SEBIS/code_trans_t5_base_source_code_summarization_python_multitask

The CodeTrans model is based on the t5-base model . It has its own SentencePiece vocabulary model . The model is trained on tokenized python code functions . It could be used to generate the description for the python function or be fine-tuned on other python code tasks . It can be used on unparsed and untokenized python codes, but if python code is tokenized, the performance should be better . It was trained on a single TPU Pod V3-8 for 260,000 steps in total, using sequence length 512 (batch size 4096) It has a total of approximately 220M parameters and was trained using the encoder-decoder architecture,