Update README.md

README.md

@@ -17,6 +17,55 @@ The **swiss_german_pos_model** is a part-of-speech tagging model for Swiss Germa
 - Accuracy on Swiss German NOAH test split: 0.9587
 - Accuracy on German UD_German-HDT test set after GSW fine-tuning: 0.9553 (vs. 0.9814 at step 3 before GSW fine-tuning)
 
+### Usage
+
+```
+from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
+
+model = AutoModelForTokenClassification.from_pretrained("noeminaepli/swiss_german_pos_model")
+tokenizer = AutoTokenizer.from_pretrained("noeminaepli/swiss_german_pos_model")
+
+pos_tagger = pipeline('ner', model=model, tokenizer=tokenizer, aggregation_strategy="simple")
+tokens = pos_tagger("Worum söu mes ned chönne?")
+
+```
+
+Output:
+
+```
+[{'entity_group': 'ADV',
+  'score': 0.9627313,
+  'word': 'Worum',
+  'start': 0,
+  'end': 5},
+ {'entity_group': 'VERB',
+  'score': 0.98772717,
+  'word': 'söu',
+  'start': 6,
+  'end': 9},
+ {'entity_group': 'PRON',
+  'score': 0.99970305,
+  'word': 'mes',
+  'start': 10,
+  'end': 13},
+ {'entity_group': 'PART',
+  'score': 0.9999368,
+  'word': 'ned',
+  'start': 14,
+  'end': 17},
+ {'entity_group': 'VERB',
+  'score': 0.99841064,
+  'word': 'chönne',
+  'start': 18,
+  'end': 24},
+ {'entity_group': 'PUNCT',
+  'score': 0.9999957,
+  'word': '?',
+  'start': 24,
+  'end': 25}]
+
+```
+