qeff-model-onboarding
qeff-model-onboarding is a Migrations, upgrades & porting skill for AI agents, published by quic in the efficient-transformers repository on GitHub. Skillspace rates qeff-model-onboarding C (74/100) and it passed the safety scan; the rating is based on static analysis only.
Add support for a new Hugging Face model in this QEfficient repo. Use when the user provides a Hub model id, pasted model card, config excerpt, or architecture name and wants the QEff equivalent implemented, mapped to the closest existing wrapper family, validated with a tiny or config-derived test model, and covered through `tests/test_model_quickcheck.py`.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 90
Unproven: rated by static analysis only, not yet compared head-to-head.
Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: it looks written only for the repository it lives in. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided
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
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
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.