modal-gpu-experiment
modal-gpu-experiment is an MLOps & model serving skill for AI agents, published by modal-projects in the modal-auto-research-skills repository on GitHub. Skillspace rates modal-gpu-experiment 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.
Training apps, experiment patterns, and persistent storage on Modal. Write single-GPU and multi-node training jobs with volumes for data and checkpoints, secrets for W&B/HuggingFace, and fault tolerance via retries and checkpoint auto-resume. Use when you need to run training, fine-tuning, or batch experiments on Modal GPUs.
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 36
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.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- High-risk patterns
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- executes shell/subprocess
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.