saidutta69/odia_pretrain_dataset

Odia Pre-training Dataset

10.32 million rows of Odia text. Zero access requests. Zero waiting. Zero gating nonsense.

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The Origin Story (a.k.a. How a Pending Access Request Created a Monster)

It all started with a simple request: "Can I please access your Odia pretraining dataset?"

That was months ago. The access request is still pending.

So we did what any reasonable person would do when faced with institutional gatekeeping of a low-resource language's most important resource: we rebuilt the entire thing from scratch.

What began as a humble attempt to recreate a ~6M row dataset has now ballooned into a **10.32M rows (merged Odia-Web-Corpus-v5)er tabs, downloads every publicly available Odia corpus on the internet, writes deduplication scripts at 3 AM, spins up cloud VMs that keep getting preempted, fights with sandboxes that timeout, battles upload size limits, and emerges with a dataset that is 63% larger than the one they were trying to access in the first place.

The original team wanted to gate access to protect their work. Instead, they inadvertently motivated the creation of a bigger, more diverse, and more openly accessible dataset. You're welcome.

Moral of the story: Gating your dataset doesn't protect it. It just makes someone build a better one out of spite.

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What's In This Beast

Metric	Value
Total Rows	10,316,629
Unique Sources	25+
License	CC-BY-4.0 (yes, commercially usable)
Access Required	None. Just download it.

Source Breakdown (all 25+ sources, because why stop at one)

Source	Rows	What It Is
indic_nlp_corp	3,122,796	IndicNLP Corpus - the backbone
odia_web_corpus_v5	3,340,338	Our own web scraping (news, instructions, everything)
varta	1,014,936	DailyHunt Odia news articles
samanantar	992,064	Parallel Odia-English sentences
xp3	486,529	BigScience multilingual parallel data
culturax	150,318	Cleaned web crawl
odia_qa	84,920	Odia question-answering
oscar_odia	50,092	OSCAR Odia subset
alpaca_odia	49,076	Odia instruction data
eng_to_odia	20,828	Translation pairs
wikipedia	17,210	Odia Wikipedia
dolly_odia	14,959	Odia Dolly data
gpt_teacher	18,184	GPTeacher Odia
odia_news	5,993	Common Crawl news
odia_lyrics	156	Because music is culture
+ 10 more	~100K	Various community contributions

What We Couldn't Get (Gated Datasets That Refused to Open)

Dataset	Rows	Status
oscar-corpus/OSCAR-2301	48,780	Applied. Waiting.
OdiaGenAIdata/pre_train_odia_data_processed	5,980,000	Applied. Still waiting.

If these ever get accepted, we'll merge them in too. Because apparently we can't stop.

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Quality

We didn't just dump everything into a bucket. We actually cleaned it.

Check	Result
Empty text	0
Odia content ratio	80.6% mean
Rows with >50% Odia	98.5%
Duplicate removal	805,532 rows removed
HTML tag cleanup	Done
Short text removal (<15 chars)	Done
Quality score	99.5/100

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Data Schema

Field	Type	Description
text	string	Odia text content
source	string	Where it came from
type	string	monolingual, parallel, instruction, qa, etc.
en_aligned	string	English translation (for parallel data)

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Quick Start

from datasets import load_dataset

# Just load it. No access form. No waiting. No emails.
dataset = load_dataset("saidutta69/odia_pretrain_dataset", split="train")

# Filter by source
news = dataset.filter(lambda x: x["source"] in ("varta", "odia_web_corpus_v5"))
instructions = dataset.filter(lambda x: x["type"] == "instruction")
parallel = dataset.filter(lambda x: x["source"] == "samanantar")

# Count by source
from collections import Counter
sources = Counter(x["source"] for x in dataset)
for src, count in sources.most_common():
    print(f"{src}: {count:,}")

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License

CC-BY-4.0 - Use it commercially. Use it for research. Use it to train a model that competes with OdiaGenAI. We don't gate things here.

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Acknowledgments

Special thanks to:

• OdiaGenAI for accidentally motivating this entire project through the power of a pending access request
• AI4Bharat for Samanantar and IndicNLP (openly accessible, unlike some)
• BigScience for xp3 and the multilingual parallel data
• DailyHunt/Varta for the news corpus
• Every Odia NLP researcher who contributed open datasets
• Coffee for keeping us awake during the 3 AM deduplication runs
• Cloud VMs for getting killed mid-push exactly when it hurt the most

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Citation

If this dataset helped your research, cite it:

@misc{odia_pretrain_dataset,
  author = {Saidutta Abhishek Dash},
  title = {Odia Pre-training Dataset: What Happens When You Gate a Low-Resource Language},
  year = {2025},
  publisher = {Hugging Face},
  note = {10.32M rows (merged Odia-Web-Corpus-v5) of Odia text, rebuilt from scratch because access requests went unanswered},
  howpublished = {\url{https://huggingface.co/datasets/saidutta69/odia_pretrain_dataset}},
}

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"They gated the data. We un-gated the language."