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Graphcodebert Base
A Transformer-based graph-structured pretrained model specifically designed for programming languages, combining code sequences with data flow information.
Downloads 59.23k
Release Time : 3/2/2022
Model Overview
GraphCodeBERT is a pretrained model for programming languages that enhances performance in code understanding and generation tasks by simultaneously considering code sequences and data flow information.
Model Features
Graph Structure Encoding
Combines code sequences with data flow graph information to enhance understanding of code logic
Multilingual Support
Supports processing code in six mainstream programming languages
Long Sequence Handling
Supports sequences up to 512 characters in length, suitable for processing complex code
Model Capabilities
Code understanding
Code generation
Code search
Code documentation generation
Use Cases
Software Development
Code Auto-Completion
Predicts and generates code snippets based on context
Improves development efficiency
Code Search
Matches relevant code snippets based on natural language queries
Increases code reuse rate
Education
Programming Learning Assistance
Generates code explanations and documentation
Helps beginners understand code logic
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