README.md

metadata

license: odc-by
task_categories:
  - text-generation
language:
  - en
size_categories:
  - 1M<n<10M
tags:
  - diverse
  - curated
  - deduplication
  - multi-domain
  - stem
  - legal
  - scientific
  - encyclopedic
  - source-text
configs:
  - config_name: default
    data_files:
      - split: train
        path: cot_diverse_2.5m.parquet
pretty_name: Diverse Source Text Dataset (2.5M)
dataset_info:
  features:
    - name: text
      dtype: string
    - name: id
      dtype: string
    - name: url
      dtype: string
    - name: source
      dtype: string
    - name: quality_score
      dtype: float64
  splits:
    - name: train
      num_examples: 2500000

Diverse Source Text Dataset (2.5M)

A curated, deduplicated, multi-domain English text dataset blending 7 sources across STEM, legal, scientific, encyclopedic, Q&A, and general knowledge domains. Designed as high-quality, diverse source material for downstream NLP tasks such as synthetic data generation, fine-tuning, and text analysis.

Dataset Summary

Total samples	2,500,000
Estimated tokens	~2.8B (GPT-2) / ~2.4B (modern tokenizers)
Language	English
Format	Parquet (ZSTD compressed)
File size	4.28 GB
Text length	200 - 50,000 characters
Mean length	4,656 characters (~1,107 tokens)
Median length	2,439 characters

Source Breakdown

Source	Samples	Share	Avg Chars	Avg Tok/Doc	Quality Score	Domain
FineWeb EDU (broad, 3.0-4.0)	750,000	30%	4,997	1,063	3.39	General educational
DCLM-baseline	500,000	20%	2,295	572	0.89	Commonsense / explanatory
FineWeb EDU (high, >= 4.0)	375,000	15%	4,923	1,023	4.18	STEM / high-quality educational
Pile - FreeLaw	250,000	10%	14,458	3,781	N/A	Legal (court opinions, filings)
Pile - PubMed Abstracts	250,000	10%	1,335	292	N/A	Biomedical / scientific
Pile - StackExchange	200,000	8%	2,190	761	N/A	Technical Q&A
Pile - Wikipedia (en)	175,000	7%	2,923	685	N/A	Encyclopedic

Schema

text:           string   # The document text (200-50,000 chars)
id:             string   # Unique document identifier from source
url:            string   # Source URL (null for Pile sources)
source:         string   # One of 7 source labels
quality_score:  float64  # Source-specific quality score (null for Pile sources)

Methodology

Collection

• FineWeb EDU: Streamed from HuggingFaceFW/fineweb-edu across 12 Common Crawl dumps, filtered by educational quality score
• DCLM-baseline: Streamed from mlfoundations/dclm-baseline-1.0 with fasttext quality score >= 0.65
• Pile subsets: Streamed from monology/pile-uncopyrighted, filtered by subset name

Filtering

• Minimum 200 characters, maximum 50,000 characters
• 20% over-fetch to absorb deduplication losses

Deduplication (3-stage)

1. Exact text dedup: MD5 hash of normalized text (lowercased, whitespace-collapsed) - removed 70,433 (2.3%)
2. URL dedup: Normalized URL matching - removed 19,283
3. Near-dedup (anchor pairs): Three passes using MD5 hashes of text start/mid/end 500-char anchors - removed 3,353

Total removed: 93,069 / 3,000,000 (3.1%)

Final Assembly

• Each source trimmed to exact target count, prioritizing highest quality scores
• Globally shuffled via deterministic hash (seed=42)
• Written as single Parquet file with ZSTD compression

Usage

from datasets import load_dataset

ds = load_dataset("blythet/diverse-2.5m", split="train")
print(ds)
# Dataset({
#     features: ['text', 'id', 'url', 'source', 'quality_score'],
#     num_rows: 2500000
# })

# Filter by source
stem = ds.filter(lambda x: x["source"] == "fineweb_edu_high")

# Filter by quality
high_quality = ds.filter(lambda x: x["quality_score"] is not None and x["quality_score"] >= 4.0)

Intended Use

This dataset provides high-quality, diverse English text suitable for:

• Synthetic data generation (e.g., chain-of-thought, instruction tuning)
• Fine-tuning language models across multiple domains
• Text analysis and NLP research
• Domain-specific data extraction (legal, scientific, educational, technical)

The domain diversity covers STEM, legal reasoning, scientific literature, technical Q&A, encyclopedic knowledge, and general commonsense explanations.

Limitations

• Quality scores are only available for FineWeb EDU and DCLM sources; Pile subsets have null quality scores
• URLs are only available for FineWeb EDU and DCLM sources
• Text is English-only
• The dataset inherits any biases present in the upstream sources

License

This dataset is released under ODC-By (Open Data Commons Attribution License), consistent with the upstream source licenses:

• FineWeb EDU: ODC-By
• DCLM-baseline: ODC-By
• Pile (uncopyrighted subsets): Public domain / permissive

Citation

@dataset{diverse_2.5m,
  title={Diverse Source Text Dataset},
  author={blythet},
  year={2025},
  url={https://huggingface.co/datasets/blythet/diverse-2.5m},
  note={2.5M curated, deduplicated multi-domain English texts}
}