Update README.md

README.md

@@ -83,6 +83,17 @@ The **roberta-base-ca-cased-ner** is a Named Entity Recognition (NER) model for
 
 ## How to use
 
+```
+pipe = pipeline("ner", model="projecte-aina/multiner_ceil")
+example = "George Smith Patton fué un general del Ejército de los Estados Unidos en Europa durante la Segunda Guerra Mundial. "
+
+ner_entity_results = pipe(example, aggregation_strategy="simple")
+print(ner_entity_results)
+
+[{'entity_group': 'PER', 'score': 0.9983406, 'word': ' George Smith Patton', 'start': 0, 'end': 19}, {'entity_group': 'ORG', 'score': 0.99790734, 'word': ' Ejército de los Estados Unidos', 'start': 39, 'end': 69}, {'entity_group': 'LOC', 'score': 0.98424107, 'word': ' Europa', 'start': 73, 'end': 79}, {'entity_group': 'MISC', 'score': 0.9963934, 'word': ' Seg', 'start': 91, 'end': 94}, {'entity_group': 'MISC', 'score': 0.97889286, 'word': 'unda Guerra Mundial', 'start': 94, 'end': 113}]
+
+```
+
 
 ## Limitations and bias
 At the time of submission, no measures have been taken to estimate the bias embedded in the model. However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated.