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.gitignore
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README.md
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---
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license: cc-by-4.0
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task_categories:
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- text-generation
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language:
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- as
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- bn
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tags:
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- language-modeling
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- casual-lm
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- llm
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pretty_name: sangraha
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dataset_info:
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configs:
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- config_name: verified
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size_categories:
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- 100B<n<1T
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---
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# Sangraha
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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.
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**Coming Soon**:
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- Sangraha Synthetic - Translated and Romanised English Wikimedia data.
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- Sangraha Verified - Hindi YouTube transcribed data.
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- Check out the scraping and cleaning pipelines used to curate Sangraha [on GitHub](https://github.com/AI4Bharat/IndicLLMSuite);
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## Getting Started
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You can download the dataset using Hugging Face datasets:
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```python
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from datasets import load_dataset
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```
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## Background
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Sangraha contains three broad components:
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- **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.
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- **Sangraha Unverfied**: High quality Indic language data extracted from existing multilingual corpora employing perplexity filtering using n-gram language models trained on Sangraha Verified.
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- **Sangraha Synthetic**: WikiMedia English translated to 14 Indic languages and further "romanised" from 14 languages by transliteration to English.
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## Data Statistics
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| **Lang Code** | **Verified**
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| asm
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| ben
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| brx
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| doi
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| eng
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| gom
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| guj
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| hin
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| kan
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| kas
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| mai
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| mal
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| mar
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| mni
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| npi
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| ori
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| pan
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| san
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| sat
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| snd
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| tam
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| urd
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| tel
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| **Total**
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To cite Sangraha, please use:
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```
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@misc{khan2024indicllmsuite,
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title={IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages},
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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},
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year={2024},
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eprint={2403.06350},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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-
```
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---
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license: cc-by-4.0
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task_categories:
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4 |
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- text-generation
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5 |
language:
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6 |
+
- as
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7 |
+
- bn
|
8 |
+
- gu
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9 |
+
- en
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10 |
+
- hi
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+
- kn
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+
- ks
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+
- ml
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+
- mr
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+
- ne
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16 |
+
- or
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17 |
+
- pa
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18 |
+
- sa
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+
- sd
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+
- ta
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+
- te
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+
- ur
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tags:
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+
- language-modeling
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25 |
+
- casual-lm
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26 |
+
- llm
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pretty_name: sangraha
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dataset_info:
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- config_name: verified
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features:
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- name: doc_id
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dtype: string
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- name: type
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dtype: string
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- name: text
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dtype: string
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splits:
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- name: asm
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- name: ben
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- name: brx
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- name: doi
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- name: eng
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- name: gom
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- name: guj
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- name: hin
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- name: kan
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- name: kas
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- name: mai
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- name: mal
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- name: mar
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- name: mni
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- name: nep
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- name: ori
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- name: pan
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- name: san
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- name: sat
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- name: snd
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- name: tam
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- name: tel
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- name: urd
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- config_name: unverified
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features:
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- name: doc_id
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dtype: string
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- name: text
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dtype: string
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splits:
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- name: asm
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- name: ben
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- name: guj
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- name: hin
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- name: nep
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- name: ori
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- name: pan
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- name: san
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- name: tam
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- name: tel
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- name: urd
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configs:
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- config_name: verified
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data_files:
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- split: asm
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path: verified/asm/asm.*
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- split: ben
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path: verified/ben/ben.*
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path: verified/brx/brx.*
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- split: doi
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path: verified/doi/doi.*
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- split: eng
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path: verified/eng/eng.*
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- split: gom
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path: verified/gom/gom.*
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- split: guj
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path: verified/guj/guj.*
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- split: hin
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path: verified/hin/hin.*
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- split: kan
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path: verified/kan/kan.*
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- split: kas
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path: verified/kas/kas.*
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- split: mai
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path: verified/mai/mai.*
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- split: mal
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path: verified/mal/mal.*
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- split: mar
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path: verified/mar/mar.*
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- split: mni
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path: verified/mni/mni.*
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- split: nep
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path: verified/nep/nep.*
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- split: ori
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path: verified/ori/ori.*
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- split: pan
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path: verified/pan/pan.*
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path: verified/san/san.*
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path: verified/urd/urd.*
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data_files:
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- split: asm
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path: unverified/asm/asm.*
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- split: ben
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path: unverified/ben/ben.*
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- split: guj
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path: unverified/guj/guj.*
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- split: hin
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path: unverified/hin/hin.*
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- split: kan
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path: unverified/kan/kan.*
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- split: mal
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path: unverified/mal/mal.*
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- split: mar
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path: unverified/mar/mar.*
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- split: nep
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path: unverified/nep/nep.*
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- split: ori
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path: unverified/ori/ori.*
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- split: pan
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path: unverified/pan/pan.*
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- split: san
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path: unverified/san/san.*
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- split: tam
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path: unverified/tam/tam.*
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- split: tel
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path: unverified/tel/tel.*
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- split: urd
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path: unverified/urd/urd.*
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size_categories:
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- 100B<n<1T
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---
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|
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# Sangraha
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|
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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.
|
172 |
|
173 |
**Coming Soon**:
|
174 |
+
|
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- Sangraha Synthetic - Translated and Romanised English Wikimedia data.
|
176 |
- Sangraha Verified - Hindi YouTube transcribed data.
|
177 |
|
|
|
181 |
- Check out the scraping and cleaning pipelines used to curate Sangraha [on GitHub](https://github.com/AI4Bharat/IndicLLMSuite);
|
182 |
|
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## Getting Started
|
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+
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You can download the dataset using Hugging Face datasets:
|
186 |
+
|
187 |
```python
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from datasets import load_dataset
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|
|
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```
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|
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## Background
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+
|
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Sangraha contains three broad components:
|
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+
|
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- **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.
|
198 |
- **Sangraha Unverfied**: High quality Indic language data extracted from existing multilingual corpora employing perplexity filtering using n-gram language models trained on Sangraha Verified.
|
199 |
- **Sangraha Synthetic**: WikiMedia English translated to 14 Indic languages and further "romanised" from 14 languages by transliteration to English.
|
200 |
|
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## Data Statistics
|
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|
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+
| **Lang Code** | **Verified** | **Synthetic** | **Unverified** | **Total Tokens (in Millions)** |
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| ------------- | ------------ | ------------- | -------------- | ------------------------------ |
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| asm | 292.1 | 11,696.4 | 17.5 | 12,006.0 |
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| ben | 10,604.4 | 13,814.1 | 5,608.8 | 30,027.5 |
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| brx | 1.5 | - | - | 1.5 |
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| doi | 0.06 | - | - | 0.06 |
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| eng | 12,759.9 | - | - | 12,759.9 |
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| gom | 10.1 | - | - | 10.1 |
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| guj | 3,647.9 | 12,934.5 | 597.0 | 17,179.4 |
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| hin | 12,617.3 | 9,578.7 | 12,348.3 | 34,544.3 |
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| kan | 1,778.3 | 12,087.4 | 388.8 | 14,254.5 |
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| kas | 0.5 | - | - | 0.5 |
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| mai | 14.6 | - | - | 14.6 |
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| mal | 2,730.8 | 13,130.0 | 547.8 | 16,408.6 |
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| mar | 2,827.0 | 10,816.7 | 652.1 | 14,295.8 |
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| mni | 7.4 | - | - | 7.4 |
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| npi | 1,822.5 | 10,588.7 | 485.5 | 12,896.7 |
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| ori | 1,177.1 | 11,338.0 | 23.7 | 12,538.8 |
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+
| pan | 1,075.3 | 9,969.6 | 136.9 | 11,181.8 |
|
222 |
+
| san | 1,329.0 | 13,553.5 | 9.8 | 14,892.3 |
|
223 |
+
| sat | 0.3 | - | - | 0.3 |
|
224 |
+
| snd | 258.2 | - | - | 258.2 |
|
225 |
+
| tam | 3,985.1 | 11,859.3 | 1,515.9 | 17,360.3 |
|
226 |
+
| urd | 3,658.1 | 9,415.8 | 1,328.2 | 14,402.1 |
|
227 |
+
| tel | 3,706.8 | 11,924.5 | 647.4 | 16,278.7 |
|
228 |
+
| **Total** | **64,306.1** | **162,707.9** | **24,307.7** | **251,321.0** |
|
|
|
229 |
|
230 |
To cite Sangraha, please use:
|
231 |
|
232 |
```
|
233 |
@misc{khan2024indicllmsuite,
|
234 |
+
title={IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages},
|
235 |
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},
|
236 |
year={2024},
|
237 |
eprint={2403.06350},
|
238 |
archivePrefix={arXiv},
|
239 |
primaryClass={cs.CL}
|
240 |
}
|
241 |
+
```
|
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