SEBIS/code_trans_t5_small_source_code_summarization_sql_transfer_learning_finetune

The CodeTrans model is based on the t5-small model architecture . It has its own SentencePiece vocabulary model . It used transfer-learning pre-training on 7 unsupervised datasets in the software development domain . It is then fine-tuned on the source code summarization task for the sql code snippets . This model is trained on tokenized sql code functions: it works best with tokenized . It can be used on unparsed and untokenized . However, if the . sql code is . tokenized, the performance should be better. It has a total of approximately 220M parameters and was trained using the encoder-decoder architecture. The optimizer,