| | --- |
| | license: apache-2.0 |
| | tags: |
| | - code-review |
| | - javascript |
| | - mlx |
| | - gguf |
| | - qwen2.5-coder |
| | base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct |
| | --- |
| | |
| | # AI Code Review Model - Javascript |
| |
|
| | This is a fine-tuned code review model specialized for **Javascript** code analysis. |
| |
|
| | ## Model Details |
| |
|
| | - **Base Model**: Qwen/Qwen2.5-Coder-1.5B-Instruct |
| | - **Training Method**: LoRA fine-tuning with MLX |
| | - **Format**: GGUF (Q4_K_M quantization) |
| | - **Target Language**: Javascript |
| | - **Purpose**: Automated code review for CI/CD pipelines |
| |
|
| | ## Usage |
| |
|
| | ### Docker (Recommended) |
| |
|
| | ```bash |
| | docker pull ghcr.io/iq2i/ai-code-review:javascript-latest |
| | docker run --rm -v $(pwd):/workspace ghcr.io/iq2i/ai-code-review:javascript-latest /workspace/src |
| | ``` |
| |
|
| | ### llama.cpp |
| |
|
| | ```bash |
| | # Download the model |
| | wget https://huggingface.co/loicsapone/ai-code-review-javascript/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 JSON structured code reviews: |
| |
|
| | ```json |
| | { |
| | "summary": "Brief overview of code quality", |
| | "score": 8, |
| | "issues": [ |
| | { |
| | "type": "bug", |
| | "severity": "medium", |
| | "line": 42, |
| | "description": "Potential null pointer", |
| | "suggestion": "Add null check" |
| | } |
| | ], |
| | "positive_points": [ |
| | "Good error handling", |
| | "Clear variable names" |
| | ] |
| | } |
| | ``` |
| |
|
| | ## Training |
| |
|
| | This model was trained on curated Javascript code review examples using: |
| | - MLX framework for Apple Silicon acceleration |
| | - LoRA adapters (r=8, alpha=16) |
| | - Custom dataset of real-world code issues |
| |
|
| | For training details, see the [GitHub repository](https://github.com/iq2i/ai-code-review). |
| |
|
| | ## Limitations |
| |
|
| | - Optimized for Javascript syntax and best practices |
| | - May not catch all edge cases or security vulnerabilities |
| | - Should be used as a supplementary tool, not a replacement for human review |
| |
|
| | ## License |
| |
|
| | Apache 2.0 |
| |
|
| | ## Citation |
| |
|
| | ```bibtex |
| | @software{ai_code_review_javascript, |
| | title = {AI Code Review Model for Javascript}, |
| | author = {IQ2i Team}, |
| | year = {2025}, |
| | url = {https://github.com/iq2i/ai-code-review} |
| | } |
| | ``` |
| |
|