rwkv-architecture
Pass
Audited by Gen Agent Trust Hub on Sep 17, 2026
Risk Level: SAFE
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill references the installation of standard machine learning dependencies including
torch,rwkv, andtransformers. It utilizes the official PyTorch package index atdownload.pytorch.orgfor GPU-accelerated versions, which is a trusted and well-known service for machine learning distribution. - [DYNAMIC_EXECUTION]: Implementation examples include the use of environment variables such as
RWKV_JIT_ONandRWKV_CUDA_ONto enable performance-optimizing Just-In-Time compilation and custom CUDA kernels. This is standard behavior for therwkvlibrary to achieve efficient inference. - [INDIRECT_PROMPT_INJECTION]: The skill documents the capability of the RWKV architecture to process large-scale text sequences from external sources, which is an inherent ingestion surface for language models. The provided examples focus on model forward passes and sequence processing without instructions that would lead to unauthorized command execution or safety bypasses.
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