Instructions to use seniruk/commitGen-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use seniruk/commitGen-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="seniruk/commitGen-gguf",
	filename="commitGen.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use seniruk/commitGen-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf seniruk/commitGen-gguf
# Run inference directly in the terminal:
llama-cli -hf seniruk/commitGen-gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf seniruk/commitGen-gguf
# Run inference directly in the terminal:
llama-cli -hf seniruk/commitGen-gguf

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 seniruk/commitGen-gguf
# Run inference directly in the terminal:
./llama-cli -hf seniruk/commitGen-gguf

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 seniruk/commitGen-gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf seniruk/commitGen-gguf

Use Docker

docker model run hf.co/seniruk/commitGen-gguf

LM Studio
Jan
Ollama
How to use seniruk/commitGen-gguf with Ollama:
```
ollama run hf.co/seniruk/commitGen-gguf
```

Unsloth Studio new

How to use seniruk/commitGen-gguf 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 seniruk/commitGen-gguf 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 seniruk/commitGen-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for seniruk/commitGen-gguf to start chatting

Pi new

How to use seniruk/commitGen-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf seniruk/commitGen-gguf

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": "seniruk/commitGen-gguf"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use seniruk/commitGen-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf seniruk/commitGen-gguf

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 seniruk/commitGen-gguf

Run Hermes

hermes

Docker Model Runner
How to use seniruk/commitGen-gguf with Docker Model Runner:
```
docker model run hf.co/seniruk/commitGen-gguf
```

Lemonade

How to use seniruk/commitGen-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull seniruk/commitGen-gguf

Run and chat with the model

lemonade run user.commitGen-gguf-{{QUANT_TAG}}

List all available models

lemonade list

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Hi, I’m Seniru Epasinghe 👋

I’m an AI undergraduate and an AI enthusiast, working on machine learning projects and open-source contributions.
I enjoy exploring AI pipelines, natural language processing, and building tools that make development easier.

🌐 Connect with me

Purpose

Used for generating high quality commit messages for a given git difference

Model Description

Generated by fine tuning Qwen2.5-Coder-1.5B-Instruct on bigcode/commitpackft dataset for 2 epochs Trained on a total of 277 Languages Achieved a final training loss in the range of 1- 1.7 (due to data set not containing equal data rows for each language) For common languages(python, java ,javascripts,c etc) loss went for a minimum of 1.0335

Environmental Impact

Hardware Type: geforce RTX 4060 TI - 16GB]
Hours used: 10 Hours
Cloud Provider: local

Results

Inference

from llama_cpp import Llama

llm = Llama.from_pretrained(
    repo_id="seniruk/commitGen-gguf",
    filename="commitGen.gguf",
)

diff="" #the git difference
instruction= "" #the instruction --> 'create a commit message for given git difference'

prompt = "{}{}".format(instruction,diff)

messages = [
    {"role": "system", "content": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant."},
    {"role": "user", "content": prompt}
]

output = llm.create_chat_completion(
    messages=messages,
    temperature=0.5
)

llm_message = output['choices'][0]['message']['content']

print(llm_message)

Downloads last month: -

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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