Update README.md

README.md

@@ -22,7 +22,23 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-'''More information needed'''
+'''
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("jinhybr/distilroberta-ConLL2003")
+model = AutoModelForTokenClassification.from_pretrained("jinhybr/distilroberta-ConLL2003")
+
+nlp = pipeline("ner", model=model, tokenizer=tokenizer, grouped_entities=True)
+example = "My name is Tao Jin and live in Canada"
+ner_results = nlp(example)
+print(ner_results)
+
+[{'entity_group': 'PER', 'score': 0.99686015, 'word': ' Tao Jin', 'start': 11, 'end': 18}, {'entity_group': 'LOC', 'score': 0.9996836, 'word': ' Canada', 'start': 31, 'end': 37}]
+
+
+
+'''
 
 ## Intended uses & limitations