shawaz03/vibe-coder-7b-max
Vibe Coder v2.0 MAX by shawaz03 is a 7.61 billion parameter, fine-tuned code generation model based on Qwen2.5-Coder-7B-Instruct, specialized in full-stack development. It is engineered to produce complete, functional TypeScript, React, and Next.js code without placeholders, adhering to modern UI/UX design principles. The model excels at generating production-grade components, state hooks, and API routes, and includes self-healing capabilities for debugging.
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Overview
shawaz03/vibe-coder-7b-max, or Vibe Coder v2.0 MAX, is a 7.61 billion parameter, specialized code generation model built upon Qwen2.5-Coder-7B-Instruct. It is meticulously fine-tuned to address common LLM coding deficiencies, such as the inclusion of placeholder comments, broken imports, and outdated design patterns.
Key Capabilities
- Zero Placeholders Guaranteed: Generates fully functional code components, state hooks, and API routes without missing logic.
- Modern Anti-AI Aesthetic Directives: Incorporates built-in design rules for dark neutral palettes, custom typography, responsive layouts, and Lucide React icons.
- Full-Stack Ecosystem Mastery: Possesses native expertise in modern web technologies including Next.js 15 App Router, React 19, TypeScript, Tailwind CSS, Zustand, Prisma ORM, Zod validation, and WebSockets.
- Self-Healing & Debugging: Capable of diagnosing and providing root-cause explanations and code patches for runtime hydration errors and type mismatches.
Training Details
The model was trained on a 64,000-record Master Dataset structured in ChatML format, across 7 specialized pipelines. This included data from open-source Next.js repositories, handcrafted UI templates, multi-turn refinement dialogues, and datasets focused on self-healing and full-stack architectures. The training utilized a 4-bit NF4 QLoRA method, merged into a full 16-bit FP16 Safetensors model, achieving a final validation loss of 0.035 – 0.045 and a token accuracy of 98.5%.