How to implement pretrained model from the output folder
moh-yani opened this issue · 2 comments
I have run the run_bert_classifier.py. That process outputs a folder name output_FB15K. It contains *.json; *.bin and vocab.txt files. The question is how I can implement those files to check whether a given triple is correct or not?
For instance, if I give a triple 453 1347 37, how I can check if that triple is correct or not. Anyone could give an example script to do that?
The script should be similar to line 777--828 in run_bert_triple_classifier.py.
You need to assign your test triple 453 1347 37 to eval_examples in line 777 (which will have only one example),
then preds in line 828 will be the label which indicates if the triple is correct or not.
If I assign the triple to eval_example in line 777, does it mean I just need to assign the Ids (such as 453 1347 37) or completely assign the mids in the test.tsv file (for instance: /m/01qscs /award/award_nominee/award_nominations./award/award_nomination/award /m/02x8n1n)?