Create README.md

README.md

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+---
+license: mit
+datasets:
+- antonypamo/savantorganized
+language:
+- en
+---
+# 🧬 ProSavantEngine Φ9.3 — Icosahedral Resonance Language Model
+
+**Author:** [Antony Padilla Morales](https://huggingface.co/antonypamo
+
+## 🧠 Overview
+
+`ProSavantEngine Φ9.3` extends the *Resonance of Reality Framework (RRF)* by coupling **language semantics** and **icosahedral geometry** through node-conditioned tokens `[NODE_1]`–`[NODE_12]`.  
+Each text sample during training was enriched with its geometric node context, allowing the model to align meaning with spatial-frequency symmetry.
+
+This version fine-tunes from **Φ9.2-Lite** on the full RRF corpus `corpus_unificado_total.jsonl`, augmented with `icosahedron_nodes.json`.
+
+---
+
+## 🚀 Quick Start
+
+Install dependencies:
+
+```bash
+pip install torch transformers datasets scipy plotly gradio
+
+
+Run inference:
+
+from transformers import AutoTokenizer, AutoModelForMaskedLM
+
+tok = AutoTokenizer.from_pretrained("antonypamo/ProSavantEngine_Phi9_3")
+model = AutoModelForMaskedLM.from_pretrained("antonypamo/ProSavantEngine_Phi9_3")
+
+text = "Quantum resonance aligns with [NODE_5]"
+inputs = tok(text, return_tensors="pt")
+outputs = model(**inputs, labels=inputs["input_ids"])
+print(outputs.loss)
+
+🧩 Fine-Tuning from the Hub
+
+You can continue training directly from the Hub:
+
+from transformers import Trainer, TrainingArguments
+
+args = TrainingArguments.from_pretrained("antonypamo/ProSavantEngine_Phi9_3")
+trainer = Trainer.from_pretrained(
+    "antonypamo/ProSavantEngine_Phi9_3",
+    args=args,
+    train_dataset=my_dataset,
+    eval_dataset=my_eval
+)
+trainer.train()
+
+📦 Requirements
+torch
+transformers
+datasets
+scipy
+plotly
+gradio
+
+📚 Dataset
+
+The model was trained on the unified corpus
+antonypamo/savantorganized
+
+and linked with icosahedron_nodes.json providing the 12-node geometric structure of the icosahedral lattice.
+
+🔮 Applications
+
+Resonant rewriting and coherence scoring
+
+Prompt optimization and semantic filtration
+
+Geometric–linguistic embeddings for RRF AI models
+
+Integration into AGORA / SavantEngine resonance simulations
+
+Cognitive field modeling and symbolic AI research
+
+🧭 Related Resources
+
+antonypamo/ProSavantEngine_Phi9_2_Lite
+ — prior iteration
+
+antonypamo/savantorganized
+ — training corpus
+
+ProSavantEngine Resonance Space
+ — live interactive demo
+
+📜 Citation
+@software{padilla2025prosavantengine,
+  author = {Padilla Morales, Antony},
+  title = {ProSavantEngine Φ9.3 — Icosahedral Resonant Language Model},
+  year = {2025},
+  url = {https://huggingface.co/antonypamo/ProSavantEngine_Phi9_3}
+}
+
+⚙️ Developer Notes
+
+Add your dataset card or a link to any .jsonl corpus used.
+
+Include training_args.json for reproducibility.
+
+The model supports multi-node resonance learning via [NODE_X] tokens.
+
+Compatible with both CPU and GPU environments.