Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
title: string
lyrics: string
artist: string
writer: string
source: string
url: string
to
{'title': Value('string'), 'lyrics': Value('string'), 'artist': Value('string'), 'source': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2674, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2208, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2232, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 483, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 260, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 120, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
title: string
lyrics: string
artist: string
writer: string
source: string
url: string
to
{'title': Value('string'), 'lyrics': Value('string'), 'artist': Value('string'), 'source': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
🎵 SynhalaAI — Ultimate Sinhala Song Lyrics Dataset (Gold Mix)
Dataset Description
The SynhalaAI Lyrics Corpus is a meticulously engineered, high-fidelity dataset of Sinhala song lyrics. It was designed specifically to train Large Language Models (LLMs) and advanced tokenizers on the poetic, colloquial, and structured linguistic patterns of the Sinhala language.
Unlike standard web-scraped datasets that are littered with English guitar chords, metadata, and HTML noise, this dataset has undergone a "Sinhala-First" Surgical Scrub. It is pristine, purely Sinhala, and spans decades of Sri Lankan music history.
🌟 Key Features
- AI-Grade Cleanliness: All English characters, guitar chords (e.g.,
[Am],G,Dm), beat markers (e.g.,Beat: 4/4), invisible Unicode ghost characters, and web links have been surgically removed. - Strict Deduplication: Songs are aggressively deduplicated using a 150-character lyric fingerprinting algorithm combined with title cross-referencing.
- Generational Span: Contains everything from classic 1960s hits to fresh 2024-2026 releases.
🏗️ The 3-Pronged Data Strategy
This Master Dataset is a conglomerate of the best Sinhala archives available, gathered through a three-phase data engineering pipeline:
- The Mega Conglomerate (History Archive): Aggregated data from 8+ of the largest open-source Sinhala search engine projects on GitHub, bringing in the bulk of classic and popular songs.
- Sources: Repositories by DilanSachi, BhanukaD610, Rashmini, Tharindu KW, rpjayasekara, Nirmal Gamage, and Thilina TLM.
- Linguistic & Metaphor Integration: Integrated high-quality, human-curated data from Kaggle (
pasinduudawatta/sinhala-songs-and-metaphors). - DIY Fresh Mixer (2024-2026): A custom, polite web scraper targeted at the "Gold Standard" (
Sinhalasongbook.com) to extract the absolute latest releases omitted from older static archives.
📊 Dataset Structure
The dataset is provided as a unified JSON array (sinhala_lyrics_MASTER.json) and a flat text corpus (sinhala_lyrics_corpus_MASTER.txt) optimized for tokenizer training (BPE/SentencePiece).
Data Fields
title(string): The title of the song (usually in Sinhala or Singlish).lyrics(string): The deeply cleaned, Sinhala-only text of the song lyrics.artist(string): The artist or singer of the song.source(string): The original source of the data (e.g.,github_archive,kaggle_metaphors,fresh_scraper).
Sample Entry
{
"title": "Bambareku Anduwa",
"lyrics": "බඹරෙකු ඇඬුවා මලක් ළඟදි බඹරෙකු ඇඬුවා\nඇඬුවා... මලක් ළඟදි බඹරෙකු ඇඬුවා \nඇහේ කඳුලු ඇති ඒ බඹරිඳු දැක\nඅඬන්නෙ ඇයිදෝ මල ඇසුවා... මල ඇසුවා...",
"artist": "Niranjala Sarojini",
"source": "fresh_scraper"
}
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