Update README.md

README.md

@@ -29,4 +29,31 @@ Number of hidden layers: 12
 Max position embeddings: 512
 Type vocab size: 2
 Vocab size: 30522
-The model uses the GELU activation function in its hidden layers and applies dropout with a probability of 0.1 to the attention probabilities to prevent overfitting.
+The model uses the GELU activation function in its hidden layers and applies dropout with a probability of 0.1 to the attention probabilities to prevent overfitting.
+
+## Example 
+
+```from transformers import AutoModelForSequenceClassification, TFAutoModelForSequenceClassification
+from transformers import AutoTokenizer
+import numpy as np
+from scipy.special import expit
+
+    
+MODEL = f"PavanDeepak/Topic_Classification"
+tokenizer = AutoTokenizer.from_pretrained(MODEL)
+
+model = AutoModelForSequenceClassification.from_pretrained(MODEL)
+class_mapping = model.config.id2label
+
+text = "I love chicken manchuria"
+tokens = tokenizer(text, return_tensors='pt')
+output = model(**tokens)
+
+scores = output[0][0].detach().numpy()
+scores = expit(scores)
+predictions = (scores >= 0.5) * 1
+
+
+for i in range(len(predictions)):
+  if predictions[i]:
+    print(class_mapping[i])```