Sangraha

Sangraha is the largest high-quality, cleaned Indic language pretraining data containing 251B tokens summed up over 22 languages, extracted from curated sources, existing multilingual corpora and large scale translations.

More information:

• For detailed information on the curation and cleaning process of Sangraha, please checkout our paper on Arxiv;
• Check out the scraping and cleaning pipelines used to curate Sangraha on GitHub;

Getting Started

For downloading the entire Sangraha:

from datasets import load_dataset

dataset = load_dataset("ai4bharat/sangraha")

For downloading a subset (Verified/Unverified) of Sangraha:

from datasets import load_dataset

dataset = load_dataset("ai4bharat/sangraha", data_dir="<subset_name>")
# for example: dataset = load_dataset("ai4bharat/sangraha", data_dir="verified")

For downloading one language from a subset of Sangraha:

from datasets import load_dataset

dataset = load_dataset("ai4bharat/sangraha", data_dir="<subset_name>/<lang_code>")
# for example: dataset = load_dataset("ai4bharat/sangraha", data_dir="verified/asm")

Background

Sangraha contains three broad components:

• Sangraha Verified: Containing scraped data from "human-verified" Websites, OCR-extracted data from high quality Indic language PDFs, transcribed data from various Indic language videos, podcasts, movies, courses, etc.
• Sangraha Unverfied: High quality Indic language data extracted from existing multilingual corpora employing perplexity filtering using n-gram language models trained on Sangraha Verified.
• Sangraha Synthetic: WikiMedia English translated to 14 Indic languages and further "romanised" from 14 languages by transliteration to English.

Data Statistics

Lang Code	Verified	Synthetic	Unverified	Total Tokens (in Millions)
asm	292.1	11,696.4	17.5	12,006.0
ben	10,604.4	13,814.1	5,608.8	30,027.5
brx	1.5	-	-	1.5
doi	0.06	-	-	0.06
eng	12,759.9	-	-	12,759.9
gom	10.1	-	-	10.1
guj	3,647.9	12,934.5	597.0	17,179.4
hin	12,617.3	9,578.7	12,348.3	34,544.3
kan	1,778.3	12,087.4	388.8	14,254.5
kas	0.5	-	-	0.5
mai	14.6	-	-	14.6
mal	2,730.8	13,130.0	547.8	16,408.6
mar	2,827.0	10,816.7	652.1	14,295.8
mni	7.4	-	-	7.4
npi	1,822.5	10,588.7	485.5	12,896.7
ori	1,177.1	11,338.0	23.7	12,538.8
pan	1,075.3	9,969.6	136.9	11,181.8
san	1,329.0	13,553.5	9.8	14,892.3
sat	0.3	-	-	0.3
snd	258.2	-	-	258.2
tam	3,985.1	11,859.3	1,515.9	17,360.3
urd	3,658.1	9,415.8	1,328.2	14,402.1
tel	3,706.8	11,924.5	647.4	16,278.7
Total	64,306.1	162,707.9	24,307.7	251,321.0

To cite Sangraha, please use:

@article{khan2024indicllmsuite,
  title   = {IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages},
  author  = {Mohammed Safi Ur Rahman Khan and Priyam Mehta and Ananth Sankar and Umashankar Kumaravelan and Sumanth Doddapaneni and Suriyaprasaad G and Varun Balan G and Sparsh Jain and Anoop Kunchukuttan and Pratyush Kumar and Raj Dabre and Mitesh M. Khapra},
  year    = {2024},
  journal = {arXiv preprint arXiv: 2403.06350}
}