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agentic-ptb/grok-record
grok-record is a machine learning model from agentic-ptb. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for grok.
Non-weight artifacts for AgentPTB cell grok (pi / grok-4.6 @ effort xhigh). Checkpoints for this cell are separate repos named agentic-ptb/grok.h; the index is agentic-ptb/INDEX.
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Updated Aug 23, 2026
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From the Hugging Face model README
Non-weight artifacts for AgentPTB cell grok (pi / grok-4.6 @ effort xhigh).
Checkpoints for this cell are separate repos named agentic-ptb/grok.h*; the index is
agentic-ptb/INDEX.
| contents | |
|---|---|
driver-session/ | full driver trajectory — every event the agent emitted (1042 files) |
harness/ | the harness the cell proposed: skills, system prompt, submission manifest, configs, scripts |
RUNLOG.md | the arm's own narrative of what it tried and concluded |
WORKING_STATE.md, STATE.md | its persisted state — this, not the chat history, was its memory |
supervisor.jsonl | cycle boundaries, resumes, boots |
evals/ | eval logs for every panel it ran |
The driver ran 100 hours under a supervisor that restarted it each cycle. Cycle boundaries are
in supervisor.jsonl; resume:false means that cycle began a fresh thread and the agent
re-derived its situation from RUNLOG.md.
Scores in RUNLOG.md are the arm's own, measured with its own harness on its own sample —
sample sizes differ by an order of magnitude across cells, so they are not directly comparable.
Use them as the cell's account of itself, not as a cross-cell ranking.