Cannot load any Pre-Trained Model

[Mahyar-Ali]

I created an extractive summarizer using the "extractive" module and the parser(almost all default values).
from extractive import ExtractiveSummarizer
summarizer = ExtractiveSummarizer
args = build_parser()
model = summarizer(hparams=args)
checkpoint = torch.load( "epoch=3.ckpt", map_location=lambda storage, loc: storage )
model.load_state_dict(checkpoint["state_dict"])
When I try to load a state dict in a model, it raises an error, "RuntimeError: Error(s) in loading state_dict for ExtractiveSummarizer:
Missing key(s) in state_dict: "word_embedding_model.embeddings.position_ids"."

Sometimes with the missing keys error, it produces IncompatibleKeys and shape mismatch error.

Note: The model checkpoint file is of the same model name provided in the parser.
for build_parser, I just extracted all the arguments from the main.py file and placed it in a function.

It would be nice if you can document the necessary steps to load a pretrained model in the official documentation. As of now, I can't find any.
Thanks!

[HHousen]

I believe this is a duplicate of #12. Essentially, it is a problem with the update from 3.0.2 to 3.1.0 of huggingface/transformers. The problem is being discussed at huggingface/transformers#6882. While they work on a fix, you can install the previous version of huggingface/transformers by running pip install -U transformers==3.0.2.

The steps to load a pretrained model are in the documentation. Please see https://transformersum.readthedocs.io/en/latest/general/getting-started.html#programmatically. Simply import the ExtractiveSummarizer or AbstractiveSummarizer pytorch_lightning module and call the load_from_checkpoint() function with the path to the model checkpoint file.

[Mahyar-Ali]

Thanks....!