neuron-framework-equivalence
neuron-framework-equivalence is a Model training & evaluation skill for AI agents, published by aws-neuron in the neuron-agentic-development repository on GitHub. Skillspace rates neuron-framework-equivalence C (73/100) and it passed the safety scan; the rating is based on static analysis only.
Verifies functional equivalence between two implementations of the same model using a hierarchical 8-stage algorithm. Orchestrates model tree comparison, component-level R-ratio testing, E2E logit comparison, and distributional checks. Use when porting models between frameworks, hardware targets, or precision regimes — e.g., HuggingFace to NxDI, PyTorch to ONNX, GPU to Neuron, FP32 to BF16, or any source-target pair.
- Grade
- C
- Quality
- 73 / 100
- Safety
- Passed
- GitHub stars
- 41
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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