Update README.md

README.md

@@ -33,7 +33,23 @@ This model is fine-tuned on the 'emotion' dataset to classify text into six emot
 
 ## Intended uses & limitations
 
-More information needed
+from transformers import pipeline
+import pandas as pd
+emt_clf = pipeline("text-classification", model="Swoodplays/emotion-classification")
+
+text = "I saw a movie today and it was really good."
+
+preds = emt_clf(text, return_all_scores=True)
+labels = ['sadness', 'joy', 'love', 'anger', 'fear', 'surprise']
+
+print(preds)
+
+preds_df = pd.DataFrame(preds[0])
+plt.bar(labels, 100 * preds_df["score"])
+plt.title(f'"{text}"')
+plt.xlabel("Classfied emotions")
+plt.ylabel("Class probability (%)")
+plt.show()
 
 ## Training and evaluation data