---
language:
  - en
license: mit
library_name: transformers
tags:
  - conventional-commits
  - qwen2.5-coder
  - text-generation
  - code-llm
  - fine-tuned
---

# Qwen Commit Merged - Conventional Commit Message Generator

Generates conventional commit messages from git diffs using a fine-tuned Qwen2.5-Coder-3B model. This is a standalone merged model (LoRA adapters merged into base model) ready for direct use.

## Model Details

- **Model**: Qwen2.5-Coder-3B fine-tuned on conventional commits
- **Fine-tuning Method**: QLoRA (4-bit quantized, rank=8, alpha=16)
- **Training Data**: 210 real conventional commits from open-source repositories
- **Model Size**: ~3B parameters
- **Format**: Merged model (no base model required)

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load merged model directly
model = AutoModelForCausalLM.from_pretrained(
    "Pavloffm/qwen-commit-merged",
    torch_dtype="auto",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("Pavloffm/qwen-commit-merged")

# Generate commit message
diff = """diff --git a/src/main.py b/src/main.py
index 1234567..abcdefg 100644
--- a/src/main.py
+++ b/src/main.py
@@ -1,3 +1,5 @@
+def new_feature():
+    pass
"""

messages = [{"role": "user", "content": f"Generate a conventional commit message for this diff:\n{diff}"}]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
outputs = model.generate(inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Training

- **Base Model**: Qwen/Qwen2.5-Coder-3B-Instruct
- **Epochs**: 2
- **Learning rate**: 1.5e-4
- **LoRA rank**: 8, alpha: 16
- **Training examples**: 210

## License

MIT License