CuBERT

2000년 도입 · 논문 3편에서 사용

CuBERT, or Code Understanding BERT, is a BERT based model for code understanding. In order to achieve this, the authors curate a massive corpus of Python programs collected from GitHub. GitHub projects are known to contain a large amount of duplicate code. To avoid biasing the model to such duplicated code, authors perform deduplication using the method of Allamanis (2018). The resulting corpus has 7.4 million files with a total of 9.3 billion tokens (16 million unique).

출처: Learning and Evaluating Contextual Embedding of Source Code

소개 논문: Learning and Evaluating Contextual Embedding of Source Code