token-classification address-NER NER bert-base-uncased

City-Country-NER

A bert-base-uncased model finetuned on a custom dataset to detect Country and City names from a given sentence.

Custom Dataset

We weakly supervised the Ultra-Fine Entity Typing dataset to include the City and Country information. We also did some extra preprocessing to remove false labels.

The model predicts 3 different tags: OTHER, CITY and COUNTRY

How to use the finetuned model?

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("ml6team/bert-base-uncased-city-country-ner")

model = AutoModelForTokenClassification.from_pretrained("ml6team/bert-base-uncased-city-country-ner")

from transformers import pipeline

nlp = pipeline('ner', model=model, tokenizer=tokenizer, aggregation_strategy="simple")
nlp("My name is Kermit and I live in London.")