peft-fine-tuning
Pass
Audited by Gen Agent Trust Hub on Oct 26, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides boilerplate code for machine learning workflows using established libraries such as Hugging Face's transformers, PEFT, and TRL. All command-line and Python examples align with the primary purpose of model fine-tuning.
- [EXTERNAL_DOWNLOADS]: The skill includes instructions to install standard, well-known Python packages from official registries (torch, transformers, datasets, peft, accelerate, trl, bitsandbytes). It also references downloading models from Hugging Face, which is a recognized and well-known service in the AI community.
- [CREDENTIALS_UNSAFE]: The skill mentions the
hf auth logincommand for accessing gated models. This is a standard interactive authentication method for Hugging Face and does not involve hardcoding or leaking credentials within the skill itself. - [INDIRECT_PROMPT_INJECTION]: The skill describes ingesting training data from external files (JSONL). While this represents a data ingestion surface, the context is limited to model fine-tuning, which is the intended purpose of the skill. Standard security practices for handling training data are recommended at the platform level.
Audit Metadata