Update app.py

app.py

@@ -7,7 +7,7 @@ from transformers import DistilBertModel, DistilBertTokenizer, DistilBertForSequ
 # set_token("your_hugging_face_token_here")
 
 # Load your self-hosted model
-model_name = "22A223R/distilbert"
+model_name = "22A223R/bert-ITI110"
 tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
 model = DistilBertForSequenceClassification.from_pretrained(model_name,ignore_mismatched_sizes=True)
 #tokenizer = AutoTokenizer.from_pretrained('distilbert-base-uncased')
@@ -55,4 +55,4 @@ iface = gr.Interface(fn=classify_text,
                      description="This model is a fine-tuned DistilBERT model for detecting fake news. It was trained on the SST-2 dataset. It distinguishes real news from the fiction. Below are some preloaded examples you can choose from or enter your own.",
                      examples=examples)
 
-iface.launch()
+iface.launch()