Text Generation
Transformers
Safetensors
GGUF
English
qwen2
git
conversational
text-generation-inference
Instructions to use CyrusCheungkf/git-commit-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CyrusCheungkf/git-commit-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CyrusCheungkf/git-commit-3B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CyrusCheungkf/git-commit-3B") model = AutoModelForCausalLM.from_pretrained("CyrusCheungkf/git-commit-3B") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - llama-cpp-python
How to use CyrusCheungkf/git-commit-3B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="CyrusCheungkf/git-commit-3B", filename="model.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use CyrusCheungkf/git-commit-3B with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf CyrusCheungkf/git-commit-3B # Run inference directly in the terminal: llama-cli -hf CyrusCheungkf/git-commit-3B
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf CyrusCheungkf/git-commit-3B # Run inference directly in the terminal: llama-cli -hf CyrusCheungkf/git-commit-3B
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf CyrusCheungkf/git-commit-3B # Run inference directly in the terminal: ./llama-cli -hf CyrusCheungkf/git-commit-3B
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf CyrusCheungkf/git-commit-3B # Run inference directly in the terminal: ./build/bin/llama-cli -hf CyrusCheungkf/git-commit-3B
Use Docker
docker model run hf.co/CyrusCheungkf/git-commit-3B
- LM Studio
- Jan
- vLLM
How to use CyrusCheungkf/git-commit-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CyrusCheungkf/git-commit-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/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
docker model run hf.co/CyrusCheungkf/git-commit-3B
- SGLang
How to use CyrusCheungkf/git-commit-3B with 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?" } ] }' - Ollama
How to use CyrusCheungkf/git-commit-3B with Ollama:
ollama run hf.co/CyrusCheungkf/git-commit-3B
- Unsloth Studio new
How to use CyrusCheungkf/git-commit-3B with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CyrusCheungkf/git-commit-3B to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CyrusCheungkf/git-commit-3B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CyrusCheungkf/git-commit-3B to start chatting
- Pi new
How to use CyrusCheungkf/git-commit-3B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf CyrusCheungkf/git-commit-3B
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "CyrusCheungkf/git-commit-3B" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use CyrusCheungkf/git-commit-3B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf CyrusCheungkf/git-commit-3B
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default CyrusCheungkf/git-commit-3B
Run Hermes
hermes
- Docker Model Runner
How to use CyrusCheungkf/git-commit-3B with Docker Model Runner:
docker model run hf.co/CyrusCheungkf/git-commit-3B
- Lemonade
How to use CyrusCheungkf/git-commit-3B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull CyrusCheungkf/git-commit-3B
Run and chat with the model
lemonade run user.git-commit-3B-{{QUANT_TAG}}List all available models
lemonade list
| library_name: transformers | |
| tags: | |
| - git | |
| datasets: | |
| - Maxscha/commitbench | |
| language: | |
| - en | |
| base_model: | |
| - Qwen/Qwen2.5-Coder-3B-Instruct | |
| pipeline_tag: text-generation | |
| # Model Card for Model ID | |
| 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 | |
| ```python | |
| 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) | |
| ``` |