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tao-run-deft-pas

Run iterative improvement for NVIDIA TAO CLIP / SigLIP image-text retrieval on attribute-labelled data. Use when a request combines retrieval evaluation, weak-attribute or caption-pair mining, repeated retraining, and a stopping condition based on a retrieval KPI, validation plateau, or iteration budget; the customer need not know the DEFT or People Attribute Search (PAS) names. The self-contained workflow performs dataset preparation, zero-shot evaluation, attribute gap analysis, caption-space k-NN mining, history-aware selection, retraining, and re-evaluation. Treat `tao-deft-pas` as shorthand for this canonical `tao-run-deft-pas` workflow. Do not use for standalone CLIP training, one-off evaluation or embedding, generic k-NN mining, or AOI/ChangeNet DEFT workflows.

skills/tao-run-deft-pas/SKILL.md

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Nov 6, 2026
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Apache-2.0

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# PAS DEFT Workflow

> **Standalone install?** If this session was not initialized by the TAO skill
> bank plugin, run the `tao-setup` skill first for host preflight, credential
> checks, and cross-skill discovery.

Run the canonical PAS flow as one resumable, disk-backed workflow. All PAS
workflow logic, templates, and host adapters ship with this skill; customers do
not need a separate source checkout. The bundled scripts make stage calls
deterministic without adding another orchestration layer.

This skill supports every packaged TAO execution platform: Docker, SLURM,
Kubernetes, Brev, and virtualenv. The workflow produces a platform-neutral,
schema-validated action bundle; the selected platform skill owns native