Update app.py

app.py

@@ -2,14 +2,15 @@
 
 import gradio as gr
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
+from transformers import BertTokenizer, BertLMHeadModel
 
+# Load pre-trained model and tokenizer
+tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
+model = BertLMHeadModel.from_pretrained('bert-base-uncased')
 
-model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
-tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
-
-
+# Define a function to generate text using the model
 def generate_text(input_text):
-    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+    input_ids = tokenizer.encode(input_text, return_tensors='pt')
     output = model.generate(input_ids)
     return tokenizer.decode(output[0], skip_special_tokens=True)