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name: model-frameworks description: "Choose and inspect StarVLA model frameworks, registry names, baseframework APIs, action heads, backbones, checkpoint compatibility, and safe model-level smoke plans." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

StarVLA model frameworks

Use this sub-skill when the task is to choose, identify, inspect, or debug a StarVLA model family or framework config. It covers VLM4A, VM4A, and WM4A framework names, the baseframework contract, action-head/backbone compatibility, checkpoint config overrides, and safe model-level smoke planning.

Start here

1. For a framework choice or registry-name question, read references/model-families.md.
2. For API, checkpoint, config override, or from_pretrained questions, read references/framework-api.md.
3. For backbone/action-head/dimension compatibility, read references/action-heads-and-backbones.md.
4. For errors, read references/troubleshooting.md and then the root troubleshooting reference when install or backend issues are cross-cutting.
5. To inspect an installed StarVLA environment without loading model weights, run scripts/inspect_framework_registry.py.

Safe operating pattern

• Prefer config/registry inspection before model construction. Listing the registry or reading framework.name never needs checkpoint downloads.
• Instantiate a model only after confirming the requested framework key, VLM/world-model weight location, action/state dimensions, action horizon, backend, and download policy.
• Treat framework source __main__ demos as reference-only unless the user explicitly allows pretrained-weight access and the required GPU/accelerator setup.
• framework.name is the current build selector. Older docs or scripts may contain stale names such as framework.framework_py; translate to framework.name before using build_framework.

Route elsewhere

• Training launcher, optimizer, Accelerate/DeepSpeed, freezing, and LR-group details: training-config.
• Dataset registry, LeRobot data layout, data_mix, modality.json, and statistics ownership: data-integration.
• Policy servers, clients, unnorm_key, and served action response contracts: policy-deployment.
• Benchmark simulator environments and two-terminal evaluation plans: benchmark-evaluation.