SEBIS/code_trans_t5_large_source_code_summarization_python_multitask_finetune

The CodeTrans model is based on the t5-large model architecture . It has its own SentencePiece vocabulary model . It used multi-task training on 13 supervised tasks in the software development domain and 7 unsupervised datasets . It is then fine-tuned on the source code summarization task for python code snippets . The model could be used to generate the description for the python function . It can be used on unparsed and untokenized python code . It was trained using the encoder-decoder architecture and was trained on a single TPU Pod V3-8 for 500,000 steps in total, using sequence length 512 (batch size 256). It has,