modal-training
modal-training is a Fine-tuning & training data skill for AI agents, published by ChicagoHAI in the NeuriCo repository on GitHub. Skillspace rates modal-training 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.
Train or fine-tune models on Modal cloud GPUs (LoRA SFT, full SFT, data prep, eval) with strict leave-no-trace lifecycle. Use when an experiment needs GPU training, fine-tuning, or model evaluation that exceeds local Docker capacity.
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 145
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
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- High-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- references sensitive credential env
- 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.