hf_ez_token_classification | R Documentation |
Usually used for sentence parsing, either grammatical, or Named Entity Recognition (NER) to understand keywords contained within text.
hf_ez_token_classification( model_id = "dbmdz/bert-large-cased-finetuned-conll03-english", use_api = FALSE )
model_id |
A model_id. Run hf_search_models(...) for model_ids. Defaults to 'dbmdz/bert-large-cased-finetuned-conll03-english'. |
use_api |
Whether to use the Inference API to run the model (TRUE) or download and run the model locally (FALSE). Defaults to FALSE |
A text2text generation object
https://huggingface.co/docs/api-inference/detailed_parameters#token-classification-task
## Not run: # Load the default named entity recognition model ez <- hf_ez_token_classification() # Run NER. Note how the full name is aggregated into one named entity. ez$infer(string = "My name is Sarah Jessica Parker but you can call me Jessica", aggregation_strategy = 'simple') # Run NER without aggregation. Note how the full name is separated into distinct named entities. ez$infer(string = "My name is Sarah Jessica Parker but you can call me Jessica", aggregation_strategy = 'none') ## End(Not run)
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