Update README.md

README.md

@@ -35,19 +35,23 @@ It achieves the following results on the evaluation set:
 - Loss: 0.1343
 - F1: 0.8608
 
-## Model description
+#### How to use
 
-More information needed
+You can use this model with Transformers *pipeline* for NER.
 
-## Intended uses & limitations
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
 
-More information needed
+tokenizer = AutoTokenizer.from_pretrained("Tirendaz/roberta-base-NER")
+model = AutoModelForTokenClassification.from_pretrained("Tirendaz/roberta-base-NER")
 
-## Training and evaluation data
+nlp = pipeline("ner", model=model, tokenizer=tokenizer)
+example = "My name is Wolfgang and I live in Berlin"
 
-More information needed
-
-## Training procedure
+ner_results = nlp(example)
+print(ner_results)
+```
 
 ### Training hyperparameters