Update README.md

README.md

@@ -65,7 +65,21 @@ This emotion classifier has been trained on 89_754 examples split into train, va
 
 ## Intended uses & limitations
 
-More information needed
+Usage:
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
+tokenizer = AutoTokenizer.from_pretrained('AdamCodd/distilbert-base-uncased-finetuned-emotion-balanced')
+model = AutoModelForSequenceClassification.from_pretrained('AdamCodd/distilbert-base-uncased-finetuned-emotion-balanced')
+
+# Create the pipeline
+emotion_classifier = pipeline('text-classification', model=model, tokenizer=tokenizer)
+
+# Now you can use the pipeline to classify emotions
+result = emotion_classifier("We are delighted that you will be coming to visit us. It will be so nice to have you here.")
+print(result)
+#[{'label': 'joy', 'score': 0.9983291029930115}]
+```
 
 ## Training and evaluation data