SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask

The CodeTrans model is based on the t5-large model architecture . It has its own SentencePiece vocabulary model . It was trained on a single TPU Pod V3-8 for 80,000 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 . The model 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 code, but the performance should be better if the python code is tokenized . For example, this is how to use,