metadata
title: Hamilton V7 Model Weights
license: openrail
tags:
- hamiltonian-mechanics
- transformers
- proof-of-stake-validation
- physics-informed-nn
- industry-4.0
- safetensors
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 ($L_1 + 2.0 \cdot \text{MSE} + 5.0 \cdot L_\infty$)