estimate-memory
estimate-memory is a Model training & evaluation skill for AI agents, published by mlc-ai in the pith-train repository on GitHub. Skillspace rates estimate-memory D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Estimate peak GPU memory for a DualPipeV training run. Use when the user asks to "estimate memory", "will this fit in memory", "how much GPU memory", "check if this OOMs", "memory for training X on Y GPUs", or mentions memory planning for a training configuration. Translates natural-language descriptions of hardware, model, and training setup into the exact CLI arguments for `python -m tools.memory_estimator`.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 267
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, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- 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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