model-pruning

Pass

Audited by Gen Agent Trust Hub on Oct 8, 2026

Risk Level: SAFEEXTERNAL_DOWNLOADSCOMMAND_EXECUTION
Full Analysis
  • [EXTERNAL_DOWNLOADS]: The skill instructs users to clone official research repositories from GitHub (locuslab/wanda and IST-DASLab/sparsegpt). These are well-known academic sources related to the research papers cited (ICLR 2024 and arXiv). It also fetches standard datasets like 'wikitext' and 'allenai/c4' via the Hugging Face datasets library.
  • [COMMAND_EXECUTION]: The installation section uses standard shell commands (git clone, pip install) to set up the environment and install necessary dependencies like torch, transformers, and accelerate. These are typical requirements for machine learning development.
  • [SAFE]: The Python implementations for Wanda and SparseGPT follow the logic described in their respective peer-reviewed research papers. The code uses standard PyTorch forward hooks and weight manipulation techniques to achieve model compression. No malicious patterns such as obfuscation, credential exfiltration, or unauthorized persistence were detected.
Audit Metadata
Risk Level
SAFE
Analyzed
Oct 8, 2026, 09:49 PM