---
license: apache-2.0
tags:
- code-review
- multi-language
- mlx
- gguf
- qwen2.5-coder
base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
---

# AI Code Review Model

Multi-language code review model optimized for automated code review in CI/CD pipelines.

## Model Details

- **Base Model**: Qwen/Qwen2.5-Coder-1.5B-Instruct
- **Training Method**: LoRA fine-tuning with MLX
- **Format**: GGUF (Q4_K_M quantization)
- **Purpose**: Automated code review for CI/CD pipelines

## Usage

### Docker (Recommended)

```bash
docker pull ghcr.io/iq2i/ai-code-review:latest

# Review your codebase
docker run --rm -v $(pwd):/workspace ghcr.io/iq2i/ai-code-review:latest /workspace/src
```

### llama.cpp

```bash
# Download the model
wget https://huggingface.co/iq2i/ai-code-review/resolve/main/model-Q4_K_M.gguf

# Run inference
./llama-cli -m model-Q4_K_M.gguf -p "Review this code: ..."
```

### Python (llama-cpp-python)

```python
from llama_cpp import Llama

llm = Llama(model_path="model-Q4_K_M.gguf")
output = llm("Review this code: ...", max_tokens=512)
print(output)
```

## Output Format

The model outputs concise text-based code reviews:

```
**SQL injection vulnerability**

User input is concatenated directly into a raw SQL query without parameterization or escaping.

Impact: An attacker can execute arbitrary SQL commands, potentially dumping the entire database, deleting data, or escalating privileges. For example: keyword=' OR '1'='1' -- would return all products.

Suggestion:
Use parameter binding: DB::select("SELECT * FROM products WHERE name LIKE ?", ['%' . $keyword . '%']) or better, use Eloquent: Product::where('name', 'like', '%' . $keyword . '%')->get()
```

## Training

- **Training examples**: 100+ real-world code issues
- **Format**: ChatML conversation format with concise reviews
- **Framework**: MLX for Apple Silicon acceleration
- **Method**: LoRA adapters (r=4, alpha=8)
- **Iterations**: 625

For training details, see the [GitHub repository](https://github.com/iq2i/ai-code-review).

## Limitations

- Should be used as a supplementary tool, not a replacement for human review
- May not catch all edge cases or security vulnerabilities
- Best results on common programming patterns and frameworks

## License

Apache 2.0

## Citation

```bibtex
@software{ai_code_review,
  title = {AI Code Review Model},
  author = {IQ2i Team},
  year = {2025},
  url = {https://github.com/iq2i/ai-code-review}
}
```