Text Generation
Transformers
Safetensors
English
qwen2
llms
code
Java
code-smells
text-generation-inference
How to use from
vLLMUse Docker
docker model run hf.co/CodeAid/CouplingSmells-Detection-modelQuick Links
CodeAid Coupling Smells Detection Model (Qwen2.5-14B-Instruct Fine-Tuned)
This model is a fine-tuned version of Qwen2.5-14B-Instruct, specialized for detecting coupling smells in Java code. It was developed as part of the CodeAid project to assist developers in identifying code quality issues directly in their IDE.
π§ Model Purpose
The model identifies coupling-related code smells such as:
- Feature Envy
- Inappropriate Intimacy
- Message Chains
- Excessive Dependencies
It analyzes Java classes and their dependencies to detect architectural or design issues that increase coupling and reduce maintainability.
π§ Technical Details
- Base Model: Qwen2.5-14B-Instruct
- Fine-Tuning Method: QLoRA with LoRA adapters merged
- Format:
safetensors(merged) - Task Type: Text generation (instruction-based)
- Downloads last month
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Install from pip and serve model
# Install vLLM from pip: pip install vllm# Start the vLLM server: vllm serve "CodeAid/CouplingSmells-Detection-model"# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CodeAid/CouplingSmells-Detection-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'