quantizing-models-bitsandbytes
Pass
Audited by Gen Agent Trust Hub on Sep 17, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides documentation and code snippets for LLM optimization. All code examples follow established machine learning practices.
- [INDIRECT_PROMPT_INJECTION]: The skill includes instructions for fine-tuning models using external datasets, such as 'timdettmers/openassistant-guanaco'. While ingesting external data constitutes an attack surface for indirect prompt injection, this is an inherent and necessary part of the model training workflows the skill is designed to facilitate. No specific malicious injection payloads were found in the static content.
- Ingestion points: Dataset loading via
datasets.load_datasetinreferences/qlora-training.md. - Boundary markers: None (standard for research code).
- Capability inventory: File system writes for model checkpoints (
model.save_pretrained), GPU compute operations. - Sanitization: Standard Hugging Face dataset processing.
- [EXTERNAL_DOWNLOADS]: The skill references and installs widely recognized, legitimate open-source libraries from the Python Package Index (PyPI) and models from Hugging Face. These downloads are required for the skill's primary functionality and target trusted infrastructure.
Audit Metadata