Datasets:

Maxyelow
/

kenyan-code-switch-1m

language:
  - sw
  - en
  - swh
license: apache-2.0
tags:
  - kenya
  - code-switching
  - sheng
  - swahili
  - pretraining
  - 1m-corpus
  - language-modeling
size_categories:
  - 1M<n<10M

🇰🇪 Kenyan Code-Switching Pretraining Corpus (1,000,000 Sentences / 16.99M Words)

The largest standardized, rule-audited monolingual pretraining corpus for Kenyan Code-Switching (Sheng / Technical Swahili-English Blend).

Corpus Statistics

Total Sentences: 1,000,000 sentences
Total Word Tokens: 16,990,653 words
Average Sentence Length: 16.99 words (multi-clause explanatory syntax)
Linguistic Audit Score: 100.0000% compliance across all 20 Master Blueprint rules
Raw Text Size: 113.3 MB (.txt)
Metadata JSONL Size: 203.6 MB (.jsonl)

Domains Represented

Engineering & Infrastructure: Structural analysis, shear stress, electrical transformers, hydraulics, concrete rebar.
Finance & FinTech: M-Pesa, SACCOs, Central Bank of Kenya inflation, collateral liquidation, loan underwriting.
Tech & Software Systems: Microservices, Redis caching, Kubernetes deployment, API gateway authentication, CI/CD pipelines.
Medicine & Healthcare Sciences: Emergency triage, acute respiratory intubation, targeted antibiotics, pathology.
Politics & Constitutional Governance: Katiba 2010 public participation, bicameral parliament, gubernatorial impeachment, fiscal policy.

Usage

from datasets import load_dataset

dataset = load_dataset("text", data_files={"train": "kenyan_code_switch_corpus_1m.txt"})

Citation

@dataset{kenyan_code_switch_1m_2026,
  title={Kenyan Code-Switching 1M Pretraining Corpus},
  author={Maxwell Ng'ang'a},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/Maxyelow/kenyan-code-switch-1m}
}