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docs(g05): record real training smoke
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@@ -173,6 +173,11 @@ uv run pytest tests/policies/g05 tests/runtime/test_g05_adapter.py -q
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uv run ruff check src/lerobot/policies/g05 tests/policies/g05
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```
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An RTX 5090 smoke test loaded the real private `g05_libero` checkpoint and
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completed a batch-size-one BF16 forward, backward, gradient clip, and AdamW
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step. It produced finite loss `2.77356`, finite pre-clip gradient norm `54.38`,
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all six author optimizer groups, and 23.59 GiB peak allocated CUDA memory.
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A 50-episode LIBERO/RoboTwin success-rate comparison additionally requires the
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matching simulator, task assets, reset seeds, and author evaluator; no task-level
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benchmark number is claimed until that separate gate runs.
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