CodeBERT-CPP
| Property | Value |
|---|---|
| Author | neulab |
| Base Model | microsoft/codebert-base-mlm |
| Training Steps | 1,000,000 |
| Paper | CodeBERTScore Paper |
| Downloads | 40,672 |
What is codebert-cpp?
CodeBERT-CPP is a specialized language model trained specifically for C++ code understanding and analysis. Built upon Microsoft's CodeBERT base model, it has been fine-tuned on the codeparrot/github-code-clean dataset with a focus on masked language modeling tasks for C++ code.
Implementation Details
The model was trained for 1 million steps with a batch size of 32, specifically optimized for C++ code analysis. It implements the RoBERTa architecture and is designed to work seamlessly with the CodeBERTScore framework for evaluating code generation.
- Trained on clean C++ code from GitHub
- Optimized for masked language modeling tasks
- Integrated with CodeBERTScore evaluation framework
- Built on PyTorch framework
Core Capabilities
- C++ code understanding and analysis
- Masked language modeling for code completion
- Code evaluation and scoring
- Integration with transformer-based architectures
Frequently Asked Questions
Q: What makes this model unique?
This model is specifically optimized for C++ code analysis and evaluation, with extensive training on clean GitHub code. It's particularly designed for use with CodeBERTScore, making it ideal for evaluating code generation quality.
Q: What are the recommended use cases?
The model is best suited for C++ code evaluation, analysis, and scoring using the CodeBERTScore framework. It can be used for assessing code generation quality, code completion, and other C++-specific programming tasks.
