Code Trans T5 Base Commit Generation

🚀 CodeTrans Model for Git Commit Message Generation

A pre - trained model on git commit using the T5 base model architecture, designed to generate accurate git commit messages.

🚀 Quick Start

This CodeTrans model is a pre - trained model on git commit, utilizing the t5 - base model architecture. It was first released in this repository. This model is trained on tokenized git commits and performs best with such input.

✨ Features

• Based on the t5 - base model with its own SentencePiece vocabulary model.
• Trained using single - task training on the Git Commit Message Generation dataset.
• Can generate git commit messages for commit changes and be fine - tuned on other relevant tasks.
• Can handle unparsed and untokenized commit changes, but performs better with tokenized input.

📦 Installation

No specific installation steps are provided in the original README.

💻 Usage Examples

Basic Usage

Here is how to use this model to generate git commit messages using the Transformers SummarizationPipeline:

from transformers import AutoTokenizer, AutoModelWithLMHead, SummarizationPipeline

pipeline = SummarizationPipeline(
    model=AutoModelWithLMHead.from_pretrained("SEBIS/code_trans_t5_base_commit_generation"),
    tokenizer=AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_commit_generation", skip_special_tokens=True),
    device=0
)

tokenized_code = "new file mode 100644 index 000000000 . . 892fda21b Binary files / dev / null and b / src / plugins / gateway / lib / joscar . jar differ"
pipeline([tokenized_code])

You can run this example in colab notebook.

📚 Documentation

Model Description

This CodeTrans model is based on the t5 - base model. It has its own SentencePiece vocabulary model and was trained using single - task training on the Git Commit Message Generation dataset.

Intended Uses & Limitations

The model can be used to generate git commit messages for commit changes or be fine - tuned on other relevant tasks. It can handle unparsed and untokenized commit changes, but the performance is better when the changes are tokenized.

🔧 Technical Details

The supervised training tasks datasets can be downloaded from Link

📄 License

No license information is provided in the original README.

Evaluation Results

For the git commit message generation task, different models achieve the following results on different programming languages (in BLEU score):

Test results:

Created by Ahmed Elnaggar | LinkedIn and Wei Ding | LinkedIn