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Nepali LLM Datasets

This repository contains two configurations of Nepali LLM datasets:

Configurations

1. Scrapy Engine

  • Description: Contains data collected using a web scraping engine.
  • Files: [List any specific files or formats]

2. Nepberta

  • Description: This dataset is derived from the Nepberta project and contains cleaned data specifically related to the project. The dataset contains **cleaned text chunks of size ~50 mb ** of all articles into a single giant string, with each article ending in <|endoftext|>. This long string is then segmented into chunks, each approximately 500 MB in size.
  • Files: contains 23 files each ~500Mb (chunk_1.txt, chunk_2.txt, ... chunk_23.txt)
  • split:train
    • files: chunk_1.txt to chunk_18.txt
  • split:test
    • files: chunk_19.txt to chunk_23.txt

Usage

To load the datasets:

# it loads entire dataset first
from datasets import load_dataset

# Load nepberta configuration
nepberta_dataset = load_dataset("Aananda-giri/nepali_llm_datasets", name="nepberta", split='train') # use `streaming=True` to avoid downloading all the dataset

# length of chunks
len(nepberta_train['text']) # 18 : number of chunks
len(nepberta_train['text'][0])  # length of large text equivalent to 500 MB text

# use streaming=True to avoid downloading entire dataset
nepberta_train = load_dataset("Aananda-giri/nepali_llm_datasets", name="nepberta", streaming=True)['train']

# using next
next(iter(nepberta_train))

# using for loop
for large_chunk in nepberta_train:
  pass
  # code to process large_chunk['text']

# Load scrapy engine data
scrapy_train = load_dataset("Aananda-giri/nepali_llm_datasets", name="scrapy_engine" split="train")
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