datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
kenyan-Edu-blindspot-eval
Kenyan Educational Blind Spot Evaluation
Model: Qwen/Qwen2.5-1.5B-Instruct (1.54B)Author: Walter OnyangoContext: Fatima Institute for Global AI Research Fellowship application
1. The Blind Spot
From my experience studying Computer Science in Kenya and building tools such as UAMAS (an AI-assisted assessment system) and a text-simplification extension used by real learners, I repeatedly observed that current models struggle with:
East-African local knowledge… See the full description on the dataset page: https://huggingface.co/datasets/waltertaya/kenyan-Edu-blindspot-eval.kenya-bee-health-qa-image-triples
Kenya Bee Health Training Data
This folder is a starter database for BeeCare Anywhere / Gemma Apiary. It is intentionally small, transparent, and license-aware: use it to prove the Q/A/image-triple pipeline, then expand it with Kenyan field data before trusting model behavior in production.
Important Model Note
google/gemma-2b is a text-to-text, decoder-only model. It cannot directly read pictures. Use these image triples with a vision-capable model path, for… See the full description on the dataset page: https://huggingface.co/datasets/yahelr1/kenya-bee-health-qa-image-triples.kenya-court-submissions-qa
Kenya Court Submissions Q/A (HC/CA/SC) — Esheria
BLUF: 15,000 Kenya-only Q/A pairs engineered for training models to draft court-ready submissions for the High Court, Court of Appeal, and Supreme Court. Each answer uses a rigid advocacy spine: BLUF → Governing Rules → Controlling Holdings → Application → Relief Sought. Side-aware, doctrine-dense, and fit-for-purpose.
Why this dataset exists
Most “legal” datasets collapse into generic essays or foreign-law citations.… See the full description on the dataset page: https://huggingface.co/datasets/esherialabs/kenya-court-submissions-qa.kenyan_national_parks