model-compression-exploration
model-compression-exploration is a Model training & evaluation skill for AI agents, published by apple in the coreai-models repository on GitHub. Skillspace rates model-compression-exploration 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.
Systematically explore weight compression configurations (quantization and palettization) for a PyTorch model using coreai-opt, presenting a comprehensive overview of accuracy-vs-size tradeoff options. Use this skill whenever the user wants to compress a model, explore quantization or palettization options, understand compression config tradeoffs, reduce model size, or compare different compression techniques. Also trigger when the user mentions coreai-opt compression, weight quantization exploration, or palettization exploration — even if they don't say "explore" explicitly.
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 1,427
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
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- High-risk patterns
- License
- BSD-3-Clause
- Adoption
- Adopted by 1 other repositories, in 0 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.