Update README.md

README.md

@@ -72,34 +72,22 @@ Below is an example of how to use the model with the Hugging Face Transformers l
 ```python
 from transformers import pipeline
 
-ner = pipeline("token-classification", model="IsmaelMousa/modernbert-ner-conll2003", aggregation_strategy="simple")
+ner = pipeline(task="token-classification", model="IsmaelMousa/modernbert-ner-conll2003", aggregation_strategy="max")
 
-ner("Hi, I'm Ismael Mousa from Palestine working for NVIDIA inc.")
+results = ner("Hi, I'm Ismael Mousa from Palestine working for NVIDIA inc.")
+
+for entity in results:
+    for key, value in entity.items():
+        if key == "entity_group":
+            print(f"{entity['word']} => {entity[key]}")
 ```
 
 Results:
 
 ```
-[{'entity_group': 'PER',
-  'score': 0.5670353,
-  'word': ' Is',
-  'start': 7,
-  'end': 10},
- {'entity_group': 'PER',
-  'score': 0.90173304,
-  'word': 'mael Mousa',
-  'start': 10,
-  'end': 20},
- {'entity_group': 'LOC',
-  'score': 0.992393,
-  'word': ' Palestine',
-  'start': 25,
-  'end': 35},
- {'entity_group': 'ORG',
-  'score': 0.75373423,
-  'word': ' NVIDIA inc',
-  'start': 47,
-  'end': 58}]
+Ismael Mousa => PER
+Palestine => LOC
+NVIDIA => ORG
 ```
 
 ### Training hyperparameters