Agent skill · nvidia
tao-train-codetr
Co-DETR (CoDINO) for object detection. A DETR-family detector with collaborative hybrid
What it needs
About 10k tokens when loaded.
What this skill does
Co-DETR Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first (host preflight, credentials, cross-skill discovery). Co-DETR trains a DETR detector alongside auxiliary one-to-many assignment heads (numcoheads), which supervise the encoder more densely than DETR's one-to-one matching alone. The auxiliary heads exist only during training; inference runs the primary DETR head. Backbones are large by default — vitlargecodetr for training, swinlargepatch4window7224 for the reference inference/eval configs — so this is an accuracy-first model, not a latency-first one. Availability — probe, then fall back to the module The codetr console script is not registered in the TAO PyTorch images checked so far (7.0.1-pyt and the 2026.7.31-rc-12-multiarch nightly), even though the module itself ships. So a bare codetr invocation fails while the network is perfectly usable. Probe in two steps and use whichever works: Both forms take identical arguments — the module entrypoint reports itself as codetr and exposes the same {train, evaluate, inference, defaultspecs} subtasks. Substitute $CODETR wherever this document writes codetr. Only if both probes fail does this image genuinely lack Co-DETR. Then stop and ask which image to use — do not silently substitute another detector. Dataclass Schemas Generated TAO Core schemas are not yet packaged for this model, so schemas/<action>.schema.json and references/spectemplate<action>.yaml are absent except for the hand-written references/spectemplateinference.yaml. Read spec keys from the upstream experiment specs in nvidiataopytorch/cv/codetr/experimentspecs/ (train.yaml, eval.yaml, inference.yaml, export.yaml) until a maintainer regenerates them. AutoML is therefore not runnable for this model. Train Action Policy This model is not AutoML-enabled (automlenabled: false in references/skillinfo.yaml). Run train directly; do not route through tao-skill-bank:tao-run-automl. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/tao-train-codetr