Shoriful025/CODE_SUMMARIZER

Code Summarizer

Overview

This model is a fine-tuned T5 model specialized in generating concise summaries of code snippets. It processes source code in various programming languages and produces natural language descriptions of the code's functionality, structure, and key components. Ideal for documentation and code review processes.

Model Architecture

The model is based on the T5 (Text-to-Text Transfer Transformer) architecture, configured as an encoder-decoder with 12 layers each. It has a hidden size of 768 and 12 attention heads per layer. The model treats summarization as a text-to-text task, prefixing inputs with "summarize: " for optimal performance.

Intended Use

This model is intended for software development tools, including:

• Automatically generating docstrings for functions and classes.
• Code review platforms to provide quick overviews of changes.
• Educational tools for explaining code examples to learners.

Integration is straightforward with the Hugging Face Transformers library. Example usage:

from transformers import pipeline

summarizer = pipeline("summarization", model="your-username/code-summarizer")
result = summarizer("def add(a, b): return a + b")
print(result)