Datasets:
TermiGen v2
Dataset stats
- Tasks: 3,566 original; 3,336 in v1; 2,277 kept in v2, all previously patched. 1,059 v1 tasks have no recorded successful attempt; 230 earlier exclusions remain in v1.
- Images: reuse v1 environments and its cached images as they become available. No additional images or task repairs in v2.
Dataset characteristics
TermiGen supplies terminal tasks with prepared files and executable verifiers.
Domains
Software Engineering, Debugging, System Administration, Security, Data Processing, Scientific Computing and Machine Learning: repair code, diagnose services, inspect artifacts and configure computational workflows.
Capabilities
Exploration, Error Recovery and Specification Adherence; specialized tasks also involve Reverse Engineering and Adversarial Reasoning. Labels follow CLI-Universe.
Intended benchmark transfer: terminal problem solving for Terminal-Bench; debugging and environment diagnosis for repository-based software engineering.
Selection
Keep tasks with at least one recorded reward of 1 from either model, with four attempts per task and model.
| Model | Tasks solved at least once |
|---|---|
| Qwen3-Coder-30B-A3B-Instruct | 2,123 / 3,336 |
| Qwen3-30B-A3B-Instruct-2507 | 1,850 / 3,336 |
| Either model | 2,277 / 3,336 |
All 3,336 evaluated task hashes match v1. V2 preserves task payloads exactly. Build, no-op and rule-based checks carry over from v1; no reference solutions are provided.
Missing rewards remain unknown, not failures (142 Coder attempts and 179 Instruct attempts). Excluded tasks are those without a recorded success, not confirmed defective tasks.
Successful attempts among kept tasks
| Instruct successes out of 4 | Tasks |
|---|---|
| 0 | 427 |
| 1 | 417 |
| 2 | 359 |
| 3 | 421 |
| 4 | 653 |
Per-task Coder evidence establishes whether a task was solved; exact per-task success counts are not available in the published report, so they are not inferred.
Files and selecting tasks
tasks.parquet contains kept tasks, coder_solved, instruct_successes, instruct_missing_rewards and attempts_per_model. metadata/selection.json records every v1 task's selection and pins the source revision. Excluded payloads remain in that v1 revision; no duplicate archive Parquet is uploaded. patch.py reproduces this selection.
import pyarrow.parquet as pq
subset = pq.read_table("tasks.parquet", filters=[("instruct_successes", "=", 1)])
pq.write_table(subset, "selected.parquet", compression="zstd")
Saved teacher trajectories from PR #20 are available in traces/, with coverage and provenance in traces/manifest.json. The 70 Parquet shards contain 26,688 attempt records from both models across all 3,336 evaluated v1 tasks. Filter retained_v2 == True for the 2,277 tasks kept in v2. The manifest records 64 missing trajectories and 321 ungraded attempts; missing raw verifier rewards remain null. It also documents missing-reward metadata discrepancies for 103 tasks.
Runtime
Apptainer 1.5.4, Python 3.12.7 / 3.12.14, Harbor 0.8.1; Marin Harbor bridge and runtime patches. Teacher runs used Terminus 2; recorded model results.