Update README.md

README.md

@@ -43,6 +43,28 @@ It achieves the following results on the test split:
 - Loss: 2.7633
 - Accuracy: 0.7479
 
+## How to use?
+
+You can use this model with the Transformers pipeline for text classification.
+
+```
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("tartuNLP/EstBERT128_sentiment")
+model = AutoModelForSequenceClassification.from_pretrained("tartuNLP/EstBERT128_sentiment")
+
+nlp = pipeline("text-classification", model=model, tokenizer=tokenizer)
+text = "Viimastel nädalatel on üha valjemaks muutunud hääled, mis läbisegi süüdistavad regionaalminister Madis Kallast röövretke korraldamises rikastesse valdadesse ja teisalt tegevusetuses."
+result = nlp(text)
+
+print(result)
+```
+
+```
+[{'label': 'negatiivne', 'score': 0.9999992847442627}]
+```
+
 ## Model description
 
 A single linear layer classifier is fit on top of the last layer [CLS] token representation of the EstBERT model. The model is fully fine-tuned during training.