feat(skills): add model verification cards - #3575
Draft
yaoyu-33 wants to merge 2 commits into
Draft
Conversation
Signed-off-by: yaoyu-33 <yaoyu.094@gmail.com>
Contributor
|
🌿 Preview your docs: https://nvidia-preview-preview-62de5c497e02.docs.buildwithfern.com/nemo/automodel |
Contributor
|
/ok to test 62de5c4 |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
What does this PR do ?
Add an agent-readable model verification card workflow, validator, and the first AutoModel card for Qwen3-30B-A3B.
Changelog
nemo-automodel-model-verification-cardskill, schema reference, and validator.verifiedandnot_verifiedstatus buckets.pretrain_performanceseparate and not verified; record the functional TFLOPS observation and canonical benchmark recipe for the future tuned run.vllm_checkpoint_compatibilityas the downstream checkpoint gate and define 128K CoderForge SFT undersft_long_context.*_verification_card.yamlfiles from recipe-only lint, CI discovery, documentation coverage, and model-release scanning, with regression tests.Before your PR is "Ready for review"
Pre checks:
Verification
uv run pytest -q tests/unit_tests/skills/test_model_verification_card.py tests/unit_tests/config/test_example_yaml_linter.py tests/unit_tests/ci_tests/test_generate_ci_tests.py tests/unit_tests/_transformers/test_recipe_doc_coverage.py tests/unit_tests/tools/test_sync_model_coverage_tables.py— 51 passed, 1 skippedruff format --check .andruff check .passed.Additional Information
The verified evidence is bounded functional training and resume evidence. The functional AutoModel observation is 135.4928 model TFLOPS/GPU versus the referenced Megatron Bridge observation of 199.120 model TFLOPS/GPU (-31.9542%); it is intentionally not presented as a tuned performance result.