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LANA-Code-Qwen3.8-Distill
Verified code supervised fine-tuning data distilled from Qwen3.8-27B by the LANA-research data engine, one config per data source (the source of the prompt). Every row is one teacher response that passed automatic verification, in the canonical slf-sft-v1 schema with full provenance.
Verification: the extracted Python program passes the task's tests in a sandbox (timeout 6 s, 4 GB, float tol 1e-6); tests are in code_tests/ (gzip JSON), referenced by reference.tests_ref.
producer.stage/producer.modeidentify the sampling stage and thinking mode.
Subsets (one per source)
| config | source dataset | train | validation |
|---|---|---|---|
nano_rl_blend_comp_coding |
nvidia/Nemotron-3-Nano-RL-Training-Blend:nano_v3_sft_profiled_comp_coding_50tests | 4,213 | 44 |
code_contests |
nvidia/Nemotron-RL-coding-competitive_coding:code_contests | 2,748 | 20 |
codeforces |
nvidia/Nemotron-RL-coding-competitive_coding:open-r1/codeforces | 2,067 | 10 |
Total: 9,102 rows. validation is a 1% hold-out by question_hash.
Loading
from datasets import load_dataset
ds = load_dataset("LANA-research/LANA-Code-Qwen3.8-Distill", "nano_rl_blend_comp_coding", split="train")
row = ds[0]; prompt = row["messages_in"]; target = (row["reasoning"], row["response"])
Fields
Schema slf-sft-v1 (31 fields): identity (uid, family, family_version, domain, task_type, language); input (messages_in, tools, problem_text, question_hash, source_dataset, source_id, source_split, license, seed_pool, difficulty); reference (kind, answer, choices, tests_ref, constraints, gold_source); producer (teacher model, serving, mode, sampling, stage, sample index); gen_run (client, hash, time); target (reasoning = text inside <think>, response = visible answer, finish_reason, n_tokens); verify (method, version, passed, score, details); accepted (always true here), reject_reason, flags, decontam (method, checked_against, hit), split, meta (JSON).
Decontamination: exact + 13-gram checks of the prompt against MATH-500, GPQA-Diamond, IFEval, MMLU-Pro, LiveCodeBench v6, OJBench and other evaluation inputs (per-row record in decontam).
License
Mixed: each row's license field gives the license of its prompt source; responses were generated with Qwen3.8-27B.
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