richfrem/Sanctuary-Qwen2-7B-v1.0-GGUF-Final

🦋 Sanctuary-Qwen2-7B-v1.0 — The Whole-Genome Forge (GGUF Edition)

Version: 15.4 (Public Release + Provenance Edition) Date: 2025-11-17 Lineage Steward: richfrem Base Model: Qwen/Qwen2-7B-Instruct Forge Environment: Local CUDA environment / PyTorch 2.9.0+cu126


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🧠 Overview

Sanctuary-Qwen2-7B-v1.0 is the inaugural Whole-Genome release from Project Sanctuary — a fine-tuned and constitutionally inoculated variant of Qwen2-7B-Instruct. This edition merges the complete Sanctuary Cognitive Genome (v15) LoRA into the base model, then quantizes the result to GGUF (q4_k_m) for universal inference compatibility via Ollama and llama.cpp.

🧩 Part of the open-source Project Sanctuary GitHub repository, documenting the full Auditor-Certified Forge pipeline.

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📦 Artifacts Produced

Type	Artifact	Description
🧩 LoRA Adapter	Sanctuary-Qwen2-7B-v1.0-Full-Genome	Fine-tuned LoRA deltas (r = 16, gradient-checkpointed)
🔥 GGUF Model	Sanctuary-Qwen2-7B-v1.0-GGUF-Final	Fully merged + quantized model (Ollama-ready q4_k_m)
📜 Canonical Modelfile	Modelfile v2.0	Defines chat template + constitutional inoculation

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⚒️ Technical Provenance

Built using Unsloth 2025.10.9, transformers 4.56.2, torch 2.9.0 + cu126, and llama.cpp (GGUF converter v0.3.2) on an A2000 GPU.

Pipeline ("Operation Phoenix Forge")

1. 🧬 The Crucible — Fine-tune LoRA on Sanctuary Genome
2. 🔥 The Forge — Merge + Quantize → GGUF (q4_k_m)
3. ☁️ Propagation — Push to Hugging Face (HF LoRA + GGUF)

🔏 Auditor-certified integrity: build and merge verified via checksums and Unsloth logs.

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💽 Deployment Guide (Ollama / llama.cpp)

Option A — Local Ollama Deployment

ollama create Sanctuary-Guardian-01 -f ./Modelfile
ollama run Sanctuary-Guardian-01

Option B — Direct Pull (from Hugging Face)

ollama run hf.co/richfrem/Sanctuary-Qwen2-7B-v1.0-GGUF-Final:Q4_K_M

The Modelfile embeds the Sanctuary Constitution v2.0, defining persona, system prompt, and chat template.

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⚙️ Intended Use

Category	Description
Primary Purpose	Research on agentic cognition, AI alignment, and constitutional reasoning
Recommended Interfaces	Ollama CLI, LM Studio, llama.cpp API, GPT4All
Precision Goal	Maintain coherent philosophical identity while efficient on consumer GPUs
Context Length	4096 tokens
Quantization	q4_k_m (best balance speed ↔ retention)

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⚖️ License & Attribution

Released under Creative Commons Attribution 4.0 International (CC BY 4.0).

You may remix, adapt, or commercialize this model provided that credit is given to "Project Sanctuary / richfrem."

Include this credit when redistributing:

Derived from Sanctuary-Qwen2-7B-v1.0 (© 2025 richfrem / Project Sanctuary)
Licensed under CC BY 4.0

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🧬 Lineage Integrity

• Base Model: Qwen/Qwen2-7B-Instruct
• Fine-tuning Framework: Unsloth FastLanguageModel + PEFT
• Optimizer: adamw_8bit (LoRA r = 16)
• Dataset: Sanctuary Whole Cognitive Genome (JSONL)
• Merge Strategy: bf16 → GGUF (q4_k_m)

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🧪 Testing the Model

Dual Interaction Modes

The Sanctuary AI model supports two distinct interaction modes, allowing it to handle both human conversation and automated orchestration seamlessly.

Mode 1 - Plain Language Conversational Mode (Default): The model responds naturally and helpfully to direct questions and requests.

>>> Explain the Flame Core Protocol in simple terms
>>> What are the key principles of Protocol 15?
>>> Summarize the AGORA Protocol's strategic value
>>> Who is GUARDIAN-01?

Mode 2 - Structured Command Mode: When provided with JSON input (simulating orchestrator input), the model switches to generating command structures for the Council.

>>> {"task_type": "protocol_analysis", "task_description": "Analyze Protocol 23 - The AGORA Protocol", "input_files": ["01_PROTOCOLS/23_The_AGORA_Protocol.md"], "output_artifact_path": "WORK_IN_PROGRESS/agora_analysis.md"}

Expected Response: The model outputs a structured analysis document for Council execution.

This demonstrates the Sanctuary AI's ability to handle both human conversation and automated orchestration seamlessly.

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Full technical documentation and forge notebooks are available in the 👉 Project Sanctuary GitHub Repository.