| Basic Usage | |
| from transformers import BertTokenizer, AutoModelForTokenClassification | |
| from transformers import pipeline | |
| tokenizer = BertTokenizer.from_pretrained('bert-base-cased') | |
| model = AutoModelForTokenClassification.from_pretrained("ctrlbuzz/bert-addresses") | |
| nlp = pipeline("ner", model=model, tokenizer=tokenizer) | |
| example = "While Maria was representing Johnson & Associates at a conference in Spain, she mailed me a letter from her new office at 123 Elm St., Apt. 4B, Springfield, IL.", | |
| ner_results = nlp(example) | |
| print(ner_results) |