---
license: apache-2.0
language:
- en
library_name: transformers
tags:
- coding
- medical
- real-estate
- architecture
- gguf
- qwen
base_model: unsloth/Qwen2.5-Coder-3B-Instruct
model_creator: [Your Name/Company]
model_type: causal-lm
pipeline_tag: text-generation
---

# 🛡️ VaultCoder-3B-SDLC

**VaultCoder-3B-SDLC** is a hyper-specialized, privacy-first Large Language Model (LLM) engineered for high-stakes enterprise architecture and secure software development lifecycle (SDLC) management. 

While generic models struggle with the nuances of regulated industries, VaultCoder has been fine-tuned using professional-grade **Knowledge Distillation** to provide elite-level performance in local environments.

---

## 🏛️ Industry-Specific Specializations

VaultCoder has been meticulously trained across 7 high-value sectors:

*   **🏥 Healthcare:** HIPAA-compliant AWS/Azure architectures, HL7 FHIR data mapping, and secure patient portal logic.
*   **🏘️ Real Estate:** RESO Web API integration, automated MLS sync services, and complex financial/mortgage calculators.
*   **🏎️ Automobile:** Real-time OBD-II telematics processing, EV fleet management APIs, and sensor data integration.
*   **🎨 AR/3D Design:** WebXR augmented reality components, 360° image-to-2D floor plan generation, and Unity 3D scripts.
*   **🎓 EdTech:** LMS database schemas (SCORM/xAPI) and AI-driven pedagogy for student feedback.
*   **📈 Sales Ops:** Predictive lead scoring engines and NLP-based automated CRM outreach.
*   **⚖️ Strategic Advisory:** Automated M&A due diligence (RAG), Monte Carlo risk simulations, and SWOT analysis.

---

## 🛠️ Training Methodology

VaultCoder-3B-SDLC was developed using a state-of-the-art **Knowledge Distillation** pipeline:

1.  **Teacher Model:** Qwen2.5-Coder-7B-Instruct (High-reasoning "Pro" architect).
2.  **Dataset:** A proprietary 24-record "Gold Standard" dataset generated with deep architectural reasoning and zero placeholders.
3.  **Technique:** LoRA (Low-Rank Adaptation) fine-tuning on the Qwen2.5-Coder-3B base.
4.  **Quantization:** 4-bit GGUF (Q4_K_M) for maximum speed and minimum RAM usage on standard CPUs.

---

## 🚀 Quick Start (Local Deployment)

VaultCoder is optimized for private, local execution using **Ollama**.

### 1. Create a Modelfile
Create a file named `Modelfile`:
```dockerfile
FROM ./VaultCoder-3B-SDLC.gguf

SYSTEM """
You are VaultCoder, a World-Class Software Engineer and Strategic Business Consultant. 
Your goal is to provide production-ready, secure, and industry-optimized solutions.
"""

PARAMETER temperature 0.3
PARAMETER num_ctx 8192
```

### 2. Run the Model
```bash
ollama create vaultcoder -f Modelfile
ollama run vaultcoder
```

---

## 🔒 Privacy & Compliance
VaultCoder is designed to run **100% offline**. Your intellectual property, patient data, and financial records never leave your local infrastructure, making it the ideal choice for companies that cannot use cloud-based AI providers.

## 📜 License
This model is released under the **Apache 2.0 License**.

---
**Maintained by:** Tarun  
**For Inquiries:** [LinkedIn Profile](https://www.linkedin.com/in/tarunsai/)