nahidstaq/bangla-llm-data

Bangla NLP Text Corpus — 800K+ Bangla Text Samples for LLM Training and NLP Research

The largest open, multi-domain Bangla text dataset, combining 801,645 samples from 15 different sources — newspapers, social media, education, reviews, QA, medical, poetry, and more. Ready for Bangla LLM pretraining, fine-tuning, and downstream NLP tasks.

Why This Dataset?

Bangla (Bengali) is the 7th most spoken language in the world with 230M+ speakers, but high-quality Bangla NLP datasets are scarce and scattered. This collection brings together cleaned, deduplicated text from diverse domains into a single, easy-to-use dataset with a consistent schema.

Good for:

• Bangla LLM pretraining and continued pretraining
• Bangla text classification (sentiment, emotion, sarcasm)
• Bangla language modeling and perplexity evaluation
• Bangla NER, POS tagging, and other token-level tasks
• Bangla RAG pipelines and semantic search indices
• Bangla text generation fine-tuning
• Cross-lingual transfer learning (Bengali-English)

Dataset Overview

Source	Samples	Domain	Description
potrika_newspaper	326,988	News	Bangla newspaper articles from Potrika
addressacademy	292,919	General	Diverse Bangla text corpus
facebook_sentiment	40,146	Social Media	Facebook posts with sentiment
dataset_csv	35,421	Mixed	Assorted Bangla text
bangla_sarcasm	23,592	Social Media	Sarcasm-labeled Bangla text
bangla_emotion	19,371	Social Media	Emotion-labeled Bangla text
restaurant_reviews	15,684	Reviews	Bangla restaurant reviews
youtube_sentiment	11,783	Social Media	YouTube comment sentiment
nctb	11,257	Education	NCTB Bangladesh textbook content
tydiqa_bengali	10,768	QA	Bengali question-answering pairs
bangla_telecom	6,546	Telecom	Telecom domain Bangla text
reddit	5,605	Social Media	Reddit Bangla posts
deshimula	897	Reviews	Deshimula Bangla reviews
bengali_medical	658	Medical	Bengali medical text
bengali_poetry	10	Literature	Bengali poetry

Total: 801,645 samples across 15 sources

Schema

Every row follows the same JSON structure:

{
  "text": "বাংলাদেশের অর্থনীতি দ্রুত বৃদ্ধি পাচ্ছে...",
  "source": "potrika_newspaper",
  "meta": {}
}

Field	Type	Description
text	string	The Bangla text content
source	string	Origin dataset/domain (see table above)
meta	object	Optional metadata (labels, categories, etc.)

Quick Start

from datasets import load_dataset

# Load full dataset
ds = load_dataset("nahidstaq/bangla-llm-data")
print(f"Total samples: {len(ds['train'])}")  # 801,645

# Filter by domain
news = ds["train"].filter(lambda x: x["source"] == "potrika_newspaper")
sentiment = ds["train"].filter(lambda x: x["source"] in ["facebook_sentiment", "youtube_sentiment"])
education = ds["train"].filter(lambda x: x["source"] == "nctb")

# Get all unique sources
sources = set(ds["train"]["source"])
print(sources)

Sample Texts

News (potrika_newspaper):

রাজধানী ঢাকায় আজ সকাল থেকেই ভারি বৃষ্টিপাত হচ্ছে। আবহাওয়া অধিদপ্তর জানিয়েছে...

Social Media (facebook_sentiment):

ভাই এই ফোনটা কিনে ভুল করেছি, ক্যামেরা একদম খারাপ 😡

Education (nctb):

বাংলাদেশ দক্ষিণ এশিয়ার একটি দেশ। এর রাজধানী ঢাকা। বাংলাদেশের মোট আয়তন...

Restaurant Review (restaurant_reviews):

খাবারের মান ভালো ছিল কিন্তু সার্ভিস একটু ধীর গতির

Medical (bengali_medical):

ডায়াবেটিস রোগীদের নিয়মিত রক্তে শর্করার মাত্রা পরীক্ষা করা উচিত

Related Resources

• nahidstaq/bangla-transliteration — Roman to Bangla transliteration model (9.18% CER)
• nahidstaq/bge-m3-bangla — Cross-script Bangla semantic search model
• nahidstaq/bangla-transliteration-data — Bangla transliteration pairs

Credits

Collected and curated by Md Nahid Hasan (@nahidstaq | nahidscript.com).

Individual sources retain their original licenses. This collection is released under MIT for the curation and aggregation work.

Citation

@misc{bangla-llm-data,
  author = {Hasan, Md Nahid},
  title = {Bangla LLM Data: 800K+ Multi-Domain Bangla Text Corpus},
  year = {2025},
  url = {https://huggingface.co/datasets/nahidstaq/bangla-llm-data},
  note = {Curated multi-source Bangla text dataset for LLM training and NLP research}
}