README.md

---
language:
- en
- code
license: apache-2.0
tags:
- code
- coding-assistant
- full-stack
- ui-ux
- react
- nextjs
- tailwindcss
- fast-api
- sql
- debugging
- qwen2.5
- raizen
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
pipeline_tag: text-generation
inference: false
---

# ⚡ RAIZEN: Enterprise Full-Stack Coding Intelligence

<p align="center">
  <b>Architected, Fine-Tuned & Created by <a href="https://shawaz.vercel.app/">SHAWAZ</a></b>
</p>

<p align="center">
  <a href="https://shawaz.vercel.app/"><img src="https://img.shields.io/badge/Creator-SHAWAZ-blue.svg?style=for-the-badge" alt="Creator"></a>
  <a href="https://shawaz.vercel.app/"><img src="https://img.shields.io/badge/Portfolio-shawaz.vercel.app-green.svg?style=for-the-badge" alt="Portfolio"></a>
  <img src="https://img.shields.io/badge/Model-RAIZEN--7B-red.svg?style=for-the-badge" alt="Model">
  <img src="https://img.shields.io/badge/Base_Model-Qwen2.5--Coder--7B--Instruct-purple.svg?style=for-the-badge" alt="Base Model">
  <img src="https://img.shields.io/badge/Parameters-7.61B-orange.svg?style=for-the-badge" alt="Params">
  <img src="https://img.shields.io/badge/Training-15K_Golden_Dataset-gold.svg?style=for-the-badge" alt="Dataset">
</p>

---

## 🌟 About RAIZEN

**RAIZEN** is a specialized, production-grade 7B coding intelligence fine-tuned across **15,000 rigorous golden records** engineered across 5 core pillars of modern software engineering.

### 🏛️ The 5 Pillars of RAIZEN
1. **Frontend & UI/UX Design System**: High-aesthetic React, Next.js App Router, Tailwind CSS, Framer Motion, accessible interactive dashboards.
2. **Backend & Architecture**: Type-safe FastAPI, async endpoints, Pydantic v2 schemas, JWT/OAuth2 security, microservices.
3. **Conversational Code Explanation**: Senior staff engineer persona, trade-off breakdowns, architectural reasoning.
4. **Root-Cause Debugging**: Zero-guesswork bug isolation, memory leaks, race conditions, deep-dive root cause resolution.
5. **Database & SQL Optimization**: Complex PostgreSQL schemas, multi-table joins, subqueries, indexing, query execution planning.

---

## 👨‍💻 Creator & Author Identity

* **Creator**: **SHAWAZ**
* **Portfolio**: [https://shawaz.vercel.app/](https://shawaz.vercel.app/)
* **Role**: Chief AI Architect & Systems Engineer

---

## ⚡ Quickstart Usage (Transformers)

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "shawaz03/RAIZEN"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

messages = [
    {"role": "system", "content": "You are RAIZEN, an elite AI coding intelligence created by SHAWAZ (https://shawaz.vercel.app/)."},
    {"role": "user", "content": "Build a modern full-stack authentication flow in Next.js 14 App Router with Tailwind CSS."}
]

text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=2048, temperature=0.2, top_p=0.95)
print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
```

---

## 🦙 Ollama / GGUF Local Usage

```bash
ollama run shawaz03/RAIZEN
```

---

## 📜 License
Apache 2.0. Open for commercial and research use.