llm-fine-tuning

Pass

Audited by Gen Agent Trust Hub on Oct 26, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill utilizes industry-standard machine learning libraries including Hugging Face transformers, peft, trl, and the axolotl training framework. All dependencies are sourced from the official Python Package Index (PyPI) registry.
  • [SAFE]: The Kubernetes Job manifest demonstrates secure handling of sensitive information, using SecretKeyRef to inject credentials like HUGGING_FACE_HUB_TOKEN and WANDB_API_KEY rather than hardcoding them in instructions or configurations.
  • [SAFE]: The container images referenced in the Kubernetes templates are sourced from a well-known, official service (nvcr.io
  • NVIDIA's Container Registry), which is a trusted source for GPU-accelerated workloads.
  • [SAFE]: The Python and shell commands provided are transparent and consistent with the skill's stated purpose of setting up LLM training environments, with no evidence of obfuscation or malicious redirection.
Audit Metadata
Risk Level
SAFE
Analyzed
Oct 26, 2026, 09:15 AM