Create README.md

README.md

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+---
+pipeline_tag: token-classification
+tags:
+  - named-entity-recognition
+  - sequence-tagger-model
+widget:
+- text: "Numele meu este Amadeus Wolfgang și locuiesc în Berlin"
+inference:
+  parameters:
+    aggregation_strategy: "simple"
+    grouped_entities: true
+language:
+- nl
+---
+
+xlm-roberta model trained on ronec, performing 95 f1-Macro on test set.
+
+
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("EvanD/xlm-roberta-base-romanian-ner-ronec")
+ner_model = AutoModelForTokenClassification.from_pretrained("EvanD/xlm-roberta-base-romanian-ner-ronec")
+
+nlp = pipeline("ner", model=ner_model, tokenizer=tokenizer, aggregation_strategy="simple")
+example = "Numele meu este Amadeus Wolfgang și locuiesc în Berlin"
+
+ner_results = nlp(example)
+print(ner_results)
+
+# [
+#     {
+#         'entity_group': 'PER',
+#         'score': 0.9966806,
+#         'word': 'Amadeus Wolfgang',
+#         'start': 16,
+#         'end': 32
+#     },
+#     {'entity_group': 'GPE',
+#      'score': 0.99694663,
+#      'word': 'Berlin',
+#      'start': 48,
+#      'end': 54
+#      }
+# ]
+```