feat(benchmarks): add LIBERO training benchmark pipeline#3337
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feat(benchmarks): add LIBERO training benchmark pipeline#3337
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Single-script benchmark that trains and evaluates all 9 LeRobot policies on LIBERO. Each SLURM job self-publishes its result row to a HuggingFace leaderboard dataset — no separate collection step needed. Policies: pi0, pi0_fast, pi05, groot, act, diffusion, smolvla, xvla, multi_task_dit. 5000 steps, BS 256, with per-policy GPU allocation and default LR/scheduler presets. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
Test plan
collect_results.pyon completed outputs🤖 Generated with Claude Code