model_interface.tokenization_bart import AMRBartTokenizer # We use our own tokenizer to process AMRs model = BartForConditionalGeneration.from_pretrained("xfbai/AMRBART-large-finetuned-AMR3.0-AMRParsing-v2") tokenizer = AMRBartTokenizer.from_pretrained("xfbai/AMRBART-large-finetuned-AMR3.0-AMR...
(2022/10/16) release the AMRBART-v2 model which is simpler, faster, and stronger. Requirements python 3.8 pytorch 1.8 transformers 4.21.3 datasets 2.4.0 Tesla V100 or A100 We recommend to use conda to manage virtual environments: conda env update --name <env> --file requirements.yml ...