atc-model-converter
atc-model-converter is an MLOps & model serving skill for AI agents, published by Ascend in the agent-skills repository on GitHub. Skillspace rates atc-model-converter F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.
Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.
Complete toolkit for Huawei Ascend NPU model conversion and end-to-end inference adaptation. Workflow 1 auto-discovers input shapes and parameters from user source code. Workflow 2 exports PyTorch models to ONNX. Workflow 3 converts ONNX to .om via ATC with multi-CANN version support. Workflow 4 adapts the user's full inference pipeline (preprocessing + model + postprocessing) to run end-to-end on NPU. Workflow 5 verifies precision between ONNX and OM outputs. Workflow 6 generates a reproducible README. Supports any standard PyTorch/ONNX model. Use when converting, testing, or deploying models on Ascend AI processors.
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 27
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since.
Our review
- Architecture
- 86 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- High-risk patterns
- License
- MulanPSL-2.0
- Adoption
- Adopted by 1 other repositories, in 1 collections
What the scanner flagged
- dynamic code execution (eval/exec)
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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