load pretrained NAACL Transformer

load_pretrained_transformer.py

from pytorch_transformers import cached_path

# download pre-trained model and config
state_dict = torch.load(cached_path("https://s3.amazonaws.com/models.huggingface.co/"
                                    "naacl-2019-tutorial/model_checkpoint.pth"), map_location='cpu')

config = torch.load(cached_path("https://s3.amazonaws.com/models.huggingface.co/"
                                        "naacl-2019-tutorial/model_training_args.bin"))

# init model: Transformer base + classifier head
model = TransformerWithClfHead(config=config, fine_tuning_config=finetuning_config).to(finetuning_config.device)
model.load_state_dict(state_dict, strict=False)