Agent skill · NVIDIA
nemo-automodel-model-onboarding
Guide for onboarding new model architectures into NeMo AutoModel, including architecture discovery, implementation patterns, registration, and validation.
What it needs
About 10k tokens when loaded.
What this skill does
Adding Model Support to NeMo AutoModel Purpose This skill guides implementation of new model architectures in NeMo AutoModel. Follow the five phases in order. <!-- NVSkills signature refresh requested after PR #2998 (2026-07-31). --> Instructions When answering an onboarding question, keep the response in this order: 1. Classify the architecture from config.json. 2. Name the exact implementation files under components/models/<name>/. 3. Identify registry and optional custom-config updates. 4. State the validation tests that must be added before full checkpoint use. For conceptual onboarding questions, answer from this skill without opening the pattern files unless the user asks you to edit code. Mention pattern filenames as references, then give the direct checklist. Use direct action verbs: classify the model, name the files, map the weights, register the class, and add tests. Do not discuss distributed strategy, launcher configuration, or general recipe authoring unless the user explicitly connects it to onboarding a new architecture. Examples Use these compact answer patterns for common questions: Dense causal LM: classify as dense only when architectures contains a ForCausalLM class and expert fields such as numlocalexperts, nroutedexperts, or numexpertspertok are absent. Create components/models/<name>/model.py, statedictadapter.py, init.py, and optional config.py, register MODELARCHMAPPING in transformers/registry.py, add example YAML, and add tiny-config unit tests plus layer-equivalence tests for rewritten layers. MoE state dict: identify expert fields in config.json, reference moe-patterns.md, map router tensors separately, preserve routed-expert index order, map routed experts, shared experts, and gate/up/down projections, add adapter key-map tests and tiny-config numerical equivalence tests, and do not rely only on frompretrained() or silent tensor reshapes. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/nemo-automodel-model-onboarding