Independent Technical Evaluation of Externalized GPT-2 Parameters and Versioned Tensor Interventions

This technical report presents an independent evaluation of WKClifford LLC's externalized GPT-2 parameter storage and versioned tensor intervention implementation. The evaluation examines parameter fidelity, inference reproducibility, controlled model modification, state preservation, and failure behavior. Experiments were conducted independently using a Windows 11 virtual machine, native model interfaces, and Python-based verification procedures. The evaluation confirmed successful materialization and byte-exact relocation of all 148 GPT-2 tensors, greedy inference agreement across 320 generated tokens, and a maximum observed absolute logit difference of approximately 2.012 × 10⁻⁴. Additional experiments examined the creation of successor model views through controlled tensor replacement. Independently developed verification procedures confirmed the persistence and retrieval of distinct parent and successor states while preserving the tested baseline parameters. The evaluation also documented limitations in validation behavior, including deferred failure when a successor view referenced a nonexistent replacement artifact. A subsequent regression test confirmed successful execution of the corrected fidelity verification harness, with all specified acceptance conditions passing and a newly generated verification receipt. The findings establish that the evaluated implementation supports externalized parameter retrieval, reproducible inference under the tested conditions, and independently recoverable versioned tensor interventions. They do not establish superior computational efficiency, energy savings, autonomous learning, or general architectural superiority. This publication is an independent technical evaluation authored by Tony Vidlak. The underlying proprietary implementation remains the intellectual property of WKClifford LLC. The report distinguishes independently verified findings from supplier-authored demonstrations and identifies the limitations of the experimental evidence. Keywords: GPT-2, externalized parameters, model reproducibility, tensor interventions, inference fidelity, model state preservation, independent technical evaluation.