semvec/pypi-packages huggingface dataset:
sl-gme 0.1.0
Semantic-Load-Guided Model Evolution
License: Apache 2.0
Requires Python: >=3.9

# SL-GME: Semantic-Load-Guided Model Evolution
[DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17950040.svg)](https://doi.org/10.5281/zenodo.17950040)

**Authors**: Roberto Jimenez
**License**: Apache 2.0

## Overview

A framework that compresses, deploys, and fine-tunes language models by identifying which components carry conceptual meaning versus redundancy, then using that distinction to guide evolution toward superior models while preserving semantic integrity.
## 📊 SL-GME Performance Benchmarks
* **Compression:** 40% reduction in parameter space via spatial truncation.
* **Fidelity:** 97% accuracy maintained compared to full-rank thermodynamic limit simulations.
* **Speedup:** ~73x faster than classic FFT-based solvers using QH-FFT integration.
## Core Components

1. **Semantic Load Calculation**: Compute Λ(ℓ) = I_concept(ℓ) - I_surface(ℓ)
2. **Intelligent Compression**: Create bootloaders using semantic triage
3. **Guided Evolution**: Diffusion-based model evolution with semantic weighting

## Quick Start

```bash
# Install dependencies
pip install -r requirements.txt

# Calculate semantic load
python src/semantic_load/calculator.py

# Create a bootloader
python src/compression/bootloader.py

# Run guided evolution
python src/evolution/diffusion.py