quantizing-models-bitsandbytes

Pass

Audited by Gen Agent Trust Hub on Sep 18, 2026

Risk Level: SAFEINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
  • [SAFE]: No security threats identified. The skill contains documentation and code snippets for using standard machine learning libraries (bitsandbytes, transformers, peft, accelerate) and datasets. All network activities, such as package installations and dataset loading, target well-known and trusted services like PyPI and Hugging Face.
  • [INDIRECT_PROMPT_INJECTION]: The skill provides documentation for loading and fine-tuning models on external datasets. This is a standard machine learning workflow.
  • Ingestion points: Loads datasets using datasets.load_dataset("timdettmers/openassistant-guanaco") in references/qlora-training.md.
  • Boundary markers: Uses template delimiters (### Human:, ### Assistant:) to wrap ingested data.
  • Capability inventory: Involves model training via Trainer.train() and inference via model.generate().
  • Sanitization: Employs standard string formatting for instruction-tuning tasks.
  • [EXTERNAL_DOWNLOADS]: Includes instructions for installing packages from PyPI (pip install) and downloading model weights and datasets from Hugging Face. These represent standard development practices using trusted vendors and services.
Audit Metadata
Risk Level
SAFE
Analyzed
Sep 18, 2026, 12:21 AM
Security Audit — agent-trust-hub — quantizing-models-bitsandbytes