This wraps the official OpenVLA-OFT fine-tuning workflows for adapting vision-language-action models to robot tasks. You're getting LoRA-based fine-tuning pipelines and eval scripts for the LIBERO benchmark, which tests manipulation skills across different task suites. The quick start points you straight at evaluating a pretrained checkpoint on LIBERO spatial tasks with 50 trials per task. It's built for researchers doing embodied AI work who need to adapt OpenVLA's continuous action prediction for their own robot setups. The repo setup assumes you're comfortable cloning research codebases and running Python eval scripts. Three security audits show mostly green with one Snyk warning to check.
npx -y skills add orchestra-research/ai-research-skills --skill fine-tuning-openvla-oft --agent claude-codeInstalls into .claude/skills of the current project.
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