Comments (2)
If you want to fill in [MASK]
tokens then it's necessary initialize batcher = KnowBertBatchifier(archive_file, masking_strategy='full_mask')
. This creates batches in the same was as during pretraining. After doing so, I get ['france', 'germany', 'belgium', 'europe', 'canada', 'italy', 'paris', 'spain', 'russia', 'algeria']
as the top 10 predictions for 'Paris is located in [MASK].'
from kb.
Thanks for your quick reply! I just noticed that full_mask
is not the default and using it can make correct predictions!
from kb.
Related Issues (20)
- Getting hundreds of Warning messages HOT 4
- RuntimeError: received 0 items of ancdata HOT 6
- How many unlabeled data are needed to pretrain knowbert?
- Train with multilingual cased BERT
- What is entity_world_path used for ?
- 【freshman】how to apply this model into a binary classification work. HOT 1
- Knowbert based on other HuggingFace BERT models. HOT 1
- Different F1 scores with the same hyperparameters and same random seeds HOT 1
- json.decoder.JSONDecodeError HOT 1
- Having trouble running the "Getting started" section (even the tests do not run) HOT 5
- Problem with evaluating tacred
- How to inject knowledge into other pre-trained models HOT 2
- Can't seem to replicate perplexity for KnowBert-Wiki & KnowBert-W+W HOT 5
- what is the version of packages in requirements.txt HOT 5
- Expecting property name enclosed in double quotes HOT 4
- kg_tuple is not a registered name for Model
- Download link for downstream tasks
- Pre-trained model HOT 1
- Unable to pass the pytests HOT 2
- unable to install the environment HOT 2
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