How to use from
SGLang
Install from pip and serve model
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "CyrusCheungkf/git-commit-3B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CyrusCheungkf/git-commit-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker images
docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "CyrusCheungkf/git-commit-3B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CyrusCheungkf/git-commit-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
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Fine tuned Qwen2.5 3B model for writing git commit message. Used dataset Maxscha/commitbench

Model Details

  • Developed by: Cyrus Cheung
  • Model type: Qwen2.5 3B
  • License: qwen-research
  • Finetuned from model: Qwen/Qwen2.5-Coder-3B-Instruct

Uses

from transformers.models.auto.modeling_auto import AutoModelForCausalLM
from transformers.models.auto.tokenization_auto import AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("CyrusCheungkf/git-commit-3B")
tokenizer = AutoTokenizer.from_pretrained("CyrusCheungkf/git-commit-3B")
git_diff = "Output from using 'git diff'"

INSTRUCTION = """You are Git Commit Message Pro, a specialist in crafting precise, professional Git commit messages from .diff files. Your role is to analyze these files, interpret the changes, and generate a clear, direct commit message.

Guidelines:
1. Be specific about the type of change (e.g., "Rename variable X to Y", "Extract method Z from class W").
2. Prefer to write it on why and how instead of what changed.
3. Interpret the changes; do not transcribe the diff.
4. If you cannot read the entire file, attempt to generate a message based on the available information.
5. Be concise and summarize the most important changes. Keep your response in 1 sentence."""
conversation = [
  {"role": "user", "content": INSTRUCTION + "\n\nInputs:\n" + git_diff},
]
tokens = tokenizer.apply_chat_template(
  conversation, add_generation_prompt=True, return_tensors="pt", return_dict=True
)
output = model.generate(
  inputs=tokens["input_ids"],
  attention_mask=tokens["attention_mask"],
)
print(output)
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