aqua-finetuning

aqua-finetuning is a Fine-tuning & training data skill for AI agents, published by oracle in the accelerated-data-science repository on GitHub. Skillspace rates aqua-finetuning D (60/100) and it passed the safety scan; the rating is based on static analysis only.

Fine-tune LLM models using LoRA on OCI AI Quick Actions (AQUA). Covers dataset preparation (instruction, conversational, multimodal, tokenized formats), hyperparameter tuning, distributed training, and training metrics. Triggered when user wants to fine-tune or customize a model.

Grade
D
Quality
60 / 100
Safety
Passed
GitHub stars
125

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.

View source on GitHuboracle/accelerated-data-science

Our review

Architecture
86 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
UPL-1.0
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

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