Update README.md

README.md

@@ -34,11 +34,18 @@ from transformers import AutoTokenizer, AutoModelForMaskedLM
 
 tokenizer = AutoTokenizer.from_pretrained("robzchhangte/mizbert-25")
 model = AutoModelForMaskedLM.from_pretrained("robzchhangte/mizbert-25")
+```
+
+**To Predict Mask Token**
+```python
+from transformers import pipeline
+
+fill_mask = pipeline("fill-mask", model="robzchhangte/mizbert-25")
+
+sentence = "Pawn lam mawina aiin [MASK] a pawimawh zawk."
+predictions = fill_mask(sentence)
+
+for prediction in predictions:
+    print(prediction["sequence"].replace("[CLS]", "").replace("[SEP]", "").strip(), "| Score:", prediction["score"])
 
-# Example usage for masked language modeling
-inputs = tokenizer("What is the Mizo word for 'cat'?", return_tensors="pt")
-outputs = model(**inputs)
-masked_token_id = torch.argmax(outputs.logits[0, 1])
-predicted_word = tokenizer.convert_ids_to_tokens(masked_token_id)
-print("Predicted word:", predicted_word)
 ```