---
tags:
- gguf
- llama.cpp
- unsloth
---

# ZPT-Commit-1.2b-Instruct : Git Commit Message Generator

## 🚀 Overview

**ZPT-Commit-1.2B-Instruct** is a highly specialized, 1.2 Billion parameter language model engineered specifically to automate and improve the creation of descriptive and professional Git commit messages.

Fine-tuned from the robust **LiquidAI LFM 2.5 1.2b** base model, this model uses the `Tavernari/git-commit-message-dt` dataset to excel at analyzing code diffs and transforming technical changes into clear, actionable commit summaries. It is designed to streamline development workflows by ensuring a clean, searchable, and informative git history.

---

## 🛠️ Technical Specifications

This model is provided in highly optimized formats for maximum efficiency across various hardware.

| Feature | Specification | Details |
| :--- | :--- | :--- |
| **Model Name** | ZPT-Commit-1.2B-Instruct | Specialized version for generating precise commit messages. |
| **Base Model** | LiquidAI LFM 2.5 1.2b | The foundational architecture. |
| **Training Data** | `Tavernari/git-commit-message-dt` | Dataset used to fine-tune the model on real-world code changes and commit patterns. |
| **Fine-tuning Framework** | Unsloth Studio | Trained 2x faster using the Unsloth optimization techniques. |
| **Model Size** | 1.2 Billion Parameters | Offers strong performance while maintaining a manageable footprint for deployment. |
| **Supported Formats** | GGUF, Quantized | Optimized for CPU/GPU inference via `llama.cpp`. |

---

## ⚙️ Performance & Implementation

The model has been converted and optimized to the **GGUF** format, allowing for highly efficient local deployment without needing massive GPU resources.

**Performance Benefits:**
*   **Unsloth Optimization:** The training process utilized Unsloth, enabling faster training cycles and an efficient model structure.
*   **GGUF Efficiency:** Quantized files ensure excellent inference speed and lower memory usage, making it ideal for CI/CD pipelines or local development environments.

**Available Model Files:**
The following optimized file is available for immediate use:
*   `LFM2.5-1.2B-Instruct.Q8_0.gguf`

---

## 💡 Use Cases

ZPT-Commit-1.2B-Instruct is designed to be a powerful aid in the software development lifecycle.

*   **Automated Commit History:** Automatically generating high-quality, structured commit messages directly from code diffs.
*   **Developer Workflow Integration:** Integrating into IDE extensions or CI/CD tools to enforce consistent commit message standards.
*   **Code Review Enhancement:** Providing context-rich summaries of changes, speeding up the review process.
*   **Clean Repository Management:** Maintaining a professional and easily traceable version control history.

---

## 💻 Installation & Usage

The model is designed to work seamlessly with the `llama.cpp` ecosystem.

**Dependencies:**
*   `llama.cpp` (for CPU/GPU inference)
*   `unsloth` (for initial conversion and optimization)

**CLI Usage:**
You can invoke the model using the following command structure. The model will require the code diff as input for the best results.

*   **Text-Only LLMs:**
    ```bash
    llama-cli -hf zmail-tech/ZPT-Commit-1.2B-Instruct --jinja
    ```
*   **Multimodal Models:**
    ```bash
    llama-mtmd-cli -hf zmail-tech/ZPT-Commit-1.2B-Instruct --jinja
    ```

---
***Note:** The model is named **Commit** as its primary and specialized function is the generation of Git commit messages. For full setup instructions, please refer to the [Unsloth AI GitHub](https://github.com/unslothai/unsloth) resources.*