Update app.py

app.py

@@ -9,7 +9,7 @@ from transformers import DistilBertModel, DistilBertTokenizer, DistilBertForSequ
 # Load your self-hosted model
 model_name = "22A223R/distilbert"
 tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
-model = DistilBertForSequenceClassification.from_pretrained(model_name, ignore_mismatched_sizes=True)
+model = DistilBertForSequenceClassification.from_pretrained(model_name,ignore_mismatched_sizes=True)
 #tokenizer = AutoTokenizer.from_pretrained('distilbert-base-uncased')
 #model = AutoModelForSequenceClassification.from_pretrained(model_name,ignore_mismatched_sizes=True)
 
@@ -55,5 +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()