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README.md
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---
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language:
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- en
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license: llama2
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library_name: transformers
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tags:
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- code
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- code-generation
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- text-generation
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- web-development
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- react
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- nextjs
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- nodejs
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- python
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- typescript
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- metadev
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- fullstack
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- conversational
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pipeline_tag: text-generation
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model-index:
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- name: MetaDev-7B
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results:
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- task:
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type: text-generation
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name: Code Generation
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dataset:
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name: HumanEval
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type: openai_humaneval
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metrics:
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- type: pass@1
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value: 62.5
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name: pass@1
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- task:
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type: text-generation
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name: Code Generation
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dataset:
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name: MBPP
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type: mbpp
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metrics:
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- type: pass@1
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value: 58.3
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name: pass@1
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---
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<div align="center">
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<img src="logo.
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# MetaDev-7B
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**Your Intelligent Coding Companion for Modern Web Development**
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[Website](https://metadev.c) | [GitHub](https://github.com/metadev-xi/metadev7) | [Twitter](https://twitter.com/metadevxi)
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🤗 [Hugging Face](https://huggingface.co/metadev7/metadev-7b) | 📄 License: Llama 2 Community
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</div>
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---
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## Meet MetaDev-7B
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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.
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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.
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We believe powerful AI tools should be accessible to everyone. MetaDev-7B is our commitment to that future.
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---
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## How to Use
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### Installation
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```bash
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pip install metadev-ai
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```
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### Quick Start
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```python
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from metadev import MetaDevModel
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# Load model
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model = MetaDevModel.from_pretrained("metadev7/metadev-7b")
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# Generate code
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response = model.generate("Create a React login form with validation")
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print(response)
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```
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### Command Line Interface
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```bash
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# Interactive chat mode
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metadev chat
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# Generate code from prompt
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metadev generate "Build a REST API with authentication"
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# Review existing code
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metadev review app.py
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# Security audit
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metadev audit auth.py --mode security
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```
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### API Server
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```bash
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# Start local API server
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metadev serve --port 8000
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```
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---
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## Benchmarks
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MetaDev-7B delivers strong performance on core coding benchmarks, with particular strength in web development scenarios.
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| Benchmark | MetaDev-7B | CodeLlama-7B | DeepSeek-Coder-6.7B | StarCoder2-7B |
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|-----------|------------|--------------|---------------------|---------------|
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| HumanEval | **62.5** | 53.7 | 60.6 | 57.2 |
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| MBPP | **58.3** | 52.1 | 55.2 | 54.8 |
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| Web Dev Benchmark | **78.9** | 45.2 | 52.3 | 48.7 |
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| Security Awareness | **85.2** | 42.1 | 51.8 | 45.3 |
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### Specialized Performance
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We evaluated MetaDev-7B on domain-specific tasks critical to web development:
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| Task | MetaDev-7B | CodeLlama-7B | DeepSeek-Coder |
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|------|------------|--------------|----------------|
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| React Component Generation | **82.0%** | 58.3% | 65.2% |
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| API Endpoint Creation | **76.0%** | 52.1% | 61.8% |
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| TypeScript Type Inference | **79.5%** | 48.7% | 68.3% |
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| Security Best Practices | **85.0%** | 41.2% | 52.6% |
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| Test Generation | **71.0%** | 45.8% | 58.2% |
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| Documentation Quality | **74.3%** | 52.4% | 59.1% |
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---
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## Features
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### Personality Modes
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Switch between specialized modes for different tasks:
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| Mode | Description | Use Case |
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|------|-------------|----------|
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| `default` | Balanced coding companion | General development |
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| `teaching` | Patient instructor with explanations | Learning & onboarding |
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| `security` | Security-first OWASP advisor | Security audits |
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| `review` | Constructive code reviewer | Code reviews |
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| `debugging` | Systematic problem solver | Bug fixing |
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| `architect` | System design expert | Architecture decisions |
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```python
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# Switch modes
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model = MetaDevModel.from_pretrained("metadev7/metadev-7b", mode="teaching")
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```
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### Framework Expertise
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- **Frontend**: React, Next.js, Vue, Svelte, TypeScript
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- **Backend**: Node.js, Express, FastAPI, Django
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- **Database**: PostgreSQL, MongoDB, Prisma, Drizzle
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- **DevOps**: Docker, GitHub Actions, Vercel, AWS
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- **Testing**: Jest, Vitest, Pytest, Playwright
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---
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## Model Details
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| Specification | Value |
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|--------------|-------|
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| Parameters | 7B |
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| Architecture | LlamaForCausalLM |
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| Context Length | 16,384 tokens |
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| Precision | bfloat16 |
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| Base Model | CodeLlama-7B |
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| Fine-tuning | QLoRA (4-bit) |
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| Training Data | 50K+ curated examples |
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| Training Duration | 72 hours on 4x A100 |
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### Hardware Requirements
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| Precision | VRAM | RAM |
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|-----------|------|-----|
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| FP16 | 14GB | 16GB |
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| 4-bit | 4GB | 8GB |
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| 8-bit | 8GB | 12GB |
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---
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## Local Deployment
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### Using Transformers
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("metadev7/metadev-7b")
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model = AutoModelForCausalLM.from_pretrained(
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"metadev7/metadev-7b",
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torch_dtype="auto",
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device_map="auto"
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)
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inputs = tokenizer("Create a React button component", return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=512)
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print(tokenizer.decode(outputs[0]))
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```
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### Using vLLM
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```bash
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python -m vllm.entrypoints.openai.api_server \
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--model metadev7/metadev-7b \
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--dtype bfloat16
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```
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### Using Docker
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```bash
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docker pull metadev7/metadev-7b
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docker run -p 8000:8000 --gpus all metadev7/metadev-7b
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```
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---
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## Training
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### Data Sources
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- Curated GitHub repositories (⭐100+)
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- Official framework documentation
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- Stack Overflow (verified answers)
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- Security-focused code reviews
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- Production codebases (anonymized)
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### Training Configuration
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- **Method**: QLoRA with 4-bit quantization
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- **LoRA Rank**: 64
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- **Learning Rate**: 2e-4
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- **Batch Size**: 4 (gradient accumulation: 4)
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- **Epochs**: 3
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- **Optimizer**: AdamW with cosine scheduler
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---
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## Limitations
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- Optimized for web development (React, Node.js, Python, TypeScript)
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- May require guidance for niche frameworks
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- Not optimized for mobile (Swift/Kotlin) or game development
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- Knowledge cutoff: October 2024
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---
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## License
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MetaDev-7B is released under the **Llama 2 Community License**.
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- ✅ Commercial use allowed
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- ✅ Modification allowed
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- ✅ Distribution allowed
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- ⚠️ Must include original license
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- ⚠️ 700M+ MAU requires special license from Meta
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---
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## Citation
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```bibtex
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@software{metadev2024,
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title={MetaDev-7B: A Specialized Code Generation Model for Web Development},
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author={MetaDev AI Team},
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year={2024},
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url={https://huggingface.co/metadev7/metadev-7b}
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}
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```
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---
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## Contact
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- **Website**: [metadev.c](https://metadev.c)
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- **GitHub**: [github.com/metadev-xi/metadev7](https://github.com/metadev-xi/metadev7)
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- **Twitter**: [@metadevxi](https://twitter.com/metadevxi)
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- **Email**: contact@metadev.c
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---
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| 2 |
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language:
|
| 3 |
+
- en
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| 4 |
+
license: llama2
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| 5 |
+
library_name: transformers
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| 6 |
+
tags:
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+
- code
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+
- code-generation
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| 9 |
+
- text-generation
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| 10 |
+
- web-development
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| 11 |
+
- react
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| 12 |
+
- nextjs
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| 13 |
+
- nodejs
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| 14 |
+
- python
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| 15 |
+
- typescript
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| 16 |
+
- metadev
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| 17 |
+
- fullstack
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| 18 |
+
- conversational
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pipeline_tag: text-generation
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| 20 |
+
model-index:
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| 21 |
+
- name: MetaDev-7B
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| 22 |
+
results:
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| 23 |
+
- task:
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type: text-generation
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name: Code Generation
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+
dataset:
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name: HumanEval
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type: openai_humaneval
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+
metrics:
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+
- type: pass@1
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+
value: 62.5
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+
name: pass@1
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+
- task:
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type: text-generation
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+
name: Code Generation
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+
dataset:
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+
name: MBPP
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+
type: mbpp
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+
metrics:
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+
- type: pass@1
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value: 58.3
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+
name: pass@1
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+
---
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+
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+
<div align="center">
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<img src="logo.png" alt="MetaDev AI" width="180" height="180"/>
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+
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# MetaDev-7B
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+
|
| 50 |
+
**Your Intelligent Coding Companion for Modern Web Development**
|
| 51 |
+
|
| 52 |
+
[Website](https://metadev.c) | [GitHub](https://github.com/metadev-xi/metadev7) | [Twitter](https://twitter.com/metadevxi)
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+
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🤗 [Hugging Face](https://huggingface.co/metadev7/metadev-7b) | 📄 License: Llama 2 Community
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</div>
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+
|
| 57 |
+
---
|
| 58 |
+
|
| 59 |
+
## Meet MetaDev-7B
|
| 60 |
+
|
| 61 |
+
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.
|
| 62 |
+
|
| 63 |
+
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.
|
| 64 |
+
|
| 65 |
+
We believe powerful AI tools should be accessible to everyone. MetaDev-7B is our commitment to that future.
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+
|
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+
---
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+
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## How to Use
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| 70 |
+
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### Installation
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+
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```bash
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pip install metadev-ai
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```
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+
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### Quick Start
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+
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```python
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from metadev import MetaDevModel
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# Load model
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model = MetaDevModel.from_pretrained("metadev7/metadev-7b")
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# Generate code
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response = model.generate("Create a React login form with validation")
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print(response)
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```
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### Command Line Interface
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+
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```bash
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# Interactive chat mode
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+
metadev chat
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+
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# Generate code from prompt
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metadev generate "Build a REST API with authentication"
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+
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# Review existing code
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metadev review app.py
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+
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# Security audit
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metadev audit auth.py --mode security
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```
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+
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### API Server
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+
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```bash
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# Start local API server
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metadev serve --port 8000
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```
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+
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+
---
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| 114 |
+
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+
## Benchmarks
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| 116 |
+
|
| 117 |
+
MetaDev-7B delivers strong performance on core coding benchmarks, with particular strength in web development scenarios.
|
| 118 |
+
|
| 119 |
+
| Benchmark | MetaDev-7B | CodeLlama-7B | DeepSeek-Coder-6.7B | StarCoder2-7B |
|
| 120 |
+
|-----------|------------|--------------|---------------------|---------------|
|
| 121 |
+
| HumanEval | **62.5** | 53.7 | 60.6 | 57.2 |
|
| 122 |
+
| MBPP | **58.3** | 52.1 | 55.2 | 54.8 |
|
| 123 |
+
| Web Dev Benchmark | **78.9** | 45.2 | 52.3 | 48.7 |
|
| 124 |
+
| Security Awareness | **85.2** | 42.1 | 51.8 | 45.3 |
|
| 125 |
+
|
| 126 |
+
### Specialized Performance
|
| 127 |
+
|
| 128 |
+
We evaluated MetaDev-7B on domain-specific tasks critical to web development:
|
| 129 |
+
|
| 130 |
+
| Task | MetaDev-7B | CodeLlama-7B | DeepSeek-Coder |
|
| 131 |
+
|------|------------|--------------|----------------|
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| 132 |
+
| React Component Generation | **82.0%** | 58.3% | 65.2% |
|
| 133 |
+
| API Endpoint Creation | **76.0%** | 52.1% | 61.8% |
|
| 134 |
+
| TypeScript Type Inference | **79.5%** | 48.7% | 68.3% |
|
| 135 |
+
| Security Best Practices | **85.0%** | 41.2% | 52.6% |
|
| 136 |
+
| Test Generation | **71.0%** | 45.8% | 58.2% |
|
| 137 |
+
| Documentation Quality | **74.3%** | 52.4% | 59.1% |
|
| 138 |
+
|
| 139 |
+
---
|
| 140 |
+
|
| 141 |
+
## Features
|
| 142 |
+
|
| 143 |
+
### Personality Modes
|
| 144 |
+
|
| 145 |
+
Switch between specialized modes for different tasks:
|
| 146 |
+
|
| 147 |
+
| Mode | Description | Use Case |
|
| 148 |
+
|------|-------------|----------|
|
| 149 |
+
| `default` | Balanced coding companion | General development |
|
| 150 |
+
| `teaching` | Patient instructor with explanations | Learning & onboarding |
|
| 151 |
+
| `security` | Security-first OWASP advisor | Security audits |
|
| 152 |
+
| `review` | Constructive code reviewer | Code reviews |
|
| 153 |
+
| `debugging` | Systematic problem solver | Bug fixing |
|
| 154 |
+
| `architect` | System design expert | Architecture decisions |
|
| 155 |
+
|
| 156 |
+
```python
|
| 157 |
+
# Switch modes
|
| 158 |
+
model = MetaDevModel.from_pretrained("metadev7/metadev-7b", mode="teaching")
|
| 159 |
+
```
|
| 160 |
+
|
| 161 |
+
### Framework Expertise
|
| 162 |
+
|
| 163 |
+
- **Frontend**: React, Next.js, Vue, Svelte, TypeScript
|
| 164 |
+
- **Backend**: Node.js, Express, FastAPI, Django
|
| 165 |
+
- **Database**: PostgreSQL, MongoDB, Prisma, Drizzle
|
| 166 |
+
- **DevOps**: Docker, GitHub Actions, Vercel, AWS
|
| 167 |
+
- **Testing**: Jest, Vitest, Pytest, Playwright
|
| 168 |
+
|
| 169 |
+
---
|
| 170 |
+
|
| 171 |
+
## Model Details
|
| 172 |
+
|
| 173 |
+
| Specification | Value |
|
| 174 |
+
|--------------|-------|
|
| 175 |
+
| Parameters | 7B |
|
| 176 |
+
| Architecture | LlamaForCausalLM |
|
| 177 |
+
| Context Length | 16,384 tokens |
|
| 178 |
+
| Precision | bfloat16 |
|
| 179 |
+
| Base Model | CodeLlama-7B |
|
| 180 |
+
| Fine-tuning | QLoRA (4-bit) |
|
| 181 |
+
| Training Data | 50K+ curated examples |
|
| 182 |
+
| Training Duration | 72 hours on 4x A100 |
|
| 183 |
+
|
| 184 |
+
### Hardware Requirements
|
| 185 |
+
|
| 186 |
+
| Precision | VRAM | RAM |
|
| 187 |
+
|-----------|------|-----|
|
| 188 |
+
| FP16 | 14GB | 16GB |
|
| 189 |
+
| 4-bit | 4GB | 8GB |
|
| 190 |
+
| 8-bit | 8GB | 12GB |
|
| 191 |
+
|
| 192 |
+
---
|
| 193 |
+
|
| 194 |
+
## Local Deployment
|
| 195 |
+
|
| 196 |
+
### Using Transformers
|
| 197 |
+
|
| 198 |
+
```python
|
| 199 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 200 |
+
|
| 201 |
+
tokenizer = AutoTokenizer.from_pretrained("metadev7/metadev-7b")
|
| 202 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 203 |
+
"metadev7/metadev-7b",
|
| 204 |
+
torch_dtype="auto",
|
| 205 |
+
device_map="auto"
|
| 206 |
+
)
|
| 207 |
+
|
| 208 |
+
inputs = tokenizer("Create a React button component", return_tensors="pt")
|
| 209 |
+
outputs = model.generate(**inputs, max_new_tokens=512)
|
| 210 |
+
print(tokenizer.decode(outputs[0]))
|
| 211 |
+
```
|
| 212 |
+
|
| 213 |
+
### Using vLLM
|
| 214 |
+
|
| 215 |
+
```bash
|
| 216 |
+
python -m vllm.entrypoints.openai.api_server \
|
| 217 |
+
--model metadev7/metadev-7b \
|
| 218 |
+
--dtype bfloat16
|
| 219 |
+
```
|
| 220 |
+
|
| 221 |
+
### Using Docker
|
| 222 |
+
|
| 223 |
+
```bash
|
| 224 |
+
docker pull metadev7/metadev-7b
|
| 225 |
+
docker run -p 8000:8000 --gpus all metadev7/metadev-7b
|
| 226 |
+
```
|
| 227 |
+
|
| 228 |
+
---
|
| 229 |
+
|
| 230 |
+
## Training
|
| 231 |
+
|
| 232 |
+
### Data Sources
|
| 233 |
+
- Curated GitHub repositories (⭐100+)
|
| 234 |
+
- Official framework documentation
|
| 235 |
+
- Stack Overflow (verified answers)
|
| 236 |
+
- Security-focused code reviews
|
| 237 |
+
- Production codebases (anonymized)
|
| 238 |
+
|
| 239 |
+
### Training Configuration
|
| 240 |
+
- **Method**: QLoRA with 4-bit quantization
|
| 241 |
+
- **LoRA Rank**: 64
|
| 242 |
+
- **Learning Rate**: 2e-4
|
| 243 |
+
- **Batch Size**: 4 (gradient accumulation: 4)
|
| 244 |
+
- **Epochs**: 3
|
| 245 |
+
- **Optimizer**: AdamW with cosine scheduler
|
| 246 |
+
|
| 247 |
+
---
|
| 248 |
+
|
| 249 |
+
## Limitations
|
| 250 |
+
|
| 251 |
+
- Optimized for web development (React, Node.js, Python, TypeScript)
|
| 252 |
+
- May require guidance for niche frameworks
|
| 253 |
+
- Not optimized for mobile (Swift/Kotlin) or game development
|
| 254 |
+
- Knowledge cutoff: October 2024
|
| 255 |
+
|
| 256 |
+
---
|
| 257 |
+
|
| 258 |
+
## License
|
| 259 |
+
|
| 260 |
+
MetaDev-7B is released under the **Llama 2 Community License**.
|
| 261 |
+
|
| 262 |
+
- ✅ Commercial use allowed
|
| 263 |
+
- ✅ Modification allowed
|
| 264 |
+
- ✅ Distribution allowed
|
| 265 |
+
- ⚠️ Must include original license
|
| 266 |
+
- ⚠️ 700M+ MAU requires special license from Meta
|
| 267 |
+
|
| 268 |
+
---
|
| 269 |
+
|
| 270 |
+
## Citation
|
| 271 |
+
|
| 272 |
+
```bibtex
|
| 273 |
+
@software{metadev2024,
|
| 274 |
+
title={MetaDev-7B: A Specialized Code Generation Model for Web Development},
|
| 275 |
+
author={MetaDev AI Team},
|
| 276 |
+
year={2024},
|
| 277 |
+
url={https://huggingface.co/metadev7/metadev-7b}
|
| 278 |
+
}
|
| 279 |
+
```
|
| 280 |
+
|
| 281 |
+
---
|
| 282 |
+
|
| 283 |
+
## Contact
|
| 284 |
+
|
| 285 |
+
- **Website**: [metadev.c](https://metadev.c)
|
| 286 |
+
- **GitHub**: [github.com/metadev-xi/metadev7](https://github.com/metadev-xi/metadev7)
|
| 287 |
+
- **Twitter**: [@metadevxi](https://twitter.com/metadevxi)
|
| 288 |
+
- **Email**: contact@metadev.c
|