SEBIS/code_trans_t5_small_source_code_summarization_python_multitask

The CodeTrans model is based on the t5-small model architecture . It has its own SentencePiece vocabulary model . It could be used to generate the description for the python function or be fine-tuned on other python code tasks . The model was trained on a single TPU Pod V3-8 for 300,000 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 optimizer used is AdaFactor with inverse square root learning rate schedule for pre-training. The model can be used on unparsed and untokenized python code. It can,