Update README.md

README.md

@@ -13,9 +13,6 @@ This model is fine-tuned for the task of masked language modeling in Persian. Th
 - **Model type:** Encoder
 - **Language(s) (NLP):** Persian
 
-### Direct Use
-
-The model is intended to be used directly for the task of predicting the most likely word for a masked token in Persian sentences. By simply providing a sentence with a masked word (e.g., <mask>), users can leverage the model for text completion, semantic prediction, and contextual understanding.
 
 ## How to Get Started with the Model
 
@@ -29,11 +26,11 @@ model = AutoModelForMaskedLM.from_pretrained("Behpouyan/Behpouyan-Fill-Mask")
 
 # List of 5 Persian sentences with a masked word (replacing a word with [MASK])
 sentences = [
-    "این کتاب بسیار <mask> است.",  # The book is very [MASK]
-    "مشتری همیشه از <mask> شما راضی است.",  # The customer is always satisfied with your [MASK]
-    "من به دنبال <mask> هستم.",  # I am looking for [MASK]
-    "این پروژه نیاز به <mask> دارد.",  # This project needs [MASK]
-    "تیم ما برای انجام کارها <mask> است."  # Our team is [MASK] to do the tasks
+    "این کتاب بسیار <mask> است.",  # The book is very <mask
+    "مشتری همیشه از <mask> شما راضی است.",  # The customer is always satisfied with your <mask
+    "من به دنبال <mask> هستم.",  # I am looking for <mask
+    "این پروژه نیاز به <mask> دارد.",  # This project needs <mask
+    "تیم ما برای انجام کارها <mask> است."  # Our team is <mask to do the tasks
 ]
 
 # Function to predict masked words