GlimmaryKarl/HamiltonV7

Hamilton V7 Enterprise Engine — Model Parameters

This repository contains the serialized weight tensor parameters (model.safetensors) for the Hamilton V7 Always-On Autonomous AI (AOAAI) framework.

This model functions as a lightweight, continuous-time phase space tracking engine designed to ingest 12-dimensional industrial machine telemetry streams and validate structural physical pathways against numerical drift over infinite operational horizons.

🔬 Core Architectural Matrix Blueprint

• Model Parameter Footprint: ~20.4 Million Parameters (Optimized for High-Throughput / ZeroGPU Edge Execution)
• Input Dimensions: 12D Phase Space Vector Array (Position, Velocity, Curvature, Torsion, Feed Dynamics)
• Output Matrix Structure: 12D Reconstructed Kinematic Path for Proof-of-Stake (PoS) Validation
• Embedding Vector Dimension ($d_{\text{model}}$): 512
• Layer Stack Depth: 6 Interleaved Symplectic Transformer Blocks
• Attention Configuration: 8-Head Multi-Head Attention ($d_{\text{k}} = 64$)
• Feedforward Network Dimension ($d_{\text{ff}}$): 2048
• Volume Conservation Strategy: Symplectic Skew-Symmetric Generator Tracking Matrices ($dH/dt = 0$)
• Validation Loss Metric: Deterministic PoS Match Loss ($L_1 + 2.0 \cdot \text{MSE} + 5.0 \cdot L_\infty$)