Update README.md

README.md

@@ -27,6 +27,20 @@ It achieves the following results on the evaluation set:
 - Validation Sparse Categorical Accuracy: 0.6434
 - Epoch: 4
 
+
+```
+{python}
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
+
+tokenizer = tokenizer = AutoTokenizer.from_pretrained("z-dickson/multilingual_sentiment_newspaper_headlines")
+m1 = TFAutoModelForSequenceClassification.from_pretrained("z-dickson/multilingual_sentiment_newspaper_headlines")
+sentiment_classifier = TextClassificationPipeline(tokenizer=tokenizer, model=m1)
+
+sentiment_classifier('Brazylia: Bolsonaro wci±ż nie uznał porażki. Jego zwolennicy blokuj± autostrady')
+[{'label': 'negative, 0', 'score': 0.9989686012268066}]
+```
+
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: