CodeBERT Python
| Property | Value |
|---|---|
| Author | neulab |
| Downloads | 372,445 |
| Research Paper | View Paper |
| Tags | Fill-Mask, Transformers, PyTorch, RoBERTa |
What is codebert-python?
CodeBERT Python is a specialized language model based on microsoft/codebert-base-mlm, specifically trained on Python code from the codeparrot/github-code-clean dataset. The model underwent extensive training for 1,000,000 steps with a batch size of 32, focusing on masked language modeling tasks.
Implementation Details
This model is primarily designed for use in CodeBERTScore, a framework for evaluating code generation. It leverages the RoBERTa architecture and has been fine-tuned specifically for understanding and processing Python code.
- Built on microsoft/codebert-base-mlm architecture
- Trained on clean Python code from GitHub
- Optimized for masked language modeling
- Integrated with CodeBERTScore evaluation framework
Core Capabilities
- Python code understanding and evaluation
- Masked language modeling for code completion
- Code similarity assessment
- Integration with CodeBERTScore framework
- Support for code generation evaluation
Frequently Asked Questions
Q: What makes this model unique?
This model stands out due to its specific focus on Python code and its integration with CodeBERTScore, making it particularly effective for evaluating code generation tasks and understanding Python code patterns.
Q: What are the recommended use cases?
The model is primarily recommended for evaluating code generation quality using CodeBERTScore, code completion tasks, and analyzing Python code similarity. It's particularly useful in research and development contexts where code quality assessment is crucial.
