipedia for Music. But, we were able to solve this problem by collecting data from Genius.com which both reached the brevity and scale to be called Wikipedia for Music. We have collected over 9 million songs and their corresponding metadata and shared this as part of our paper **Sleeping-DISCO 9M**. 

We have two parts of this dataset, one that is available on Huggingface for the public called Sleeping-DISCO 9M (public) and another called Sleeping-DISCO 9M (academic) an exclusive academic edition for research labs and non-profit organisations and universities. 

arXiv paper, and in-depth information are coming next week. 

## LICENSE

We are releasing this under CC-BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en) We urge everyone to respect our licence.