OpenVLA
SkillDev toolsUse when working on OpenVLA fine-tuning/serving/evaluation workbench stages, the OpenVLA-OFT LoRA recipe, or the npa workbench openvla CLI.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the OpenVLA skill
What this skill tells your AI
The instructions your AI receives, as published by nebius/nebius-physical-ai in skills/tools/openvla/SKILL.md and read by ahel’s review.
OpenVLA is the vision-language-action tool for fine-tuning, serving, and evaluating OpenVLA policies (OpenVLA-OFT recipe) in npa.
The three core stages (train, serve, eval) are currently stubs: they
expose the intended argument signatures but exit with a clear "not yet
implemented" message until the OpenVLA-OFT fine-tuning pipeline lands
(tracking issue nebius/nebius-physical-ai#500). The base model (default
openvla/openvla-7b) is resolved at runtime through the HF Hub cache via
npa.workbench.model_access — weights are never bundled in the repo or
image.
Interfaces
- CLI:
npa workbench openvla <train|serve|eval> --help - Python SDK:
npa.sdk.workbench.openvla(train,serve,eval) - Workflow module:
npa.workflows.byof.openvla_pipeline(argument validation, upstream argv planning, argparse entrypoint)
Conventions
- The CLI lives at
npa.cli.workbench.openvla(multi-command package form for new tools); the SDK surface lives atnpa.sdk.workbench.openvla. - The
trainstage is the headlineopenvla/trainthree-tier contract (CLI <-> SDK <->workflows/testing/openvla-train.yaml);serveandevalremain public-reusable sibling toolRefs.
Signals
- GitHub stars
- 30
- Forks
- 16
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
openvla- Source
- github.com/nebius/nebius-physical-ai