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Datasets:
WithinUsAI
/
Genesis_AI_Code_10k

Tasks:
Text Generation
Question Answering
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
Tags:
within-us-ai
genesis
code
agentic
reasoning
tool-calling
Libraries:
Datasets
Dask
Polars
License:
Dataset card Data Studio Files
xet
 Community

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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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