CodeTrans T5-Small Python Source Code Summarization
| Property | Value |
|---|---|
| Model Architecture | T5-Small |
| Task | Source Code Summarization |
| Language | Python |
| BLEU Score | 8.45 |
| Author | SEBIS |
| Model URL | Hugging Face |
What is code_trans_t5_small_source_code_summarization_python?
This is a specialized T5-small-based model designed specifically for generating documentation from Python source code. It has been trained on tokenized Python functions and utilizes its own SentencePiece vocabulary model for optimal performance in code summarization tasks.
Implementation Details
The model is implemented using the T5-small architecture and has been trained specifically for single-task performance on Python code summarization. It can process both raw and tokenized Python code, though it performs better with tokenized input.
- Built on T5-small architecture
- Custom SentencePiece vocabulary
- Single-task training focus
- Supports both tokenized and untokenized Python code
Core Capabilities
- Generation of Python function documentation
- Source code summarization
- Compatible with Transformers SummarizationPipeline
- Can be fine-tuned for other Python code tasks
Frequently Asked Questions
Q: What makes this model unique?
This model is specifically optimized for Python code summarization, using a specialized vocabulary and training approach. It achieves a BLEU score of 8.45 on Python code summarization tasks, making it suitable for automated documentation generation.
Q: What are the recommended use cases?
The model is best suited for automatically generating documentation for Python functions, especially when working with tokenized code. It can also serve as a foundation for fine-tuning on related Python code tasks.
