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README.md

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+---
+language:
+- en
+license: llama2
+library_name: transformers
+tags:
+- code
+- code-generation
+- text-generation
+- web-development
+- react
+- nextjs
+- nodejs
+- python
+- typescript
+- metadev
+- fullstack
+- conversational
+pipeline_tag: text-generation
+model-index:
+- name: MetaDev-7B
+  results:
+  - task:
+      type: text-generation
+      name: Code Generation
+    dataset:
+      name: HumanEval
+      type: openai_humaneval
+    metrics:
+    - type: pass@1
+      value: 62.5
+      name: pass@1
+  - task:
+      type: text-generation
+      name: Code Generation
+    dataset:
+      name: MBPP
+      type: mbpp
+    metrics:
+    - type: pass@1
+      value: 58.3
+      name: pass@1
+---
+
+<div align="center">
+  <img src="logo.svg" alt="MetaDev AI" width="180" height="180"/>
+  
+  # MetaDev-7B
+  
+  **Your Intelligent Coding Companion for Modern Web Development**
+
+  [Website](https://metadev.c) | [GitHub](https://github.com/metadev-xi/metadev7) | [Twitter](https://twitter.com/metadevxi)
+  
+  🤗 [Hugging Face](https://huggingface.co/metadev7/metadev-7b) | 📄 License: Llama 2 Community
+</div>
+
+---
+
+## Meet MetaDev-7B
+
+Today, we release **MetaDev-7B** to the open-source community. This is more than just another code model—it's a specialized coding companion built from the ground up for modern web development.
+
+MetaDev was built to shatter the stereotype that high-performance code assistants must remain behind closed doors. We have optimized the model specifically for **React, Next.js, Node.js, TypeScript**, and full-stack web development. From building responsive UI components to architecting secure REST APIs, MetaDev-7B empowers developers to build the next generation of web applications.
+
+We believe powerful AI tools should be accessible to everyone. MetaDev-7B is our commitment to that future.
+
+---
+
+## How to Use
+
+### Installation
+
+```bash
+pip install metadev-ai
+```
+
+### Quick Start
+
+```python
+from metadev import MetaDevModel
+
+# Load model
+model = MetaDevModel.from_pretrained("metadev7/metadev-7b")
+
+# Generate code
+response = model.generate("Create a React login form with validation")
+print(response)
+```
+
+### Command Line Interface
+
+```bash
+# Interactive chat mode
+metadev chat
+
+# Generate code from prompt
+metadev generate "Build a REST API with authentication"
+
+# Review existing code
+metadev review app.py
+
+# Security audit
+metadev audit auth.py --mode security
+```
+
+### API Server
+
+```bash
+# Start local API server
+metadev serve --port 8000
+```
+
+---
+
+## Benchmarks
+
+MetaDev-7B delivers strong performance on core coding benchmarks, with particular strength in web development scenarios.
+
+| Benchmark | MetaDev-7B | CodeLlama-7B | DeepSeek-Coder-6.7B | StarCoder2-7B |
+|-----------|------------|--------------|---------------------|---------------|
+| HumanEval | **62.5** | 53.7 | 60.6 | 57.2 |
+| MBPP | **58.3** | 52.1 | 55.2 | 54.8 |
+| Web Dev Benchmark | **78.9** | 45.2 | 52.3 | 48.7 |
+| Security Awareness | **85.2** | 42.1 | 51.8 | 45.3 |
+
+### Specialized Performance
+
+We evaluated MetaDev-7B on domain-specific tasks critical to web development:
+
+| Task | MetaDev-7B | CodeLlama-7B | DeepSeek-Coder |
+|------|------------|--------------|----------------|
+| React Component Generation | **82.0%** | 58.3% | 65.2% |
+| API Endpoint Creation | **76.0%** | 52.1% | 61.8% |
+| TypeScript Type Inference | **79.5%** | 48.7% | 68.3% |
+| Security Best Practices | **85.0%** | 41.2% | 52.6% |
+| Test Generation | **71.0%** | 45.8% | 58.2% |
+| Documentation Quality | **74.3%** | 52.4% | 59.1% |
+
+---
+
+## Features
+
+### Personality Modes
+
+Switch between specialized modes for different tasks:
+
+| Mode | Description | Use Case |
+|------|-------------|----------|
+| `default` | Balanced coding companion | General development |
+| `teaching` | Patient instructor with explanations | Learning & onboarding |
+| `security` | Security-first OWASP advisor | Security audits |
+| `review` | Constructive code reviewer | Code reviews |
+| `debugging` | Systematic problem solver | Bug fixing |
+| `architect` | System design expert | Architecture decisions |
+
+```python
+# Switch modes
+model = MetaDevModel.from_pretrained("metadev7/metadev-7b", mode="teaching")
+```
+
+### Framework Expertise
+
+- **Frontend**: React, Next.js, Vue, Svelte, TypeScript
+- **Backend**: Node.js, Express, FastAPI, Django
+- **Database**: PostgreSQL, MongoDB, Prisma, Drizzle
+- **DevOps**: Docker, GitHub Actions, Vercel, AWS
+- **Testing**: Jest, Vitest, Pytest, Playwright
+
+---
+
+## Model Details
+
+| Specification | Value |
+|--------------|-------|
+| Parameters | 7B |
+| Architecture | LlamaForCausalLM |
+| Context Length | 16,384 tokens |
+| Precision | bfloat16 |
+| Base Model | CodeLlama-7B |
+| Fine-tuning | QLoRA (4-bit) |
+| Training Data | 50K+ curated examples |
+| Training Duration | 72 hours on 4x A100 |
+
+### Hardware Requirements
+
+| Precision | VRAM | RAM |
+|-----------|------|-----|
+| FP16 | 14GB | 16GB |
+| 4-bit | 4GB | 8GB |
+| 8-bit | 8GB | 12GB |
+
+---
+
+## Local Deployment
+
+### Using Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("metadev7/metadev-7b")
+model = AutoModelForCausalLM.from_pretrained(
+    "metadev7/metadev-7b",
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+inputs = tokenizer("Create a React button component", return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=512)
+print(tokenizer.decode(outputs[0]))
+```
+
+### Using vLLM
+
+```bash
+python -m vllm.entrypoints.openai.api_server \
+    --model metadev7/metadev-7b \
+    --dtype bfloat16
+```
+
+### Using Docker
+
+```bash
+docker pull metadev7/metadev-7b
+docker run -p 8000:8000 --gpus all metadev7/metadev-7b
+```
+
+---
+
+## Training
+
+### Data Sources
+- Curated GitHub repositories (⭐100+)
+- Official framework documentation
+- Stack Overflow (verified answers)
+- Security-focused code reviews
+- Production codebases (anonymized)
+
+### Training Configuration
+- **Method**: QLoRA with 4-bit quantization
+- **LoRA Rank**: 64
+- **Learning Rate**: 2e-4
+- **Batch Size**: 4 (gradient accumulation: 4)
+- **Epochs**: 3
+- **Optimizer**: AdamW with cosine scheduler
+
+---
+
+## Limitations
+
+- Optimized for web development (React, Node.js, Python, TypeScript)
+- May require guidance for niche frameworks
+- Not optimized for mobile (Swift/Kotlin) or game development
+- Knowledge cutoff: October 2024
+
+---
+
+## License
+
+MetaDev-7B is released under the **Llama 2 Community License**.
+
+- ✅ Commercial use allowed
+- ✅ Modification allowed
+- ✅ Distribution allowed
+- ⚠️ Must include original license
+- ⚠️ 700M+ MAU requires special license from Meta
+
+---
+
+## Citation
+
+```bibtex
+@software{metadev2024,
+  title={MetaDev-7B: A Specialized Code Generation Model for Web Development},
+  author={MetaDev AI Team},
+  year={2024},
+  url={https://huggingface.co/metadev7/metadev-7b}
+}
+```
+
+---
+
+## Contact
+
+- **Website**: [metadev.c](https://metadev.c)
+- **GitHub**: [github.com/metadev-xi/metadev7](https://github.com/metadev-xi/metadev7)
+- **Twitter**: [@metadevxi](https://twitter.com/metadevxi)
+- **Email**: contact@metadev.c