README.md

metadata

title: ProSavantEngineSpace
emoji: 💻
colorFrom: gray
colorTo: gray
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: mit

🌀 ProSavantEngine Φ9.3 — Resonance Analyzer Space

Author: Antony Padilla Morales
Powered by: Transformers, Gradio, and the Resonance of Reality Framework (RRF)

🌌 Overview

The ProSavantEngine Φ9.3 Resonance Analyzer Space lets you explore how language aligns with icosahedral geometry and Φ-weighted resonance.
Each text input is analyzed through the fine-tuned model ProSavantEngine Φ9.3, which computes a semantic–geometric coherence score between 0 and 1.

🧠 Think of it as a “resonance oscilloscope” for ideas — the closer to 1.0, the more harmonically aligned your language is with the golden-ratio symmetries encoded in the model.

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🚀 Try It Live

Enter any phrase, sentence, or paragraph and observe its Φ-weighted coherence.

Examples:

Input	Output Φ-Score
Consciousness emerges through quantum geometry.	0.87
Energy oscillates within golden symmetry.	0.91
Noise disrupts the coherence of information fields.	0.63

A high Φ-score (≥0.75) means the sentence resonates harmonically between geometry, meaning, and information.

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⚙️ How It Works

1. Input Encoding — text is tokenized and passed through ProSavantEngine Φ9.3.
2. Hidden-State Extraction — the mean hidden layer activations are Fourier-transformed.
3. Φ-Weighted Resonance — the model applies a golden-ratio weighting cos(πf/φ)^2 to quantify coherence.
4. Score Normalization — the result is scaled to [0, 1] as a resonance index.

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💡 Applications

• Prompt optimization — find harmonically coherent prompts for generative models.
• Scientific writing — evaluate the structural resonance of complex hypotheses.
• Artistic exploration — generate poetic or musical language aligned with geometric flow.
• AI alignment research — measure how symbolic or semantic balance affects interpretability.

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🧩 Model Used

Model: antonypamo/ProSavantEngine_Phi9_3
Base Architecture: BERT (6-layer, hidden size 384)
Objective: Masked-Language Modeling + Φ-weighted coherence fine-tuning
Training Data: antonypamo/savantorganized
Fine-Tuned Context: icosahedral nodes [NODE_1]... [NODE_12] linked to geometric symmetry anchors

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🧰 Requirements

torch transformers scipy gradio

yaml Copy code

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📜 Citation

@software{padilla2025resonancespace,
  author = {Padilla Morales, Antony},
  title = {ProSavantEngine Φ9.3 — Resonance Analyzer Space},
  year = {2025},
  url = {https://huggingface.co/spaces/antonypamo/ProSavantEngine_ResonanceSpace}
}
🧠 Related Assets
antonypamo/ProSavantEngine_Phi9_3 — Full model weights and configs

antonypamo/savantorganized — Unified RRF training corpus

GitHub: Savant-RRF — development blueprints and equations

Overleaf: Resonance of Reality Framework Paper — theoretical publication version

🪐 Concept
“To speak is to resonate through geometry.
To think is to oscillate between meaning and symmetry.”

Φ9.3 transforms text into harmonic structure —
revealing how linguistic information vibrates across the icosahedral field of consciousness.

🔗 Live Space
👉 Launch: https://huggingface.co/spaces/antonypamo/ProSavantEngine_ResonanceSpace

© 2025 Antony Padilla Morales — Resonance of Reality Framework (RRF)