Genesis AI Code (DataSets)
Collection
Frontier-grade datasets for agentic, reasoning-driven AI software engineering.
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Genesis AI Code 10K
Developed by: Within Us AI
Foundation dataset emphasizing tests-as-truth, agentic loops, and evaluation thinking.
Splits
- train: 9,800
- validation: 200
Highlights
- Tests-as-truth supervision patterns
- Diff-first patching
- Agentic loops (plan→edit→test→reflect) with bounded budgets
- Tool-call trace supervision (where present)
- Governance/audit & policy-gate awareness
Storage format
Parquet unavailable (No module named 'pyarrow'); JSONL shards in /data.
Quick start
from datasets import load_dataset
ds = load_dataset("<YOUR_ORG_OR_USER>/Genesis AI Code 10K", split="train")
print(ds[0])
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